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Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross‐validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems. We present an analytical framework to estimate species density in aquatic systems using eDNA and monitoring data. We tested the performance with carp eDNA data obtained in an experimental setting. We also assessed the method in a natural setting, using stream salamander data collected in the field.

Defining lentic and lotic system types is critical for understanding hydrological, ecological, and biochemical processes. Traditional classification methods rely on non‐generalizable site‐specific parameters such as visual characteristics, historical inventory, and residence time. While machine learning and deep learning models address these challenges to some extent, they are limited by high data requirements, unverified training data sets, computational demands, and the inability to accurately detect inland waters smaller than 3 ha. To address this gap, this study introduces a novel Automated Data Efficient Morphometric Approach (ADEMA) that classifies inland waters into lentic and lotic system types globally up to 0.09 ha (33 times smaller than previous studies) using multi‐dimensional morphometric interpretations. ADEMA was developed and validated using 17,391 expert‐labeled inland waters spanning 66 globally diverse locations and compared against state‐of‐the‐art, comprehensively optimized machine learning, deep learning, and global models. Results show ADEMA equivalently performed to the machine learning and deep learning models, achieving F1 scores of 92%, 95%, and 71% in small, medium, and large inland waters, respectively. Across 17,391 expert‐labeled samples, ADEMA maintained a high performance with a precision of 89%, a recall of 99%, and an F1 score of 94%. Analysis across four decadal intervals (1991–2021) demonstrated ADEMA's temporal invariance, with consistently high F1 scores (90%–93%) and negligible omission errors (0%–2%). Further, ADEMA surpassed global classification products (average F1 score: 97% vs. 62%). These findings emphasize ADEMA's potential for accurately classifying global inland waters into lentic and lotic system types.

Microplastic pollution has been identified as a potential threat to the aquatic environment and humans globally, with widespread occurrence in ecosystems, including reservoirs that constitute a key role in ecosystem services for humans. However, the evaluation of microplastic pollution in reservoirs is limited, especially in inland fishing ground reservoirs. The spatial and temporal distributions of microplastics in surface water and sediment at 13 stations of the Ubolratana Reservoir, Thailand, were assessed during the wet and dry seasons. The abundance and morphological characteristics of the microplastics were identified and classified by color, shape, size and polymer type. Microplastic abundance in surface water and sediment ranged between 25 and 3363 particles/m3 and 6 and 81 particles/kg, respectively. Seasonal variations impacted microplastic abundance in surface water, while tourism activity in the reservoir also influenced the abundance and morphological characteristics of microplastics. A microplastic risk assessment showed that the pollution load index reached extremely high levels in surface water during the dry season in tourist areas. The results provide a database to assess the risk of microplastic contamination and to monitor plastic pollution in lentic ecosystems, including preserving the health of aquatic habitats.

With growing population and urbanization, there is an increasing exploitation of natural resources, and this often results to environmental pollution. In this review, the levels of heavy metal in lentic compartments (water, sediment, fishes, and aquatic plants) over the past two decades (1997–2017) have been summarized to evaluate the current pollution status of this ecosystem. In all the compartments, the heavy metals dominated are zinc followed by iron. The major reason could be area mineralogy and lithogenic sources. Enormous quantity of metals like iron in estuarine sediment is a very natural incident due to the permanently reducing condition of organic substances. Contamination of cadmium, lead, and chromium was closely associated with anthropogenic origin. In addition, surrounding land use and atmospheric deposition could have been responsible for substantial pollution. The accumulation of heavy metals in fishes and aquatic plants is the result of time-dependent deposition in lentic ecosystems. Moreover, various potential risk assessment methods for heavy metals were discussed. This review concludes that natural phenomena dominate the accumulation of essential heavy metals in lentic ecosystems compared to anthropogenic sources. Amongst other recent reviews on heavy metals from other parts of the world, the present review is executed in such a way that it explains the presence of heavy metals not only in water environment, but also in the whole of the lentic system comprising sediment, fishes, and aquatic plants.

Microplastics are widespread pollutants in freshwater ecosystems, yet comprehensive data on their occurrence across large geographic scales remains scarce. This nationwide study, therefore, examined microplastic ingestion in 621 individuals of non-native Gambusia holbrooki across 24 freshwater sites in Türkiye, selected to represent diverse hydrological types and anthropogenic pressures. Microplastic particles were extracted from the gastrointestinal tracts and analyzed for morphology, polymer type, size, and color using stereomicroscopy and ATR-FTIR spectroscopy. Fibers were the dominant shape (66%), followed by fragments (23%), films (9%), and spheres (2%). The most common polymer types were polyethylene terephthalate (PET, 40%) and polyethylene (PE, 28%), while black (35%) and blue (22%) were the most frequent colors. Over 80% of particles measured less than 1 mm in size. Microplastic loads were higher in lentic systems and areas influenced by agricultural or domestic discharge, highlighting spatial variability driven by land use and waterbody type. This pattern aligns with the ecology of G. holbrooki, whose surface-feeding behavior and preference for lentic waters likely increase its exposure to microplastics. These findings demonstrate the utility of G. holbrooki as a bioindicator of localized microplastic pollution. Future monitoring programs should integrate land-use data and adopt multi-species approaches to capture the full spectrum of contamination. This study supports the inclusion of adaptable, invasive species in cost-effective freshwater pollution assessments and informs targeted management strategies. Graphical Abstract

Plastic debris is thought to be widespread in freshwater ecosystems globally 1 . However, a lack of comprehensive and comparable data makes rigorous assessment of its distribution challenging 2 , 3 . Here we present a standardized cross-national survey that assesses the abundance and type of plastic debris (>250 μm) in freshwater ecosystems. We sample surface waters of 38 lakes and reservoirs, distributed across gradients of geographical position and limnological attributes, with the aim to identify factors associated with an increased observation of plastics. We find plastic debris in all studied lakes and reservoirs, suggesting that these ecosystems play a key role in the plastic-pollution cycle. Our results indicate that two types of lakes are particularly vulnerable to plastic contamination: lakes and reservoirs in densely populated and urbanized areas and large lakes and reservoirs with elevated deposition areas, long water-retention times and high levels of anthropogenic influence. Plastic concentrations vary widely among lakes; in the most polluted, concentrations reach or even exceed those reported in the subtropical oceanic gyres, marine areas collecting large amounts of debris 4 . Our findings highlight the importance of including lakes and reservoirs when addressing plastic pollution, in the context of pollution management and for the continued provision of lake ecosystem services. Analysis of plastic debris found in surface waters shows that lakes and reservoirs in densely populated and urbanized regions, as well as those with elevated deposition areas, are particularly vulnerable to plastic contamination.

Hematological studies of fishes are useful in the diagnosis of many diseases as well as investigation of the extent of damage to the blood. These parameters act as efficient and insightful index to examine health status, physiological and pathological changes occurring in various fishes, i.e., metabolic perturbations in fish body thereby acting as non-specific biomarkers in the field of environmental toxicology, deficiencies and chronic stress in natural as well as aquaculture systems and checking water quality. The assessments of these blood parameters help the biologists to understand the fish homeostasis and biomonitoring of severe and chronic patho-physiological changes inferable to nutrition, water quality, or disease so as to establish the normal reference values of different species and determine systematic relationships among them. Lot of work on various aspects of hematological parameters and their relation with ecological factors has been reported on several fish species from different parts of the world. Each study attributes one or other factors responsible for variation in hematological parameters among different fish species. Therefore, in the present study, an attempt has been made to compile the information about the hematological studies of various fish species reported from different parts of the world, and through this study, a general overview has been generated about the major factors responsible for the variation in hematological parameters of fish. The review provides an insight to the characteristics of hematological values showing that fluctuating internal environment of the fish, along with other intrinsic (age, body size, the cycle of sexual maturity, health condition, nutritional state, species) and extrinsic factors (temperature, stress, season, dissolved oxygen, water quality, lotic or lentic environment, stocking density, photoperiod, sampling conditions, laboratory techniques), are the reasons of huge variability of hematological parameters in fishes.

Great attention has been given to freshwater ecosystems worldwide due to the increased exploitation of water resources and the degradation of water quality. This study was aimed to demonstrate the phytoplankton-stressor interactions using multivariate approaches and assess the ecological conditions of 28 sampling stations of 12 lentic ecosystems (five lakes and seven reservoirs) in the western Mediterranean basin using phytoplankton indices in dry and rainy seasons 2018. Freshwater and brackish water systems were separately ordinated by canonical correspondence analysis. The brackish ecosystems were under pressures of Ar (arsenic), N-N O 2 − (nitrite), Ca (calcium), EC (electrical conductivity), Cl (chloride), B (boron), etc., whereas shallow freshwater ecosystems were associated with total organic carbon. These factors had significant effects on phytoplankton distribution among lentic ecosystems on the basin. Ecological associations of phytoplankton assemblages varied in the western Mediterranean basin during the study. Pseudanabaena catenata and Palatinus apiculatus , considered tolerant taxa, are associated with higher Ar, EC, and V (vanadium) while Desmodesmus abundans and Microcystis flos-aquae are related to total organic carbon. The modified PTI (phytoplankton trophic index) had the highest correlation coefficient value. Scores of the PTI varied from 2.02 in Çavdır Reservoir to 2.59 in Lake Kocagöl. Results of phytoplankton indices indicated that two (Gölhisar and Yazır) lakes and two (Yapraklı and Çavdır) reservoirs were classified as Good, and three lakes and five reservoirs were classified as Moderate condition. Other predicted classifications (high, poor, and bad) by phytoplankton metrics were not represented. The modified PTI could be a suitable phytoplankton metric for assessing the ecological status of lentic ecosystems in the Mediterranean system according to its highest correlation coefficient value. Overall, the results of this limno-ecological study demonstrated that responses of phytoplankton taxa to explanatory factors provide crucial ecological information about their ecology and to estimate the ecological status of lentic ecosystems.

Recent climate-change research largely confirms the impacts on US ecosystems identified in the 2009 National Climate Assessment and provides greater mechanistic understanding and geographic specificity for those impacts. Pervasive climate-change impacts on ecosystems are those that affect productivity of ecosystems or their ability to process chemical elements. Loss of sea ice, rapid warming, and higher organic inputs affect marine and lake productivity, while combined impacts of wildfire and insect outbreaks decrease forest productivity, mostly in the arid and semi-arid West. Forests in wetter regions are more productive owing to warming. Shifts in species ranges are so extensive that by 2100 they may alter biome composition across 5-20% of US land area. Accelerated losses of nutrients from terrestrial ecosystems to receiving waters are caused by both winter warming and intensification of the hydrologic cycle. Ecosystem feedbacks, especially those associated with release of carbon dioxide and methane release from wetlands and thawing permafrost soils, magnify the rate of climate change.

The health of an ecosystem can be evaluated based on its ecological characteristics and intrinsic biological quality. Furthermore, as nutrients are easily accessible by the algal cells in an aquatic ecosystem, the biochemical composition of an algal cell also varies accordingly with the ecological condition of its habitat. This study was carried out to understand the impact of seasonal variation of physicochemical parameters on the microalgal diversity and composition of five freshwater ponds in Mangalore, India. The diversity indices, viz. Shannon’s (0.88–3.42), Margalef’s (0.16–3.6), and Simpson’s dominance index (0.47–0.96), were analyzed using PAST. A prominent variation in both the abundance and diversity of species was observed during the study period. About 150 species of algae belonging to Cyanophyceae, Chlorophyceae, Bacillariophyceae, Euglenophyceae, Xanthophyceae, and Rhodophyceae were recorded. Of these groups, Chlorophyceae, specifically, desmids formed the dominant flora. Zygnematales were dominant during monsoon, while Chroococcales was the most dominant group during the post-monsoon season. Ecological conditions like temperature, pH, dissolved gases, and inorganic salts were found to impact the growth and abundance of microalgae. The ecological parameters showed a prominent effect on microalgal diversity. The results indicated that site SR was the least polluted and most diverse among the lentic habitats studied. It also had lesser noxious algal species which could be attributed to its nutrient composition.