Underlying mechanisms governing on distribution and stratification of DOM during seasonal freeze-thaw cycles

During the freeze-thaw cycles of ice-covered lakes, DOM undergoes a series of transformations including enrichment, dispersion, and filtration. However, the mechanisms and influence factors on lake pollution processes remain unclear. Therefore, this study investigates the distribution of DOM components and elucidate the role of ice-layer sieving its mechanisms within ice-water-sediments. Study identifies significant variations in the characteristics of DOM, protein-like substances tend to migrate towards the ice layer, while humic-like substances predominantly remain in water. This selective distribution is primarily influenced by the physical and chemical properties of DOM during the freezing process. The ice layer acts as a sieve, allowing smaller molecules such as protein-like substances to pass through more easily, while larger molecules like humic-like substances are retained in the water. Additionally, Temperature plays a pivotal role in affecting the contents of DOM. As the temperature decreases, the solubility of DOM decreases, leading to its precipitation and enrichment in sediments. Conversely, an increase in temperature can facilitate the release of DOM from sediments into the water. Furthermore, high content of total dissolved solids can affect the solubility and stability of DOM, potentially leading to changes in its composition and distribution. These insights provide a deeper understanding of the complex interplay between thermal processes and chemical dynamics within ice-covered aquatic environments. They offered valuable insights into the behavior of organic pollutants in frozen lake systems. The findings have potential implications for environmental management strategies aimed at mitigating the effects of climate.

Cycles of solar ultraviolet radiation favor periodic expansions of cyanobacterial blooms in global lakes

Global warming and eutrophication are known to increase the prevalence of cyanobacterial blooms, posing a severe threat to the ecological stability and sustainability of water bodies. The long-term (over an annual time frame) effect of UV radiation on cyanobacterial blooms in lakes are rarely discussed though the substantial effects of high-intensity UV radiation on the growth inhibition of marine phytoplankton were studied. Here, we employed the datasets on surface solar UV radiation, nitrogen and phosphorus concentrations, and the annual scales and frequencies of cyanobacterial blooms in lakes across long-term spatial scales to probe the relationship of UV radiation with cyanobacterial blooms. The results indicated that enhanced solar UV radiation may unintentionally stimulate cyanobacterial growth and favor the expansions of cyanobacterial blooms in lakes around the world. The fluctuating UV radiation significantly affects the annual scales of cyanobacterial blooms in both eutrophic and oligotrophic lakes. Solar UV radiation enhances the positive impact of rising phosphorus levels on cyanobacterial blooms because UV radiation prompts the synthesis of polyphosphate in cyanobacteria cells, which helps cyanobacteria to alleviate the stress of UV light. The scales of cyanobacterial blooms are significantly impacted by solar UV radiation intensities as opposed to the annual frequency of cyanobacterial blooms. Furthermore, solar UV radiation fluctuation with a 9-year period over a 14-year main cycles significantly affects the periodicities of cyanobacterial blooms in global lakes, which provides a basis for predicting the peak value of the scales of cyanobacterial blooms in lakes. These findings opened up new avenues of inquiry into the mechanism and management strategies of cyanobacterial blooms in lakes worldwide.

Eutrophication evolution of lakes in China: Four decades of observations from space

The lake eutrophication is highly variable in both time and location, and greatly restricts the sustainable development of water resources. The lack of national eutrophication evaluation for multi-scale lakes limits the pertinent governance and sustainable management of water quality. In this study, a remote sensing approach was developed to capture 40-year dynamics of trophic state index (TSI) for nationwide lakes in China. 32% of lakes (N = 1925) in China were eutrophic and 26% were oligotrophic, and a longitudinal pattern was discovered, with the 40-year average TSI of 62.26 in the eastern plain compared to 23.72 in the Tibetan Plateau. A decreasing trend was further observed in the past four decades with a correlation of -0.16, which was mainly discovered in the Tibetan Plateau lakes (r > -0.90, p < 0.01). The contribution of climate change and human activities was quantified and varied between lake zones, with anthropogenic factors playing a dominant role in the east plain lakes (88%, N = 473) and large lakes are subject to a more complex driving mechanism (≥ 3 driving factors). The study expands the spatiotemporal scale for eutrophication monitoring and provides an important base for strengthening lake management and ecological services.

Sedimentary ancient DNA reveals the impact of anthropogenic land use disturbance and ecological shifts on fish community structure in small lowland lake

Freshwater fish biodiversity and abundance are decreasing globally. The drivers of decline are primarily anthropogenic; however, the causative links between disturbances and fish community change are complex and challenging to investigate. We used a suite of sedimentary DNA methods (droplet digital PCR and metabarcoding) and traditional paleolimnological approaches, including pollen and trace metal analysis, ITRAX X-ray fluorescence and hyperspectral core scanning to explore changes in fish abundance and drivers over 1390 years in a small lake. This period captured a disturbance trajectory from pre-human settlement through subsistence living to intensive agriculture. Generalized additive mixed models explored the relationships between catchment inputs, internal drivers, and fish community structure. Fish community composition distinctly shifted around 1350 CE, with the decline of a sensitive Galaxias species concomitant with early land use changes. Total fish abundance significantly declined around 1950 CE related to increases in ruminant bacterial DNA (a proxy for ruminant abundance) and cadmium flux (a proxy for phosphate fertilizers), implicating land use intensification as a key driver. Concurrent shifts in phytoplankton and zooplankton suggested that fish communities were likely impacted by food web dynamics. This study highlights the potential of sedDNA to elucidate the long-term disturbance impacts on biological communities in lakes.

Analysis of taiga and tundra lake browning trends from 2002 to 2021 using MODIS data

Lakes in taiga and tundra regions may be silently undergoing changes due to global warming. One of those changes is browning in lake color. The browning interacts with the carbon cycle, ecosystem dynamics, and water quality in freshwater systems. However, spatiotemporal variabilities of browning in these regions have not been well documented. Using MODIS remote sensing reflectance at near ultraviolet wavelengths from 2002 to 2021 on the Google Earth Engine platform, we quantified long-term browning trends across 7616 lakes (larger than 10 km2) in taiga and tundra biomes. These lakes showed an overall decreased trend in browning (Theil-Sen Slope = 0.00015), with ∼36% of these lakes showing browning trends, and ∼1% of these lakes showing statistically significant (p-value <0.05) browning trends. The browning trends more likely occurred in small lakes in high latitude, low ground ice content regions, where air temperature increased and precipitation decreased. While temperature is projected to increase in response to climate change, our results provide one means to understand how biogeochemical cycles and ecological dynamics respond to climate change.

Application of diffusive gradient in thin films probes to monitor trace levels of labile methylmercury in freshwaters

This study aimed to optimize the methods for sampling and analyzing methylmercury (MeHg) concentrated within diffusive gradients in thin films (DGT) and its application to different water bodies. We explored the elution solution for MeHg, comprised of 1.13 mM thiourea and 0.1M HCl, optimizing its volume to 50 mL. In addition, we found that it is necessary to analyze the entire extraction solution after adjusting its pH, to ensure completion of the ethylation reaction. The DGT samplers were deployed in two distinct aquatic environments (i.e., Okjeong Lake and Nakdong River) for up to 6 weeks, and this study demonstrated to predict the time-weighted average concentration with a diffusion coefficient of 7.65 × 10-6 cm2 s-1 for MeHg in the diffusive gel. To assess the diffusive boundary layer (DBL) effects, the DGT samplers with different agarose diffusive gel thickness were deployed. The mass of MeHg accumulated in the DGT resin at a given time decreased with increasing diffusive gel thickness, because of creating longer diffusion pathways within thicker gels. The labile MeHg concentration estimated by the DGT in Okjeong Lake and Nakdong River are found in the range of 61-111 and 55-105 pg L-1, respectively, which were found to be similar to the grab sampling data. Additionally, this study evaluated depth-dependent MeHg in Okjeong Lake. The vertical profile results showed that the concentration of MeHg at the depth of 2.3 and 15.7 m are about 1.5 and 4.6 times of the DGT installed at 0.3 m of the surface layer, respectively, suggesting potential mercury methylation in deep waters. These findings have practical implications for predicting bioavailability, assessing risks, and formulating strategies for water body management and contamination remediation.

Setting nutrient boundaries to protect aquatic communities: The importance of comparing observed and predicted classifications using measures derived from a confusion matrix

Defining nutrient thresholds that protect and support the ecological integrity of aquatic ecosystems is a fundamental step in maintaining their natural biodiversity and preserving their resilience. With increasing catchment pressures and climate change, it is more important than ever to develop clear methods to establish thresholds for status classification and management of waters. This must often be achieved using complex data and should be robust to interference from additional pressures as well as ameliorating or confounding conditions. We use both artificial and real data to examine challenges in setting nutrient thresholds in unbalanced and skewed data. We found significant advantages to using binary logistic regression over other techniques. However, one of the key challenges is objectively selecting a probability from which to derive the nutrient threshold. For this purpose, the examination of the proportions of matching and mismatching status classifications of nutrients and a biological quality element using a confusion matrix is a key step that should be more widely adopted in threshold selection. We examined a large array of statistical measures of classification accuracy and their performance over combinations of skewness and imbalance in the data. The most appropriate threshold probability is a compromise between maximising overall classification accuracy and reducing mismatches expressed as commission (false positives) without excessive omission (false negatives). An application to a lake type indicated total phosphorus thresholds that would be around 50 μg l-1 lower than the threshold achieved by an 'unguided' approach, indicating that this approach is a very significant development meriting attention from national authorities responsible for water management.

Imbalance in lake variability but not embodying driving factors on the Qinghai-Tibetan Plateau calls on heterogeneous lake management

Comprehensive regional remote analysis tends to neglect lakes in exorheic basins on the Qinghai-Tibetan Plateau (QTP), and a concurrent lack of discussions on whether there exist imbalanced explanations for the driving forces of both internal and external lakes is also present. We integrate multisourced lake datasets, high-resolution information, and available altimetry datasets to establish multiple mathematical models to meta-simulate lake volume changes, extend current lake variation datasets, and quantify the imbalance of variations and factors driving the water mass budget. The results showed that the primary cause of lake variations in QTP is net precipitation (57.75 ± 31.46%), followed by glacier runoff (33.53 ± 31.42%), and permafrost (8.34 ± 7.87%). Even though glacier runoff is currently considered as a weak factor of lake variation, heterogeneous results call for remaining attention in glacier-induced lake basins. Imbalance embodying in lake variability but not in contributions of driving factors, which calls for special lake management ways in different watersheds.

Making waves: The sensitivity of lakes to brownification and issues of concern in ecological status assessment

Brownification or increasing water colour is a common problem in aquatic ecosystems. It affects both physico-chemical properties and biotic communities of the impacted waters. A common view is that lakes having low background water colour are most sensitive to brownification. In this article, we show that although low-colour and high-colour lakes respond differently to brownification, the effects on biotic communities can be strong irrespective of water colour. For phytoplankton production, the effect of brownification can be positive at low colour and negative at high colour, the relative effect being strongest at high colour. For fish foraging, the disturbance per increasing unit of colour may also be highest at high-colour conditions. Additionally, the presently used classification systems mostly describe the effects of eutrophication and do not account for the effects of brownification. Studies on the whole colour range of lakes are needed and indicators used in the ecological status assessment of lakes must be developed to reveal the effects of brownification. Indicators distinguishing the effects of brownification from those of eutrophication are especially needed.

Branched GDGT-based temperature calibrations from Central European lakes

Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are common in lake sediments, where they are frequently employed to infer mean annual air temperatures (MAAT) or air temperatures of months above freezing (MAF) using the MBT'5Me lipid paleothermometer. The reliable reconstruction of such temperatures, however, requires robust calibration functions. Here, we investigated brGDGT distributions in surface sediments from 41 freshwater lakes located along an altitudinal gradient across the Alps (Central Europe) and spanning a MAAT range from 1.3 to 12.9 °C. Linear regression analysis demonstrates that fractional abundances of brGDGTs are strongly correlated with MAAT and MAF allowing to establish regional MBT'5Me-based transfer functions: MAAT (°C) = -2.19 + 31.91 × MBT'5Me (r2 = 0.72; RMSE = 1.51 °C) and MAF (°C) = 4.81 + 15.64 × MBT'5Me (r2 = 0.64, RMSE = 0.92 °C). Stepwise forward selection yielded the following, alternate temperature calibrations: MAAT (°C) = 7.11 + 67.66 × Ib - 13.54 × IIIa (r2 = 0.72; RMSE = 1.47 °C) and MAF (°C) = 5.19 + 16.22 × Ia (r2 = 0.66; RMSE = 0.98 °C). Our results demonstrate that the above calibration functions allow precise temperature reconstructions using lacustrine sediment records. However, our data also show that high-altitude lakes are more prone to warm bias and that lakes characterized by comparatively high abundances of 6-methyl brGDGTs show aberrant behaviors with temperature offsets up to ∼7 °C. Determining the IR6Me, as an independent control complementary to the MBT'5Me, is thus essential to validate the robustness of brGDGT-based temperature reconstructions of past climates. A cut-off value of 0.50 for the IR6Me is here proposed, after which MBT'5Me-reconstructed MAATs from lacustrine archives should be regarded as unreliable.

Inputs, amplification and sinks of perfluoroalkyl substances at coastal Antarctica

The sources, biogeochemical controls and sinks of perfluoroalkyl substances, such as perfluoroalkyl acids (PFAAs), in polar coastal regions are largely unknown. These were evaluated by measuring a large multi-compartment dataset of PFAAs concentrations at coastal Livingston and Deception Islands (maritime Antarctica) during three austral summers. PFAAs were abundant in atmospheric-derived samples (aerosols, rain, snow), consistent with the importance of atmospheric deposition as an input of PFAAs to Antarctica. Such PFAAs deposition was unequivocally demonstrated by the occurrence of PFAAs in small Antarctic lakes. Several lines of evidence supported the relevant amplification of PFAAs concentrations in surface waters driven by snow scavenging of sea-spray aerosol-bound PFAAs followed by snow-melting. For example, vertical profiles showed higher PFAAs concentrations at lower-salinity surface seawaters, and PFAAs concentrations in snow were significantly higher than in seawater. The higher levels of PFAAs at Deception Island than at Livingston Island are consistent with the semi-enclosed nature of the bay. Concentrations of PFOS decreased from 2014 to 2018, consistent with observations in other oceans. The sink of PFAAs due to the biological pump, transfer to the food web, and losses due to sea-spray aerosols alone are unlikely to have driven the decrease in PFOS concentrations. An exploratory assessment of the potential sinks of PFAAs suggests that microbial degradation of perfluoroalkyl sulfonates should be a research priority for the evaluation of PFAAs persistence in the coming decade.

A graph-based modeling framework for tracing hydrological pollutant transport in surface waters

Anthropogenic pollution of hydrological systems affects diverse communities and ecosystems around the world. Data analytics and modeling tools play a key role in fighting this challenge, as they can help identify key sources as well as trace transport and quantify impact within complex hydrological systems. Several tools exist for simulating and tracing pollutant transport throughout surface waters using detailed physical models; these tools are powerful, but can be computationally intensive, require significant amounts of data to be developed, and require expert knowledge for their use (ultimately limiting application scope). In this work, we present a graph modeling framework - which we call HydroGraphs - for understanding pollutant transport and fate across waterbodies, rivers, and watersheds. This framework uses a simplified representation of hydrological systems that can be constructed based purely on open-source data (National Hydrography Dataset and Watershed Boundary Dataset). The graph representation provides a flexible intuitive approach for capturing connectivity and for identifying upstream pollutant sources and for tracing downstream impacts within small and large hydrological systems. Moreover, the graph representation can facilitate the use of advanced algorithms and tools of graph theory, topology, optimization, and machine learning to aid data analytics and decision-making. We demonstrate the capabilities of our framework by using case studies in the State of Wisconsin; here, we aim to identify upstream nutrient pollutant sources that arise from agricultural practices and trace downstream impacts to waterbodies, rivers, and streams. Our tool ultimately seeks to help stakeholders design effective pollution prevention/mitigation practices and evaluate how surface waters respond to such practices.

Ponds as experimental arenas for studying animal movement: current research and future prospects

Animal movement is a multifaceted process that occurs for multiple reasons with powerful consequences for food web and ecosystem dynamics. New paradigms and technical innovations have recently pervaded the field, providing increasingly powerful means to deliver fine-scale movement data, attracting renewed interest. Specifically in the aquatic environment, tracking with acoustic telemetry now provides integral spatiotemporal information to follow individual movements in the wild. Yet, this technology also holds great promise for experimental studies, enhancing our ability to truly establish cause-and-effect relationships. Here, we argue that ponds with well-defined borders (i.e. "islands in a sea of land") are particularly well suited for this purpose. To support our argument, we also discuss recent experiences from studies conducted in an innovative experimental infrastructure, composed of replicated ponds equipped with modern aquatic telemetry systems that allow for unparalleled insights into the movement patterns of individual animals.

Assessing the suitability of lakes and reservoirs for recreation using Landsat 8

Water clarity has long been used as a visual indicator of the condition of water quality. The clarity of waters is generally valued for esthetic and recreational purposes. Water clarity is often assessed using a Secchi disk attached to a measured line and lowered to a depth where it can be no longer seen. We have applied an approach which uses atmospherically corrected Landsat 8 data to estimate the water clarity in freshwater bodies by using the quasi-analytical algorithm (QAA) and Contrast Theory to predict Secchi depths for more than 270 lakes and reservoirs across the continental US. We found that incorporating Landsat 8 spectral data into methodologies created to retrieve the inherent optical properties (IOP) of coastal waters was effective at predicting in situ measures of the clarity of inland water bodies. The predicted Secchi depths were used to evaluate the recreational suitability for swimming and recreation using an assessment framework developed from public perception of water clarity. Results showed approximately 54% of the water bodies in our dataset were classified as "marginally suitable to suitable" with approximately 31% classed as "eminently suitable" and approximately 15% classed as "totally unsuitable-unsuitable". The implications are that satellites engineered for terrestrial applications can be successfully used with traditional ocean color algorithms and methods to measure the water quality of freshwater environments. Furthermore, operational land-based satellite sensors have the temporal repeat cycles, spectral resolution, wavebands, and signal-to-noise ratios to be repurposed to monitor water quality for public use and trophic status of complex inland waters.

Mechanisms shaping dissolved organic matter and microbial community in lake ecosystems

Lakes are active components of the global carbon cycle and host a range of processes that degrade and modify dissolved organic matter (DOM). Through the degradation of DOM molecules and the synthesis of new compounds, microbes in aquatic environments strongly and continuously influence chemodiversity, which can feedback to influence microbial diversity. Developing a better understanding of the biodiversity patterns that emerge along spatial and environmental gradients is one of the key objectives of community ecology. A changing climate may affect ecological feedback, including those that affect microbial communities. To maintain the function of a lake ecosystem and predict carbon cycling in the environment, it is increasingly important to understand the coupling between microbial and DOM diversity. To unravel the biotic and abiotic mechanisms that control the structure and patterns of DOM and microbial communities in lakes, we combined high-throughput sequencing and ultra-high resolution mass spectrometry together with a null modeling approach. The advantage of null models is their ability to evaluate the relative influences of stochastic and deterministic assembly processes in both DOM and microbial community assemblages. The present study includes spatiotemporal signatures of DOM and the microbial community in six temperate lakes contrasting continental and Mediterranean climates during the productive season. Different environmental conditions and nutrient sources characterized the studied lakes. Our results have shown high covariance between molecular-level DOM diversity and the diversity of individual microbial communities especially with diversity of microeukaryotes and free-living bacteria indicating their dynamic feedback. We found that the differences between lakes and climatic regions were mainly reflected in the diversity of DOM at the molecular formula-level and the microeukaryota community. Furthermore, using null models the DOM assembly was governed by deterministic variable selection operating consistently and strongly within and among lakes. In contrast, microbial community assembly processes were highly variable across lakes with different trophic status and climatic regions. Difference in the processes governing DOM and microbial composition does not indicate weak coupling between these components, rather it suggests that distinct factors may be influencing microbial communities and DOM assemblages separately. Further understanding of the DOM-microbe coupling (or lack thereof) is key to formulating predictive models of future lake ecology and function.

Sediment core records and impact factors of polycyclic aromatic hydrocarbons in Chinese lakes

Lake sediment is a natural sink for polycyclic aromatic hydrocarbons (PAHs). PAH sedimentation characteristics and their impact factors of Chinese lakes have mainly been qualitative assessed. However, quantitative impacts of PAH sedimentation from different factors have not been well analyzed. To fill this gap, we screened PAH sedimentation records from the literature, for 51 lakes in China and other regions of the world, to identify historical concentration variation and the impact factors of PAHs in different regions, in lake sediment. The results show that PAH concentrations in the sediment core in the selected Chinese lakes (478 ± 812 ng/g dry weight (dw)) were significantly lower than those in North America (5518 ± 6572 ng/g dw) and Europe (3817 ± 4033 ng/g dw). From 1900 to 2015, most of the lakes in China showed an increasing trend of PAH sedimentation concentrations, with the lakes in Southeastern China showed a decreasing trend of PAH concentration in the period of 2001-2015, which was later than the peak times shown in Western countries (1941-1970). The 2-3-ring PAHs were the main components in the sediment core of Chinese lakes, but the proportion to the total PAHs decreased from 72% in 1900-1940 to 55% in 2001-2015. Generalized additive modeling (GAM) was adopted to simulate the associations between PAH sedimentation records and the impact factors. There are large regional variations of economic and industrial development in China. The impact factors of PAH accumulation in the lake sediments differ in different regions. However, population and the consumption of coal, pesticides, and fertilizer were identified to be the most important impact factors influencing PAH sedimentation. The Chinese government needs to strengthen control measures on pollutant discharge to reduce the anthropogenic impact of PAH sedimentation in lakes.

Minor impacts of rain on methane flux from hemiboreal, boreal, and subarctic lakes

Methane (CH4) emissions (FCH4) from northern freshwater lakes are not only significant but also highly variable in time and one driver variable suggested to be important is precipitation. Rain can have various, potentially large effects on FCH4 across multiple time frames, and verifying the impact of rain on lake FCH4 is key to understand both contemporary flux regulation, and to predict future FCH4 related to possible changes in frequency and intensity of rainfall from climate change. The main objective of this study was to assess the short-term impact of typically occurring rain events with different intensity on FCH4 from various lake types located in hemiboreal, boreal, and subarctic Sweden. In spite of high time resolution automated flux measurements across different depth zones and covering numerous commonly types of rain events in northern areas, in general, no strong impact on FCH4 during and within 24 h after the rainfall could be observed. Only in deeper lake areas and during longer rain events FCH4 was weakly related to rain (R2 = 0.29, p < 0.05), where a minor FCH4 decrease during the rain was identified, suggesting that direct rainwater input, during greater rainfall, may decrease FCH4 by dilution of surface water CH4. Overall, this study indicates that typical rain events in the studied regions have minor direct short-term effects on FCH4 from northern lakes and do not enhance FCH4 from shallow and deeper parts of lakes during and up to 24-h after the rainfall. Instead, other factors such as wind speed, water temperature and pressure changes were more strongly correlated with lake FCH4.

Sedimentary processes, metal enrichment and potential ecological risk of metals in lacustrine sediments of Svalbard, Arctic

The Svalbard archipelago is a glacial environment bestowed with various lakes that act as a natural archive for understanding environmental conditions. The accumulation of sediments in lake basins and their distribution are affected by different mechanisms. Therefore, to understand the distribution of sediments, factors controlling the transport and metal enrichment in the lake environment, core sediments were studied from four lakes (L-A, L-1, L-2 and L-3). Also, the potential ecological risk index (PERI) was computed to determine the impact of metal enrichment on the sediment-associated biota. The results obtained showed that the distribution of trace elements was mainly controlled by the major elements like Al, Ti, Fe, and Mn attributed to their lithogenic origin. Index of geoaccumulation (Igeo) of all four lakes showed a moderate level of enrichment of metals like Cr and Cd indicating an enhanced supply of these metals probably from the catchment rocks and anthropogenic activities. A comparison of metals with Arctic Sediment Quality Guidelines (ASQGs) showed that Cd, Cr and Cu were enriched in the sediments of all the cores indicating the occurrence of adverse biological effects. Furthermore, a potential ecological risk index (PERI) revealed high Cd indicating considerable potential ecological risk to the sediment-associated biota. Thus, trace element influx to the lakes needs to be monitored with due emphasis on Cd contamination.

A new diatom-based multimetric index to assess lake ecological status

Eutrophication impairs lake ecosystems at a global scale. In this context, as benthic microalgae are well-established warnings for a large range of stressors, particularly nutrient enrichment, the Water Framework Directive required the development of diatom-based methods to monitor lake eutrophication. Here, we present the diatom-based index we developed for French lakes, named IBDL (Indice Biologique Diatomées en Lacs). Data were collected in 93 lakes from 2015 to 2020. A challenge arose from the discontinuous pressure gradient of our dataset, especially the low number of nutrient-impacted lakes. To analyze the data we opted for the so-called "Threshold Indicator Taxa ANalysis" method, which makes it possible to determine a list of "alert taxa." We obtained a multimetric index based on specific pressure gradients (Kjeldahl nitrogen, suspended matter, biological oxygen demand, and total phosphorous). Considering the European intercalibration process, the very good correlation between IBDL and the common metric (R2 from 0.52 to 0.87 according to the lake alkalinity type) makes us very confident in our ability to match future IBDL quality thresholds with European standards. The IBDL proved at last to be particularly relevant as it has a twofold interest: an excellent relationship with total phosphorus (R2 from 0.63 to 0.83 according to the lake alkalinity type) and a possible application to any lake metatype. Its complementarity with macrophyte-based indices moreover justifies the use of at least two primary producer components for lake ecological status classification.

The distribution of diatom assemblages with the effects of environmental parameters and ecological status assessment based on diatom indices in the lentic systems of the Akarçay and Asi Basins (Türkiye)

In order to detect the effects of different stressors on the littoral diatom assemblages and biodiversity of the lentic systems in two different basins in Türkiye, 15 lentic systems in the Akarçay and Asi basins were sampled three times (spring, summer, and fall) for littoral diatoms and environmental variables. The biological assessment of these sites was also evaluated using 9 different river and lake diatom indices. Based on the total phosphorus (TP), total nitrogen (TN), electrical conductivity (EC), salinity (SAL) values, and dominant diatom species, three lentic systems in Akarçay Basin (Lake Eber, 26 Ağustos Pond, and Lake Karamık) were more eutrophic and under the pressure of anthropogenic and climatic (precipitation) stressors. Trophic diatom index for lakes (TDIL) showed a higher correlation with TN and TP and was the most effective index in explaining ecological quality in 15 lentic systems. The species richness of diatoms was also negatively affected by EC and SAL values. The lentic systems of the two basins were separated from each other based on the species composition and the distribution of the dominant species with the effect of altitude (ALT). Considering the distribution of diatom assemblage of the lentic systems in these two basins, anthropogenic, climatic, and geographical factors have become prominent to shape the diatom community structure.

Impact of ecosystem metabolism on CO2 emissions: Insights from high-resolution time series of pH measured in situ

Lakes and reservoirs are important sources/sinks of atmospheric CO2. Primary production and respiration transforming inorganic to organic carbon and vice versa alter CO2 concentrations in the surface waters and thus affect CO2 emissions. Here we investigate the link between net-production (NEP) and CO2 concentrations and emissions at high temporal resolution over more than two months in a German pump storage reservoir. Continuous in-situ pH measurements in combination with few alkalinity measurements provided concentrations of CO2 and dissolved inorganic carbon (DIC) at high temporal resolution over more than 75 days. Time series of metabolic rates of carbon were determined with an open-water diel pH technique, which utilizes the diel changes in DIC obtained from the observed diel changes in pH and data on alkalinity. During the measuring period, average NEP was positive and CO2 concentrations were typically substantially under-saturated. On average, the reservoir acted as a sink for CO2, whereby CO2 uptake was 39% larger in the evening than in the morning. Only few consecutive days with negative NEP were sufficient to turn the reservoir temporally into a source of CO2. Therefore, the average CO2 uptake determined from continuous data can be 80% larger to 30% smaller than estimates of average uptake based on bi-weekly data. Daily mean NEP explained only 9% and 4% of the variance of daily mean DIC and CO2. Note that NEP is proportional to the time derivative of DIC and therefore not expected to correlate well with DIC in general. Because CO2 changes nonlinearly with DIC, NEP explains less variance of CO2 than of DIC. Numerical experiments confirmed the arguments above and revealed that at positive average NEP the total CO2 uptake over several weeks is not well predicted by average NEP but depends on the detailed temporal pattern of NEP. However, if average NEP is negative, average NEP may be a good predictor of total CO2 emissions. Similar conclusions apply for high and low alkalinity waters, but uptake rates and temporal variability of CO2 emissions are smaller in high than in low alkalinity waters. Assessment of the link between NEP and CO2 emissions requires differentiation between lakes with different alkalinity and, because of the non-linear relationship between NEP and CO2, strongly benefits from data with high temporal resolution especially during time-periods with positive net-production.

Occurrence, distribution and their correlation with different parameters of antibiotics and antibiotic resistance genes in lakes of China: A review

The exposure of antibiotics and antibiotic resistance genes (ARGs) as potential threats to the environment has raised global concern. This study provides discussion on the emergence and distribution of antibiotics and ARGs in lakes. The correlation of critical water quality parameters with antibiotics and ARGs are evaluated along with their integrative potential ecological risk. Sulfonamides (∼67.18 ng/L) and quinolones (∼77.62 ng/L) were the dominant antibiotics distributed in the aqueous phase, while the quinolones and tetracyclines were the primary contamination factors in the sediment phase. The temporal and spatial distribution revealed that the antibiotic concentrations were significantly lower in summer than other seasons and the lakes in Hebei and Jiangsu provinces exhibited the highest antibiotic pollution. The detection frequency and relative abundance of sul1 gene have been the highest among all detected ARGs. Moreover, ARGs in lakes were driven by several factors, with bacterial communities and mobile genetic elements that prevailed the positive distribution of ARGs. Antibiotics have been identified as critical factors in inducing the propagation of ARGs, which could be further enhanced by chemical contaminants (e.g., heavy metals and nutrients). Involving the risk assessment strategies, research attention should be paid on three antibiotics (ofloxacin, sulfamethoxazole and erythromycin) to strengthen the policy and management of Baiyangdian Lake and East Dongting Lake. This review analysis will provide in-depth understanding to the researchers and policy-makers in formulation of strategies for remediation of antibiotic contamination in the lakes.

A mega study of antibiotics contamination in Eastern aquatic ecosystems of China: occurrence, interphase transfer processes, ecotoxicological risks, and source modeling

Understanding the occurrence, sources, transfer mechanisms, fugacity, and ecotoxicological risks of antibiotics play a pivotal role in improving the sustainability and ecological health of freshwater ecosystems. Therefore, in order to determine the levels of antibiotics, water and sediment samples were collected from multiple Eastern freshwater ecosystems (EFEs) of China, including Luoma Lake (LML), Yuqiao Reservoir (YQR), Songhua Lake (SHL), Dahuofang Reservoir (DHR), and Xiaoxingkai Lake (XKL), and were analyzed using Ultra Performance Liquid Chromatography/Tandem Mass Spectrometry (UPLC-MS/MS). EFEs regions are particularly interesting due to higher urban density, industrialization, and diverse land use in China. The findings revealed that a collective total of 15 antibiotics categorized into four families, which included sulfonamides (SAs), fluoroquinolones (FQs), tetracyclines (TCs), and macrolides (MLs), exhibited high detection frequencies, indicating widespread antibiotic contamination. The pollution levels in the water phase were in the order of LML > DHR > XKL > SHL > YQR. The sum concentration of individual antibiotics for each water body ranged from not detected (ND) to 57.48 ng/L (LML), ND to 12.25 ng/L (YQR), ND to 57.7 ng/L (SHL), ND to 40.50 ng/L (DHR), and ND to 26.30 ng/L (XKL) in the water phase. Similarly, in the sediment phase, the sum concentration of individual antibiotics ranged from ND to 15.35 ng/g, ND to 198.75 ng/g, ND to 1233.34 ng/g, ND to 388.44 ng/g, and ND to 862.19 ng/g, for LML, YQR, SHL, DHR, and XKL, respectively. Interphase fugacity (ff_sw) and partition coefficient (K_d) indicated dominant resuspension of antibiotics from sediment to water, causing secondary pollution in EFEs. Two groups of antibiotics, namely MLs (erythromycin, azithromycin, and roxithromycin) and FQs (ofloxacin and enrofloxacin), showed a medium-high level of adsorption tendency on sediment. Source modeling (PMF5.0) identified wastewater treatment plants, sewage, hospitals, aquaculture, and agriculture as the major antibiotic pollution sources in EFEs, contributing between 6% and 80% to different aquatic bodies. Finally, the ecological risk posed by antibiotics ranged from medium to high in EFEs. This study offers valuable insights into the levels, transfer mechanisms, and risks associated with antibiotics in EFEs, enabling the formulation of large-scale policies for pollution control.

Exploring invertebrate indicators of ecosystem health by focusing on the flow transitional zones in a large, shallow eutrophic lake

The river-lake transitional zone provides a unique environment for the biological community and can reduce pollution inputs in lake ecosystems from their catchments. To explore environmental conditions with high purification potential in Lake Taihu and indicator species, we examined the river-to-lake changes in water and sediment quality and benthic invertebrate communities in the transitional zone of four regions. The spatial variations in the environment and invertebrate community observed in this study followed the previously reported patterns in Taihu; the northern and western regions were characterized by higher nutrient concentrations in water, higher heavy metal concentrations in sediment, and higher total invertebrate density and biomass dominated by pollution-tolerant oligochaetes and chironomids. Although nutrient concentrations were low and transparency was high in the eastern region, the taxon richness was the lowest there, which disagreed with the previous findings and might be due to a poor cover of macrophytes in this study. The river-to-lake change was large in the southern region for water quality and the invertebrate community. Water circulation induced by strong wind-wave actions in the lake sites of the southern region is assumed to have promoted photosynthetic and nutrient uptake activities and favored invertebrates that require well-aerated conditions such as polychaetes and burrowing crustaceans. Invertebrates usually adapted to brackish and saline environments are suggested to be indicators of a well-circulated environment with active biogeochemical processes and a less eutrophic state in Taihu, and wind-wave actions are key to maintaining such a community and natural purifying processes.

Evaluation of planktonic cyanobacteria in Peruvian freshwater lentic water bodies: prevalence and regulatory framework to aid policy making

Increasing reports of cyanobacteria or cyanotoxins around the world expose a major threat for the environment, animal, and human health. Current water treatment processes are ineffective at eliminating cyanotoxins; hence, risk management relies mostly on early detection and on the development of specific regulatory frameworks. In developed countries, well-documented monitoring activities offer a good assessment of the cyanobacterial and/or cyanotoxin status and are used to prevent intoxications. In developing countries such as Peru, despite their potential threat to the environment and public health, cyanobacteria and cyanotoxins are still poorly studied. We found that the regulatory measures regarding cyanobacteria and/or cyanotoxin are almost non-existent. We also present and discuss some examples of recent monitoring efforts underwent by isolated local authorities and scientific reports that, whereas limited, may provide some important insights to be considered nationally. A revision of the available information of planktonic cyanobacteria or cyanotoxins in Peruvian freshwater lentic water bodies revealed a total of 50 documented reports of 15 different genera across 19 water bodies, including the reported highly toxic Dolichospermum and Microcystis. A unique case of microcystin-LR has been documented. We propose some recommendations to be implemented to improve potential toxic cyanobacteria risk management that include incorporating a widespread monitoring of cyanobacterial communities in lakes and reservoirs used for human consumption via specific guidelines. Aligning Peruvian regulations on cyanobacteria and cyanotoxins to international standards may also support law enforcement and ensure compliance.

Research progress on the content and distribution of rare earth elements in rivers and lakes in China

This study reviewed the content and distribution of rare earth elements (REE) in rivers and lakes in China based on the online literature. The sequence distribution of REE presented the decreasing trends in the order: of Ce > La > Nd > Pr > Sm > Gb > Dy>Er > Yb > Eu > Lu > Ho > Tb > Tm in rivers water. Pearl River and the Jiulong River constitute a significant sediments REE reservoir with an average value mean of 229.6 mg/kg and 266.86 mg/kg, respectively; both have higher concentrations than the global river average (174.8 mg/kg) and higher than the local soil background (Chinese soil background). The Liaohe River is one of China's most polluted rivers, with REE distribution ranging from 106.61 to 174.71 g/L (average 144.59 g/L in water). The total concentrations of dissolved REE in rivers near REE mining areas in China are higher than in other rivers. Increasing anthropogenic inputs to natural systems may permanently alter the natural signatures of REE. The distribution characteristics of REE in Chinese lakes (sediments) varied greatly, and the mean enrichment factor (EF) was sorted as follows: Ce > La > Nd > Pr > Sm > Gd > Dy>Er > Yb > Eu > Ho > Tb > Tm > Lu, where Ce was the most abundant followed by La, Nd, and Pr, and these four elements account for 85.39 % of the total concentration of REE. The REE in the sediments obtained from Poyang Lake and Dongting Lake had an average concentration respectively of 254.0 μg/g and 197.95 μg/g; both are considerably higher than the average upper continental crust (146.4 μg/g) and higher than in other lakes in China and around the world. The distribution and accumulation of LREE in most lake sediments result from the joint action of human activities and natural processes. It concluded that mining tailings were the primary cause of REE pollution in sediments, and industrial and agricultural activities are mainly responsible for water contamination.

A stacked machine learning model for multi-step ahead prediction of lake surface water temperature

Lake surface water temperature is one of the most important physical and ecological indices of lakes, which has frequently been used as the indicator to evaluate the impact of climate change on lakes. Knowing the dynamics of lake surface water temperature is thus of great significance. The past decades have witnessed the development of different modeling tools to forecast lake surface water temperature, yet, simple models with fewer input variables, while maintaining high forecasting accuracy are scarce. Impact of forecast horizons on model performance has seldom been investigated. To fill the gap, in this study, a novel machine learning algorithm by stacking multilayer perceptron and random forest (MLP-RF) was employed to forecast daily lake surface water temperature using daily air temperature as the exogenous input variable, with the Bayesian Optimization procedure applied for tuning the hyperparameters. Prediction models were developed using long-term observed data from eight Polish lakes. The MLP-RF stacked model showed very good forecasting capabilities for all lakes and forecast horizons, far better than shallow multilayer perceptron neural network, a model coupling wavelet transform and multilayer perceptron neural network, non-linear regression and air2water models. A reduction in model performance was observed as the forecast horizon increased. However, the model also performs well with a forecast horizon of several days (e.g., 7 days ahead, testing stage: R² - [0.932, 0.990], RMSE °C - [0.77, 1.83], MAE °C - [0.55, 1.38]). In addition, the MLP-RF stacked model has proven to be reliable for both intermediate temperatures and minimum and maximum peaks. The model proposed in this study will be useful to the scientific community in predicting lake surface water temperature, thus contributing to studies on such sensitive aquatic ecosystems as lakes.

Genomic insights into cryptic cycles of microbial hydrocarbon production and degradation in contiguous freshwater and marine microbiomes

BACKGROUND

Cyanobacteria and eukaryotic phytoplankton produce long-chain alkanes and generate around 100 times greater quantities of hydrocarbons in the ocean compared to natural seeps and anthropogenic sources. Yet, these compounds do not accumulate in the water column, suggesting rapid biodegradation by co-localized microbial populations. Despite their ecological importance, the identities of microbes involved in this cryptic hydrocarbon cycle are mostly unknown. Here, we identified genes encoding enzymes involved in the hydrocarbon cycle across the salinity gradient of a remote, vertically stratified, seawater-containing High Arctic lake that is isolated from anthropogenic petroleum sources and natural seeps. Metagenomic analysis revealed diverse hydrocarbon cycling genes and populations, with patterns of variation along gradients of light, salinity, oxygen, and sulfur that are relevant to freshwater, oceanic, hadal, and anoxic deep sea ecosystems.

RESULTS

Analyzing genes and metagenome-assembled genomes down the water column of Lake A in the Canadian High Arctic, we detected microbial hydrocarbon production and degradation pathways at all depths, from surface freshwaters to dark, saline, anoxic waters. In addition to Cyanobacteria, members of the phyla Flavobacteria, Nitrospina, Deltaproteobacteria, Planctomycetes, and Verrucomicrobia had pathways for alkane and alkene production, providing additional sources of biogenic hydrocarbons. Known oil-degrading microorganisms were poorly represented in the system, while long-chain hydrocarbon degradation genes were identified in various freshwater and marine lineages such as Actinobacteria, Schleiferiaceae, and Marinimicrobia. Genes involved in sulfur and nitrogen compound transformations were abundant in hydrocarbon producing and degrading lineages, suggesting strong interconnections with nitrogen and sulfur cycles and a potential for widespread distribution in the ocean.

CONCLUSIONS

Our detailed metagenomic analyses across water column gradients in a remote petroleum-free lake derived from the Arctic Ocean suggest that the current estimation of bacterial hydrocarbon production in the ocean could be substantially underestimated by neglecting non-phototrophic production and by not taking low oxygen zones into account. Our findings also suggest that biogenic hydrocarbons may sustain a large fraction of freshwater and oceanic microbiomes, with global biogeochemical implications for carbon, sulfur, and nitrogen cycles. Video Abstract.

Anthropogenic pollution drives the bacterial resistome in a complex freshwater ecosystem

Aquatic ecosystems in anthropogenically impacted areas are important reservoirs of antibiotic resistance genes (ARGs) of allochthonous origin. However, the dynamics of the different ARGs within the bacterial communities of lakes and rivers, as well as the factors that drive their selection, are not completely understood. In this study, we analysed the fate of the bacterial resistome (total content of ARGs and of metal resistance genes, MRGs) for a period of six months (summer-winter) in a continuum lake-river-lake system (Lake Varese, River Bardello, Lake Maggiore) in Northern Italy, by shotgun metagenomics. The metagenomic data were then compared with chemical, physical and microbiological data, to infer the role of anthropogenic pressure in the different sampling stations. ARGs and MRGs were more abundant and diverse in the River Bardello, characterised by the highest anthropogenic pollution. The date of sampling influenced ARGs and MRGs, with higher abundances in summer (August) than in fall or in winter, when the impact of the treated wastewater discharge in the river was limited by a higher water flow from Lake Varese. ARG and MRG abundances were significantly correlated and they co-occurred in the main network analysis modules with potential pathogenic bacteria. Different levels of anthropogenic impact selectively promoted specific ARGs while others, generally abundant in waters, were not affected by anthropogenic pressure. Reducing the level of anthropogenic pressure resulted in a rapid decrease of most ARGs. From our results, the role of anthropogenic pressure in promoting the spread of specific antibiotic resistances and of potential pathogens in aquatic ecosystem becomes clear. Finally we highlight the strict correlation between ARGs and MRGs suggesting their potential co-selection in stressed aquatic bacterial communities.

Identifying lakes at risk of toxic cyanobacterial blooms using satellite imagery and field surveys across the United States

Harmful algal blooms caused by cyanobacteria are a threat to global water resources and human health. Satellite remote sensing has vastly expanded spatial and temporal data on lake cyanobacteria, yet there is still acute need for tools that identify which waterbodies are at-risk for toxic cyanobacterial blooms. Algal toxins cannot be directly detected through imagery but monitoring toxins associated with cyanobacterial blooms is critical for assessing risk to the environment, animals, and people. The objective of this study is to address this need by developing an approach relating satellite imagery on cyanobacteria with field surveys to model the risk of toxic blooms among lakes. The Medium Resolution Imaging Spectrometer (MERIS) and United States (US) National Lakes Assessments are leveraged to model the probability among lakes of exceeding lower and higher demonstration thresholds for microcystin toxin, cyanobacteria, and chlorophyll a. By leveraging the large spatial variation among lakes using two national-scale data sources, rather than focusing on temporal variability, this approach avoids many of the previous challenges in relating satellite imagery to cyanotoxins. For every satellite-derived lake-level Cyanobacteria Index (CI_cyano) increase of 0.01 CI_cyano/km2, the odds of exceeding six bloom thresholds increased by 23-54 %. When the models were applied to the 2192 satellite monitored lakes in the US, the number of lakes identified with ≥75 % probability of exceeding the thresholds included as many as 335 lakes for the lower thresholds and 70 lakes for the higher thresholds, respectively. For microcystin, the models identified 162 and 70 lakes with ≥75 % probability of exceeding the lower (0.2 μg/L) and higher (1.0 μg/L) thresholds, respectively. This approach represents a critical advancement in using satellite imagery and field data to identify lakes at risk for developing toxic cyanobacteria blooms. Such models can help translate satellite data to aid water quality monitoring and management.

Remote sensing monitoring of mining tailings in the fluvial-estuarine-coastal ocean continuum of the Lower Doce River Valley (Brazil)

Water clarity is a key parameter of aquatic ecosystems impacted by mining tailings. Tracking down tailings dispersion along the river basin requires a regional monitoring approach. The longitudinal fluvial connectivity, river-estuary-coastal ocean, and the lateral connectivity, river-floodplain-alluvial lakes are interconnected by hydrological flows, particularly during high fluvial discharge. The present study aims to track the dispersal of iron ore tailing spill, from the collapse of the Fundão dam (Mariana, MG, Brazil), on November 5, 2015, in the Lower Doce River Valley. A semi-empirical model of turbidity data, as a water clarity proxy, and multispectral remote sensing data (MSI Sentinel-2), based on different hydrological conditions and well-differentiated water types, yielded an accuracy of 92%. Five floods (> 3187m³ s^-1) and five droughts (< 231m³ s^-1) events occurred from 2013 to 2020. The flood of January 2016 occurred one month after the mining slurries reached the coast, intruding tailings on some alluvial and coastal plain lakes with highly turbid waters (> 400 NTU). A fluvial plume is formed in the inner shelf adjoining the river mouth on high flow. The dispersion of river plume was categorized as plume core (turbidity > 200 NTU), plume core and inner shelf waters (100-199 NTU), other shelf water (50-99 NTU), and offshore waters (< 50 NTU). Fluvial discharge and local winds are the main drivers for river plume dispersion and transport of terrigenous material along the coast. This work provides elements for evaluating the impact of mining tailings and an approach for remote sensing regional monitoring of surface water quality.

High-frequency time series comparison of Sentinel-1 and Sentinel-2 satellites for mapping open and vegetated water across the United States (2017-2021)

Frequent observations of surface water at fine spatial scales will provide critical data to support the management of aquatic habitat, flood risk and water quality. Sentinel-1 and Sentinel-2 satellites can provide such observations, but algorithms are still needed that perform well across diverse climate and vegetation conditions. We developed surface inundation algorithms for Sentinel-1 and Sentinel-2, respectively, at 12 sites across the conterminous United States (CONUS), covering a total of >536,000 km2 and representing diverse hydrologic and vegetation landscapes. Each scene in the 5-year (2017-2021) time series was classified into open water, vegetated water, and non-water at 20 m resolution using variables from Sentinel-1 and Sentinel-2, as well as variables derived from topographic and weather datasets. The Sentinel-1 algorithm was developed distinct from the Sentinel-2 model to explore if and where the two time series could potentially be integrated into a single high-frequency time series. Within each model, open water and vegetated water (vegetated palustrine, lacustrine, and riverine wetlands) classes were mapped. The models were validated using imagery from WorldView and PlanetScope. Classification accuracy for open water was high across the 5-year period, with an omission and commission error of only 3.1% and 0.9% for the Sentinel-1 algorithm and 3.1% and 0.5% for the Sentinel-2 algorithm, respectively. Vegetated water accuracy was lower, as expected given that the class represents mixed pixels. The Sentinel-2 algorithm showed higher accuracy (10.7% omission and 7.9% commission error) relative to the Sentinel-1 algorithm (28.4% omission and 16.0% commission error). Patterns over time in the proportion of area mapped as open or vegetated water by the Sentinel-1 and Sentinel-2 algorithms were charted and correlated for a subset of all 12 sites. Our results showed that the Sentinel-1 and Sentinel-2 algorithm open water time series can be integrated at all 12 sites to improve the temporal resolution, but sensor-specific differences, such as sensitivity to vegetation structure versus pixel color, complicate the data integration for mixed-pixel, vegetated water. The methods developed here provide inundation at 5-day (Sentinel-2 algorithm) and 12-day (Sentinel-1 algorithm) time steps to improve our understanding of the short- and long-term response of surface water to climate and land use drivers in different ecoregions.

Analyzing eutrophication and harmful algal bloom dynamics in a deep Mediterranean hypereutrophic reservoir

Excessive point and non-point nutrient loadings accompanied with elevated temperatures have increased the prevalence of harmful algal bloom (HAB). HABs pose significant environmental and public health concerns, particularly for inland freshwater systems. In this study, the eutrophication and HAB dynamics in the Qaraoun Reservoir, a hypereutrophic deep monomictic reservoir suffering from poor water quality, were assessed. The reservoir was mostly phosphorus limited, and large algal particulates dominated light attenuation in the water column. During bloom events, surface chlorophyll-a concentrations increased up to 961.3 µg/L, while surface concentrations of ammonia and ortho-phosphate were rapidly depleted; surface dissolved oxygen reached supersaturation levels and surface pH levels were up to 3 units higher than those measured in the hypolimnion. Meanwhile, measured Microcystin-LR toxin concentrations in the reservoir exceeded the World Health Organization 1 μg/L provisional guideline 45% of the times. Yet, the results showed that most of the toxins were intra-cellular, suggesting that they decayed rapidly when released into the reservoir. Results from a random forests ensemble model indicated that tracking the changes in surface dissolved oxygen levels, ammonium, ortho-phosphate, and pH can be an effective program towards predicting the reservoir's trophic state and algae blooms.

Panarchy suggests why management mitigates rather than restores ecosystems from anthropogenic impact

Panarchy, a model of dynamic systems change at multiple, interconnected spatiotemporal scales, allows assessing whether management influences ecological processes and resilience. We assessed whether liming, a management action to counteract anthropogenic acidification, influenced scale-specific temporal fluctuation frequencies of benthic invertebrates and phytoplankton assemblages in lakes. We also tested whether these fluctuations correlated with proxies of liming (Ca:Mg ratios) to quantify scale-specific management effects. Using an ecosystem experiment and monitoring data, time series analyses (1998-2019) revealed significant multiscale temporal (and thus panarchy) structure for littoral invertebrates across limed and reference lakes. Such patterns were inconsistent for sublittoral invertebrates and phytoplankton. When significant panarchy structure was found, Ca:Mg ratios correlated with only a few of the identified temporal fluctuation frequencies across limed and reference lakes. This suggests that liming effects become diluted in the managed lakes. The lack of manifestations of liming across the independent temporal fluctuation patterns suggest that this lake management form fails to create and enforce cross-scale interactions, a crucial component of ecological resilience. This interpretation supports liming as a mitigation effort rather than a tool to restore acidified lakes to a self-organizing system equivalent of circumneutral references.

A new method based on additive vegetation index for mapping Huangtai algae coverage in Lake Ulansuhai

Huangtai algal blooms are key indicators of eutrophication and lake-ecosystem damage. Understanding the spatiotemporal heterogeneity of their growth is critical for preserving the ecological environment. The dimidiate pixel model is commonly used to estimate vegetation coverage; however, indices such as the normalized difference vegetation index have not been specifically constructed for the Huangtai algae spectrum and thus are not specific or sufficiently precise for use as indicators. Therefore, we propose a new dimidiate pixel model based on a novel additive vegetation index to calculate the Huangtai algal coverage for each pixel using Landsat multispectral satellite images with 30-m resolution. The results showed that the additive vegetation index with R² = 0.994 is a better indicator than the normalized difference vegetation index, enhanced vegetative index, and ratio vegetative index, with the accuracy of the new model reaching 86.61%. Monthly Landsat images from 2006 to 2016 were used to calculate the Huangtai algal coverage. Analysis of the inter-monthly variation indicated increased coverage from May to July, with an annual maximum and minimum of 14.43% and 0.33% in 2008 and 2013, respectively. This study provides a new reference map of Huangtai algal cover, which is important for monitoring and protecting the Lake Ulansuhai environment.

Distribution of microplastics in the catchment region of Pallikaranai marshland, a Ramsar site in Chennai, India

Microplastics are persistent toxic pollutants, detected in different environmental compartments. Numerous studies on the characteristics and distribution of microplastics present in different environmental matrices are being carried out. However, limited studies have been performed in environmental systems like eco-sensitive freshwater marshlands. Therefore, to enrich the existing knowledge and understanding, this current study has analysed the distribution and characteristics of microplastics present in the catchment region of Pallikaranai marshland, Chennai, India. Both surface water and sediment samples were contaminated with microplastics in the range of 740-2826 items/m³and 700 to 5833 items/kg of dry sediment, respectively. Compared to other shapes, fibrous microplastics were predominant in most of the surface water (n = 11) and sediment (n = 8) samples. The abundant presence of smaller microplastics (<1 mm) in the surface water suggests elevated impacts on the aquatic species owing to their higher bioavailability. Elevated anthropogenic activities and frequent movement of people in urban and residential areas were noted to possibly influence the spatial distribution of microplastics. Furthermore, heavy metals' occurrence on microplastics was investigated using X-Ray Fluorescence Analyser (XRF) and Zn, Fe, Ti, and Ni are the commonly detected (>50% of the samples) elements. The estimated average pollution load index of 2.5 indicates the polluted state of Pallikaranai catchment region.

Phosphorus removal by aquatic vegetation in shallow eutrophic lakes: a laboratory study

Eutrophication in inland lakes is occurring frequently with the rapid urbanization, the increases in human population, and the intensive agricultural activities. Traditional management programs focusing on external nutrient reduction failed in recovery of certain aquatic environments where internal nutrient releases are substantial. In this study, we evaluated the effects of aquatic vegetation in altering the phosphorus concentrations in a shallow, eutrophic lake through laboratory flume experiments. Our measurements demonstrated that aquatic vegetation could effectively lower the phosphorus levels in the water column, and the average reduction reached 90% for submerged vegetation and 80% for emergent vegetation. The experimental results showed that the submerged vegetation was effective to reduce phosphorus concentrations in the top and mid layers of pore waters and sediments. Differently, the emergent vegetation would assimilate more phosphorus in the bottom layer due to its deep root distributions. The flowing-water environment favored phosphorus removal for emergent vegetation, while the submerged vegetation was more functional in static waters according to our observations. The flux results showed that phosphorus transports from water columns to leaves, roots to leaves, and sediments to roots were all inhibited in flowing-water environments for submerged vegetation. Oppositely, the fluxes of emergent vegetation groups were all enhanced in flowing waters. Our experiments could inform ecosystem management concerning the potentials of aquatic vegetation in nutrient removal at regional and lake-wide scales.

Assessing temporal variability of lake turbidity and trophic state of European lakes using open data repositories

Water turbidity is one of the more important water quality parameters that is strictly linked with the productivity of the lake and is commonly used as an indicator of the trophic state. However, limited field data availability across wide geographic gradients may hinder the conduction of large scale longitudinal studies. In this study, time series of lake turbidity and trophic state index (TSI) between 2002 and 2012 were obtained from the Copernicus Lake Water products to create a large longitudinal dataset of lake variables for 22 European lakes. The dataset was combined with estimates of nutrient concentrations and surface water temperature obtained from the Hydrological Predictions for the Environment (HYPE) and ERA5-Land data repositories, that were used as environmental predictors. Hence, the validity of the lake water quality parameters was tested by a) exploring their spatial and temporal variability and b) identifying associations with the environmental predictors. For this purpose, seasonal Mann-Kendall tests were applied to find significant inter-annual trends of turbidity and TSI for each lake, and generalized additive models (GAMs) were employed to identify the main parameters that shape their temporal dynamics. Although we did not find significant inter-annual changes, our findings highlighted the strong influence of seasonality and surface water temperature in defining the temporal variability patterns in most of the lakes. In addition, the importance of nutrients varied among lakes as several lakes exhibited narrow nutrient gradients reflecting relatively stable nutrient conditions during the examined period. Other lake intrinsic factors, such as local climate and biotic interactions, are important drivers of shaping turbidity and nutrient dynamics. This study highlighted the usefulness of combining lake data from large repositories in conducting large scale spatial studies as a valuable asset for future lake research and management purposes.

Carbon, nitrogen, and phosphorus dynamics in China's lakes: climatic and geographic influences

Given the differences in geomorphology, climate, hydrology, and human activities in various regions, lake chemometrics may also vary. However, the spatial distribution of lake chemistry and the factors affecting such pattern are still unclear. Here, we collected data for carbon, nitrogen, and phosphorus from published literature and databases in 224 lakes and calculated the trophic status index to represent the nutrient classification state of lakes. We found that lakes with high carbon concentrations were located in the Tibet-Qinghai Limnetic Region of western China, whereas lakes with high nitrogen and phosphorus concentrations were located in the Inner Mongolia-Xinjiang Limnetic Region and Northeast Limnetic Region of northern China. Areas with larger cropland and urban residential land (such as the junction of the three lake regions, i.e., the Northeast Limnetic Region, East Limnetic Region, and Inner Mongolia-Xinjiang Limnetic Region) tended to have lakes with high nitrogen and phosphorus concentrations. Our analysis suggested that spatial distribution of carbon, nitrogen, and phosphorus concentrations reflect the effect of climate, geomorphology, and land use in each lake region and nationwide.

Human access and deterministic processes play a major role in structuring planktonic and sedimentary bacterial and eukaryotic communities in lakes

Lakes provide habitat for a diverse array of species and offer a wide range of ecosystem services for humanity. However, they are highly vulnerable as they are not only impacted by adverse actions directly affecting them, but also those on the surrounding environment. Improving knowledge on the processes responsible for community assembly in different biotic components will aid in the protection and restoration of lakes. Studies to date suggested a combination of deterministic (where biotic/abiotic factors act on fitness differences amongst taxa) and stochastic (where dispersal plays a larger factor in community assembly) processes are responsible for structuring biotic communities, but there is no consensus on the relative roles these processes play, and data is lacking for lakes. In the present study, we sampled different biotic components in 34 lakes located on the South Island of New Zealand. To obtain a holistic view of assembly processes in lakes we used metabarcoding to investigate bacteria in the sediment and surface waters, and eukaryotes in the sediment and two different size fractions of the water column. Physicochemical parameters were collected in parallel. Results showed that deterministic processes dominated the assembly of lake communities although the relative importance of variable and homogeneous selection differed among the biotic components. Variable selection was more important in the sediment (SSbact and SSeuks) and for the bacterioplankton (Pbact) while the assembly of the eukaryotic plankton (SPeuks, LPeuks) was driven more by homogeneous selection. The ease of human access to the lakes had a significant effect on lake communities. In particular, clade III of SAR11 and Daphnia pulex were only present in lakes with public access. This study provides insights into the distribution patterns of different biotic components and highlights the value in understanding the drivers of different biological communities within lakes.

Urbanization promotes specific bacteria in freshwater microbiomes including potential pathogens

Freshwater ecosystems are characterized by complex and highly dynamic microbial communities that are strongly structured by their local environment and biota. Accelerating urbanization and growing city populations detrimentally alter freshwater environments. To determine differences in freshwater microbial communities associated with urbanization, full-length 16S rRNA gene PacBio sequencing was performed in a case study from surface waters and sediments from a wastewater treatment plant, urban and rural lakes in the Berlin-Brandenburg region, Northeast Germany. Water samples exhibited highly habitat specific bacterial communities with multiple genera showing clear urban signatures. We identified potentially harmful bacterial groups associated with environmental parameters specific to urban habitats such as Alistipes, Escherichia/Shigella, Rickettsia and Streptococcus. We demonstrate that urbanization alters natural microbial communities in lakes and, via simultaneous warming and eutrophication and creates favourable conditions that promote specific bacterial genera including potential pathogens. Our findings are evidence to suggest an increased potential for long-term health risk in urbanized waterbodies, at a time of rapidly expanding global urbanization. The results highlight the urgency for undertaking mitigation measures such as targeted lake restoration projects and sustainable water management efforts.

Sediment organic matter properties facilitate understanding nitrogen transformation potentials in East African lakes

East African lakes include the most productive and alkaline lake group in the world. Yet, they generally receive fewer nutrient inputs than the densely populated subtropical and temperate lakes in the northern hemisphere. In these lakes with insufficient supplies of inorganic nitrogen, the mineralization of benthic organic matter can play an important role in driving the nutrient cycle and nitrogen loss. Using a suite of stable ¹⁵N isotope dilution and tracer techniques, we examined five main processes of the sediment nitrogen cycle in 16 lakes and reservoirs of Tanzania and Kenya, East Africa: gross nitrogen mineralization, ammonium immobilization, dissimilatory nitrate reduction to ammonium (DNRA), and the dinitrogen (N₂) production via denitrification and anaerobic ammonium oxidation (anammox). Gross nitrogen mineralization and ammonium immobilization showed the maximum values of 9.84 and 12.39 μmol N kg^-1 h^-1, respectively. Potential DNRA rates ranged from 0.22 to 8.15 μmol N kg^-1 h^-1 and accounted for 10 %-74 % (average 25 %) of the total dissimilatory nitrate reduction. Potential nitrate reduction rates in most lakes were dominated by denitrification with a contribution of 26 %-85 % and a mean of 65 %. We further found that the sediment nitrogen transformations were driven mainly by benthic organic matter properties and water column phosphate concentrations, reflecting microbial metabolic responses to the changing carbon and nutrients availability. For instance, autochthonous production of protein-like organic matter attributed to active sediment nitrogen mineralization, DNRA, and denitrification. In contrast, the high degree of humification caused by the inputs of terrestrial humic-like substances slowed down the sediment nitrogen transformations. The contribution of DNRA to total dissimilatory nitrate reduction was significantly positively correlated to sediment C: N ratios. These results indicate that predictions of sediment N supply and loss in East African lakes can be improved by incorporating sediment organic matter properties.

Composition of dissolved organic matter (DOM) in lakes responds to the trophic state and phytoplankton community succession

Dissolved organic matter (DOM), a heterogeneous mixture of diverse compounds with different molecular weights, is crucial for the lake carbon cycle. The properties and concentration of DOM in lakes are closely related to anthropogenic activities, terrigenous input, and phytoplankton growth. Thus, the lake's trophic state, along with the above factors, has an important effect on DOM. We determined the DOM sources and molecular composition in six lakes along a trophic gradient during and after phytoplankton bloom by combining optical techniques and the Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). CDOM pools in eutrophic lakes may be more biologically refractory than in oligotrophic and mesotrophic lakes. Molecular formulas of DOM were positively correlated with the TSI (trophic state index) value (R² = 0.73), with the nitrogen-containing compounds (CHON) being the most abundant formulas in all studied lakes. Eutrophication modified the molecular formulas of DOM to have less CHO% and more heteroatom S-containing compounds (CHOS% and CHNOS%), and this was the synactic result of the anthropogenic perturbation and phytoplankton proliferation. In eutrophic lakes, summer DOM showed higher molecular lability than in autumn, which was related to the seasonal phytoplankton community succession. Although the phytoplankton-derived DOM is highly bioavailable, we detected a simpler and more fragile phytoplankton community ecosystem in autumn, which may be accompanied by a lower phytoplankton production and metabolic activity. Therefore, we concluded that the lake eutrophication increased the allochthonous DOM accumulation along with sewage and nutrient input, and subsequently increased its release with phytoplankton bloom. Eutrophication and phytoplankton growth are accompanied by more highly unsaturated compounds, O₃S+O₅S compounds, and carboxylic-rich alicyclic compounds (CRAMs), which are the biotransformation product of phytoplankton-derived DOM. Eutrophication may be a potential source of refractory DOM compounds for biodegradation and photodegradation. Our results can clarify the potential role of water organic matter in the future global carbon cycle processes, considering the increasing worldwide eutrophication of inland waters.

Variation trends and attribution analysis of lakes in the Qiangtang Plateau, the Endorheic Basin of the Tibetan Plateau

The Tibetan Plateau (TP) is the area with most high-altitude lakes in the world, of which most are in the Qiangtang Plateau (QP), the endorheic basin of the TP. Since the 1990s, abundant studies have reported the accelerated expansion of lakes in the QP. However, the dominant factors affecting lakes expansion or shrinkage are still controversial. Here we extract six periods of 300 lakes according to the satellite image. It indicates that 90% of the lakes in the QP were expanding, mainly located in the middle of the plateau; 10% of the lakes tended to shrink, mainly located in the areas surrounding the plateau and near the Tanggula Mountain and Nyainqentanglha Mountain, with an altitude over 4500 m. Meanwhile, we explored the influence factors for lake area changes by analyzing the variations in precipitation and glacier. Seven different driving models leading to the lake changes are proposed. Lake expansion was mainly caused by the increase of precipitation and glacier melting, while the causes of lake shrinkage are quite different, such as the change of precipitation and evaporation, the geological structure of lake outlet, the increase of outflow caused by the more transformation of lake water from solid to liquid, etc. This study can provide some support for plateau grassland protection and ice lake outburst prevention.

Seasonal variations in the abundance and distribution of microplastic particles in the surface waters of a Southern Indian Lake

Hazardous anthropogenic particles, such as microplastics (MPs) in the lake ecosystems, are a serious concern. In this work, we have investigated the seasonal occurrence and distribution of microplastics in the surface water samples of Lake Manipal in southwest India. The concentration of MPs was found to be higher during the monsoon season (0.423 particles/L) in comparison with the post-monsoon (0.117 particles/L) period. The higher abundance is attributed to the input of storm-water sewers connected to the lake as well as surface runoff during periods of high rainfall. The concentrations of small-sized (0.3-1 mm) microplastics were greater in both seasons. Approximately 96% of the microplastics were fibres, followed by smaller amounts of fragments, pellets, films, and foams. Polyethylene terephthalate (PET) was the principal polymer composition of the microplastics, followed by cellulose. The PET and cellulose fibres were mainly derived from the laundering of clothes in the residential colonies and hostels situated close to the lake. The storm-water sewers were the likely conduit for these PET fibres into the lake. The Pollution Load Index (PLI) data reveals that pollution due to microplastics in Lake Manipal falls within the Level I risk category. The PLI was higher during the monsoon season due to an increased flux of these particles from the nearby region. During the post-monsoon period, the PLI values decreased, suggesting that MPs in the water column may have settled and mixed with the sediments. The baseline data generated in this study is important as different types of birds, amphibians, and other microorganisms are present in the environment of Lake Manipal. We also propose certain policy measures that can be adopted by the regional population to mitigate microplastic pollution in the lake and its vicinity.

Microplastics in Flathead Lake, a large oligotrophic mountain lake in the USA

Microplastics are contaminants that are closely associated with human activity and are often abundant even in remote areas. As the largest natural freshwater lake in the western USA, Flathead Lake is a suitable site to study microplastics in lakes in less-populated areas of North America. Our assessment of microplastics in lake surface water samples showed that microplastic densities and concentrations in Flathead Lake were similar to those in other lakes located in less-populated areas around the world, with densities ranging from 8.00 × 10⁴ to 4.22 × 10⁵ particles/km² with a mean concentration of 1.89 × 10⁵ particles/km². Dry deposition rates for microplastics ranged from 4 to 140 particles/m²/day with an average of 69 particles/m²/day and were significantly higher in the fall. Microplastic concentrations in wet deposition ranged from 0.006 particles/mL to 0.050 particles/mL with highest concentrations in winter and lowest in summer. Fibrous microplastics were predominant in both lake water and atmospheric deposition. The high densities of microplastics in the sample sites located near the Flathead River inlet suggests that the river is an important source of microplastics to Flathead Lake. The high densities of microplastics and high proportions of non-fibrous microplastics near populated areas of the lake imply that local human activities also affect microplastics in Flathead Lake. Although the annual flux of microplastics in dry deposition was higher than that in wet deposition, the relatively modest difference suggests that precipitation might enhance the deposition of microplastics. The results of this study indicate that instituting increased control measures that target both reducing the microfibers generated by laundry and improving the overall level of plastic waste management in the watershed may help in controlling microplastic levels in Flathead Lake.

Ecotoxicological impacts of the Fundão dam failure in freshwater fish community: Metal bioaccumulation, biochemical, genetic and histopathological effects

This study investigates the ecotoxicological impacts of the Fundão dam rupture, one of the major environmental disaster that occurred in Brazil and in the world mining industry history, through multi-biomarkers responses and metals bioaccumulation in the fish community of different trophic levels. Specimens of the fishes (omnivorous/herbivorous and carnivorous) were collected along the Doce River channel and its affluent Guandú River, and in different lakes and coastal lagoons adjacent to the river channel, in the Espirito Santo State, Southeast of Brazil. Four sampling collections were carried out over two years (2018 to 2020, during dry and rainy seasons). For both trophic groups the biomarkers responses indicated physiological alterations related to metals exposure and showed strong seasonal variations. The principal component analysis and integrated biomarker response index showed that DNA damage and lipid peroxidation were more associated with dry season 2 (Sep/Oct 2019) and the oxidative damage in proteins, metallothioneins concentration and the activity of superoxide dismutase in the gills showed a greater association with rainy season 2 (Jan/Feb 2020). On the other hand, the enzymes of energy metabolism, catalase and histological damage in the liver and the gills, were more associated with the dry and rainy campaigns of the first year of monitoring. The multivariate approach also suggested a temporal intensification in the bioaccumulation of metals and biological effects in the lacustrine environments. Thus, these results demonstrate that the release of mineral residues from the rupture of the Fundão mine dam affects the health status of the fish from the Doce River basin, provoking metals bioaccumulation, hepatic and branchial damage in the fish besides inducing of enzyme activity related to metal contamination, even four years after the rupture.

Trends of lake temperature, mixing depth and ice cover thickness of European lakes during the last four decades

Lakes are particularly vulnerable ecosystems to global warming. Surface temperature of most lakes in the world has significantly increased. Here, we analysed time-series of water temperature, mixing-depth, and ice depth of 51 European lakes over the last four decades. We used data of surface temperature, total layer water temperature, mix-layer temperature, mix-layer depth, and ice cover depth obtained from the ERA5-Land reanalysis dataset. Our main objectives were a) to identify significant changes of the examined variables that have occurred from 1981 to 2019 and b) to assess the variability of changes in relation with geographical and lake morphological gradients. To this end, time series analysis was conducted using generalized additive models (GAMs). In addition, we quantified the magnitude of change by estimating the Sen's slopes for each variable and then we examined the variability of these slopes to geographical and lake morphological parameters using GAMs. Our results confirmed that water temperature parameters (surface, total-layer and mix-layer temperature) have significantly increased for all lakes during the last four decades. We also found significant changes of the mixing depth for 14 lakes. In addition, the lake ice depth has significantly decreased in all fifteen lakes of the subarctic climate region. Finally, we showed that the Sen's slopes depend on the geographic coordinates and the elevation of the lakes, whereas lake morphometry (e.g. depth) has a smaller effect on the magnitude of changes. These findings hint that lake ecosystems of Europe have substantially changed over the last forty years and urge the need to take precautionary measures to prevent future implications for the freshwater biota.

A review on the research progress of lake water volume estimation methods

Surface water provides a basic resource for life and is vital for maintaining climate stability, hydrological cycles, and natural ecosystems. Lakes, which are an important part of surface water, play a crucial role in sustaining the hydrological balance and maintaining a healthy environment. The onset of climate change and anthropogenic disturbance on lakes and the environment, however, have drastically changed the morphological characteristics of lakes, leading to undesirable negative effects on the ecological environment. In recent years, many lakes around the world are undergoing phenomenal changes due to climate change and human activities. These changes have greatly affected the availability of freshwater resources, leading to a series of regional ecological and environmental problems, which constrain the regional sustainable development. Changes in lake parameters often indicate environmental change. Therefore, it is of great practical significance to extract lake water information to reflect the water quantity changes in the lake, understand its implications, and come up with timely solutions. This paper summarizes the existing research methods of lake water estimation in China and abroad and draws the following conclusions: (1) In the study of lake water volume estimation, it can be roughly divided into with topographic data and without topographic data. The most representative methods are the estimation methods based on topographic parameters and the Triangle Irregular Network (TIN) model method. In the actual research process, most of the scarce data that are difficult to obtain are lake topographic data, prompting researchers to constantly put forward new methods; (2) From the perspective of research methods, estimation of lake water volume can be divided into remote sensing-based and non-remote sensing-based research. With the continuous improvement of scientific and technological levels, current geographical researchers tend to use remote sensing to monitor lake water volume; (3) Although researchers have proposed a series of models for lake water volume estimation for the long-time process. However, many models are based on the ideal static estimation process, which poses challenges for researchers to make a long-term dynamic estimation of lake storage capacity in the future. At the same time, the accuracy of the model can be a problem that researchers need to work out solutions in the future. Finally, combined with the current development of remote sensing technology, the application potential and the future prospect of remote sensing in lake monitoring are briefly discussed.

Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales

Previous studies indicate that cyanobacterial harmful algal bloom (cyanoHAB) frequency, extent, and magnitude have increased globally over the past few decades. However, little quantitative capability is available to assess these metrics of cyanoHABs across broad geographic scales and at regular intervals. Here, the spatial extent was quantified from a cyanobacteria algorithm applied to two European Space Agency satellite platforms-the MEdium Resolution Imaging Spectrometer (MERIS) onboard Envisat and the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3. CyanoHAB spatial extent was defined for each geographic area as the percentage of valid satellite pixels that exhibited cyanobacteria above the detection limit of the satellite sensor. This study quantified cyanoHAB spatial extent for over 2,000 large lakes and reservoirs across the contiguous United States (CONUS) during two time periods: 2008-2011 via MERIS and 2017-2020 via OLCI when cloud-, ice-, and snow-free imagery was available. Approximately 56% of resolvable lakes were glaciated, 13% were headwater, isolated, or terminal lakes, and the rest were primarily drainage lakes. Results were summarized at national-, regional-, state-, and lake-scales, where regions were defined as nine climate regions which represent climatically consistent states. As measured by satellite, changes in national cyanoHAB extent did have a strong increase of 6.9% from 2017 to 2020 (|Kendall's tau (τ)| = 0.56; gamma (γ) = 2.87 years), but had negligible change (|τ| = 0.03) from 2008 to 2011. Two of the nine regions had moderate (0.3 ≤ |τ| < 0.5) increases in spatial extent from 2017 to 2020, and eight of nine regions had negligible (|τ| < 0.2) change from 2008 to 2011. Twelve states had a strong or moderate increase from 2017 to 2020 (|τ| ≥ 0.3), while only one state had a moderate increase and two states had a moderate decrease from 2008 to 2011. A decrease, or no change, in cyanoHAB spatial extent did not indicate a lack of issues related to cyanoHABs. Sensitivity results of randomly omitted daily CONUS scenes confirm that even with reduced data availability during a short four-year temporal assessment, the direction and strength of the changes in spatial extent remained consistent. We present the first set of national maps of lake cyanoHAB spatial extent across CONUS and demonstrate an approach for quantifying past and future changes at multiple spatial scales. Results presented here provide water quality managers information regarding current cyanoHAB spatial extent and quantify rates of change.