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Freshwater biodiversity conservation has received substantial attention in the scientific literature and is finally being recognized in policy frameworks such as the Global Biodiversity Framework and its associated targets for 2030. This is important progress. Nonetheless, freshwater species continue to be confronted with high levels of imperilment and widespread ecosystem degradation. An Emergency Recovery Plan (ERP) proposed in 2020 comprises six measures intended to "bend the curve" of freshwater biodiversity loss, if they are widely adopted and adequately supported. We review evidence suggesting that the combined intensity of persistent and emerging threats to freshwater biodiversity has become so serious that current and projected efforts to preserve, protect and restore inland-water ecosystems may be insufficient to avert substantial biodiversity losses in the coming decades. In particular, climate change, with its complex and harmful impacts, will frustrate attempts to prevent biodiversity losses from freshwater ecosystems already affected by multiple threats. Interactions among these threats will limit recovery of populations and exacerbate declines resulting in local or even global extinctions, especially among low-viability populations in degraded or fragmented ecosystems. In addition to impediments represented by climate change, we identify several other areas where the absolute scarcity of fresh water, inadequate scientific information or predictive capacity, and a widespread failure to mitigate anthropogenic stressors, are liable to set limits on the recovery of freshwater biodiversity. Implementation of the ERP rapidly and at scale through many widely dispersed local actions focused on regions of high freshwater biodiversity and intense threat, together with an intensification of ex-situ conservation efforts, will be necessary to preserve native freshwater biodiversity during an increasingly uncertain climatic future in which poorly understood, emergent and interacting threats have become more influential. But implementation of the ERP must be accompanied by measures that will improve water, energy and food security for humans - without further compromising the condition of freshwater ecosystems. Unfortunately, the inadequate political implementation of policies to arrest widely recognized environmental challenges such as climate change do not inspire confidence about the possible success of the ERP. In many parts of the world, the Anthropocene future seems certain to include extended periods with an absolute scarcity of uncontaminated surface runoff that will inevitably be appropriated by humans. Unless there is a step-change in societal awareness of - and commitment to - the conservation of freshwater biodiversity, together with necessary actions to arrest climate change, implementation of established methods for protecting freshwater biodiversity may not bend the curve enough to prevent continued ecosystem degradation and species loss.

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Inland waters (rivers, lakes, and reservoirs) and wetlands (marshes and coastal wetlands) represent large and continuous sources of nitrous oxide (N2O) emissions, in view of adequate biomass and anaerobic conditions. Considerable uncertainties remain in quantifying spatially explicit N2O emissions from aquatic systems, attributable to the limitations of models and a lack of comprehensive data sets. Herein, we conducted a synthesis of 1659 observations of N2O emission rates to determine the major environmental drivers across five aquatic systems. A framework for spatially explicit estimates of N2O emissions in China was established, employing a data-driven approach that upscaled from site-specific N2O fluxes to robust multiple-regression models. Results revealed the effectiveness of models incorporating soil organic carbon and water content for marshes and coastal wetlands, as well as water nitrate concentration and dissolved organic carbon for lakes, rivers, and reservoirs for predicting emissions. Total national N2O emissions from inland waters and wetlands were 1.02 × 105 t N2O yr-1, with contributions from marshes (36.33%), rivers (27.77%), lakes (25.27%), reservoirs (6.47%), and coastal wetlands (4.16%). Spatially, larger emissions occurred in the Songliao River Basin and Continental River Basin, primarily due to their substantial terrestrial biomass. This study offers a vital national inventory of N2O emissions from inland waters and wetlands in China, providing paradigms for the inventorying work in other countries and insights to formulate effective mitigation strategies for climate change.

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Carbon dioxide (CO2) production and emissions from inland waters play considerable roles in global atmospheric CO2 sources, while there are still uncertainties regarding notable nutrient inputs and anthropogenic activities. Urban inland waters, with frequently anthropogenic modifications and severely nitrogen loadings, were hotspots for CO2 emissions. Here, we investigated the spatiotemporal patterns of partial pressure of CO2 (pCO2) and CO2 fluxes (FCO2) in typical urban inland waters in Tianjin, China. Our observation indicated that pCO2 values were oversaturated in highly polluted waters, particularly in sewage rivers and urban rivers, exhibiting approximately 9 times higher than the atmosphere equilibrium concentration during sampling campaigns. Obviously, the spatiotemporal distributions of pCO2 and FCO2 emphasized that the water environmental conditions and anthropogenic activities jointly adjusted primary productivity and biological respiration of inland waters. Meanwhile, statistically positive correlations between pCO2/FCO2 and NH4+-N/NO3--N (p < 0.05) suggested that nitrogen biogeochemical processes, especially the nitrification, played a dominant role in CO2 emissions attributing to the water acidification that stimulated CO2 production and emissions. Except for slight CO2 sinks in waters with low organic contents, the total CO2 emissions from the urban surface waters of Tianjin were remarkable (286.8 Gg yr-1). The results emphasized that the reductions of nitrogen loadings, sewage draining waters, and agricultural pollution could alleviate CO2 emissions from urban inland waters.

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Cyanobacterial blooms introduce autochthonous dissolved organic matter (DOM) into aquatic environments, but their impact on surface water photoreactivity has not been investigated through collaborative field sampling with comparative laboratory assessments. In this work, we quantified the apparent quantum yields (Φapp,RI) of reactive intermediates (RIs), including excited triplet states of dissolved organic matter (3DOM*), singlet oxygen (1O2), and hydroxyl radicals (•OH), for whole water samples collected by citizen volunteers from more than 100 New York lakes. Multiple comparisons tests and orthogonal partial least-squares analysis identified the level of cyanobacterial chlorophyll a as a key factor in explaining the enhanced photoreactivity of whole water samples sourced from bloom-impacted lakes. Laboratory recultivation of bloom samples in bloom-free lake water demonstrated that apparent increases in Φapp,RI during cyanobacterial growth were likely driven by the production of photoreactive moieties through the heterotrophic transformation of freshly produced labile bloom exudates. Cyanobacterial proliferation also altered the energy distribution of 3DOM* and contributed to the accelerated transformation of protriptyline, a model organic micropollutant susceptible to photosensitized reactions, under simulated sunlight conditions. Overall, our study provides insights into the relationship between the photoreactivity of surface waters and the limnological characteristics and trophic state of lakes and highlights the relevance of cyanobacterial abundance in predicting the photoreactivity of bloom-impacted surface waters.

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Human activities have long impacted the health of Earth's rivers and lakes. These inland waters, crucial for our survival and productivity, have suffered from contamination which allows the formation and spread of antibiotic-resistant genes (ARGs) and consequently, ARG-carrying pathogens (APs). Yet, our global understanding of waterborne pathogen antibiotic resistance remains in its infancy. To shed light on this, our study examined 1240 metagenomic samples from both open and closed inland waters. We identified 22 types of ARGs, 19 types of mobile genetic elements (MGEs), and 14 types of virulence factors (VFs). Our findings showed that open waters have a higher average abundance and richness of ARGs, MGEs, and VFs, with more robust co-occurrence network compared to closed waters. Out of the samples studied, 321 APs were detected, representing a 43 % detection rate. Of these, the resistance gene 'bacA' was the most predominant. Notably, AP hotspots were identified in regions including East Asia, India, Western Europe, the eastern United States, and Brazil. Our research underscores how human activities profoundly influence the diversity and spread of resistome. It also emphasizes that both abiotic and biotic factors play pivotal roles in the emergence of ARG-carrying pathogens.

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Widespread eutrophication has been considered as the most serious environment problems in the world. Given the critical roles of lakes in human society and serious negative effects of water eutrophication on lake ecosystems, it is thus fundamentally important to monitor and assess water trophic status of lakes. However, a reliable model for accurately estimating the trophic state index (TSI) of lakes across a large-scale region is still lacking due to their high complexity. Here, we proposed an optical mechanism-based deep learning approach to remotely estimate TSI of lakes based on Landsat images. The approach consists of two steps: (1) determining the optical indicators of TSI and modeling the relationship between them, and (2) developing an approach for remotely deriving the determined optical indicator from Landsat images. With a large number of in situ datasets measured from lakes (2804 samples from 88 lakes) across China with various optical properties, we trained and validated three machine learning methods including deep neural network (DNN), k-nearest neighbors (KNN) and random forest (RF) to model TSI with the optical indicators and TSI and derive the determined optical indicator from Landsat images. The results showed that (1) the total absorption coefficients of optically active constituents at 440 nm (at-w(440)) performs best in characterizing TSI, and (2) DNN outperforms other models in the inversion of both TSI and at-w(440). Overall, our proposed optical mechanism-based deep learning approach demonstrated a robust and satisfactory performance in assessing TSI using Landsat images (root mean squared error (RMSE) = 5.95, mean absolute error (MAE) = 4.81). This highlights its merit as a nationally-adopted method in lake water TSI estimation, enabling the convenience of the acquisition of water eutrophic information in large scale, thereby assisting us in managing lake ecology. Therefore, we assessed water TSI of 961 lakes (>10 km2) across China using the proposed approach. The resulting at-w(440) and TSI ranged from 0.01 m-1 to 31.42 m-1 and from 6 to 96, respectively. Of all these studied lakes, 96 lakes (11.40 %) were oligotrophic, 338 lakes were mesotrophic (40.14 %), 360 lakes were eutrophic (42.76 %), and 48 were hypertrophic (5.70 %) in 2020.

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Microorganisms are integral to freshwater ecological functions and, reciprocally, their activity and diversity are shaped by the ecosystem state. Yet, the diversity of bacterial community and its driving factors at a large scale remain elusive. To bridge this knowledge gap, we delved into an analysis of 16S RNA gene sequences extracted from 929 water samples across China. Our analyses revealed that inland water bacterial communities showed a weak latitudinal diversity gradient. We found 530 bacterial genera with high relative abundance of hgcI clade. Among them, 29 core bacterial genera were identified, that is strongly linked to mean annual temperature and nutrient loadings. We also detected a non-linear response of bacterial network complexity to the increasing of human pressure. Mantel analysis suggested that MAT, HPI and P loading were the major factors driving bacterial communities in inland waters. The map of taxa abundance showed that the abundant CL500-29 marine group in eastern and southern China indicated high eutrophication risk. Our findings enhance our understanding of the diversity and large-scale biogeographic pattern of bacterial communities of inland waters and have important implications for microbial ecology.

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Nitrous oxide (N2O) is a long-lived greenhouse gas and currently contributes ∼10% to global greenhouse warming. Studies have suggested that inland waters are a large and growing global N2O source, but whether, how, where, when, and why inland-water N2O emissions changed in the Anthropocene remains unclear. Here, we quantify global N2O formation, transport, and emission along the aquatic continuum and their changes using a spatially explicit, mechanistic, coupled biogeochemistry-hydrology model. The global inland-water N2O emission increased from 0.4 to 1.3 Tg N yr-1 during 1900-2010 due to (1) growing N2O inputs mainly from groundwater and (2) increased inland-water N2O production, largely in reservoirs. Inland waters currently contribute 7 (5-10)% to global total N2O emissions. The highest inland-water N2O emissions are typically in and downstream of reservoirs and areas with high population density and intensive agricultural activities in eastern and southern Asia, southeastern North America, and Europe. The expected continuing excessive use of nutrients, dam construction, and development of suboxic conditions in aging reservoirs imply persisting high inland-water N2O emissions.

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Methane (CH4) supersaturation in oxygenated waters is a widespread phenomenon despite the traditional perception of strict anoxic methanogenesis. This notion has recently been challenged by successive findings of processes and mechanisms that produce CH4 in oxic environments. While some of the processes contributing to the vertical accumulation of CH4 in the oxygenated upper water layers of freshwater lakes have been identified, temporal variations as well as drivers are still poorly understood. In this study, we investigated the accumulation of CH4 in oxic water layers of two contrasting lakes in Germany: Lake Willersinnweiher (shallow, monomictic, eutrophic) and Lake Stechlin (deep, dimictic, eutrophic) from 2019 to 2020. The dynamics of isotopic values of CH4 and the role of potential precursor compounds of oxic CH4 production were explored. During the study period, persistent strong CH4 supersaturation (relative to air) was observed in the surface waters, mostly concentrated around the thermocline. The magnitude of vertical CH4 accumulation strongly varied over season and was generally more pronounced in shallow Lake Willersinnweiher. In both lakes, increases in CH4 concentrations from the surface to the thermocline mostly coincided with an enrichment in 13C-CH4 and 2H-CH4, indicating a complex interaction of multiple processes such as CH4 oxidation, CH4 transport from littoral sediments and oxic CH4 production, sustaining and controlling this CH4 supersaturation. Furthermore, incubation experiments with 13C- and 2H-labelled methylated P-, N- and C- compounds clearly showed that methylphosphonate, methylamine and methionine acted as potent precursors of accumulating CH4 and at least partly sustained CH4 supersaturation. This highlights the need to better understand the mechanisms underlying CH4 accumulation by focusing on production and transport pathways of CH4 and its precursor compounds, e.g., produced via phytoplankton. Such knowledge forms the foundation to better predict aquatic CH4 dynamics and its subsequent rates of emission to the atmosphere.

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Pollution by synthetic polymers is even more problematic to the environment when this material is fragmented into small portions, forming microplastics (MPs). We analyzed the contamination of ichthyofauna by MPs in an important river of the Atlantic Rainforest in regard to abundance, diversity of morphotypes, polymers, colors, and sizes of the synthetic particles in 20 species of fish. Fish were collected in November 2019 and in March 2020 in five sites along the Pomba River. Of the 101 fish analyzed, 49 (49%) presented MPs in at least one organ. Of the 20 species of fish collected 13 included individuals with at least one MP in their analyzed organs. The organs, trophic categories and feeding areas did not affect the general abundance of MPs types. Blue MPs were predominant, followed by the colors black, red, and white. MP fibers represented 91% of total MPs. Most MPs were between 2 and 3 mm in size. Polyethylene terephthalate (PET), polypropylene (PP), polyamide (PA), polyvinylidene chloride "Nylon" (PVDC), and high-density polyethylene (HDPE) were detected in the fishes. The exposure of the fish species to MPs was associated mainly with individual size and species-specific aspects, regardless of ecological traits. Considering that 55% of the fish species studied are consumed by humans, it is necessary to study the potential impact of MP ingestion on human health and to understand to what extent we may be consuming both plastic particles and contaminants that are adsorbed to MPs.

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In recent years, under the dual pressure of climate change and human activities, the cyanobacteria blooms in inland waters have become a threat to global aquatic ecosystems and the environment. Phycocyanin (PC), a diagnostic pigment of cyanobacteria, plays an essential role in the detection and early warning of cyanobacterial blooms. In this context, accurate estimation of PC concentration in turbid waters by remote sensing is challenging due to optical complexity and weak optical signal. In this study, we collected a comprehensive dataset of 640 pairs of in situ measured pigment concentration and the Ocean and Land Color Instrument (OLCI) reflectance from 25 lakes and reservoirs in China during 2020-2022. We then developed a framework consisting of the water optical classification algorithm and three candidate algorithms: baseline height, band ratio, and three-band algorithm. The optical classification method used remote sensing reflectance (Rrs) baseline height in three bands: Rrs(560), Rrs(647) and Rrs(709) to classify the samples into five types, each with a specific spectral shape and water quality character. The improvement of PC estimation accuracy for optically classified waters was shown by comparison with unclassified waters with RMSE = 72.6 µg L-1, MAPE = 80.4 %, especially for the samples with low PC concentration. The results show that the band ratio algorithm has a strong universality, which is suitable for medium turbid and clean water. In addition, the three-band algorithm is only suitable for medium turbid water, and the line height algorithm is only suitable for high PC content water. Furthermore, the five distinguished types with significant differences in the value of the PC/Chla ratio well indicated the risk rank assessment of cyanobacteria. In conclusion, the proposed framework in this paper solved the problem of PC estimation accuracy problem in optically complex waters and provided a new strategy for water quality inversion in inland waters.

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Rivers are known for carrying out a fundamental role in the transportation of human debris from continental areas to the marine environment and have been identified as hotspots for plastic pollution. We characterized microplastics (MPs) along confluence areas in the Paraíba do Sul River basin, the biggest river in southeastern Brazil. This water body crosses highly industrialized areas, with the highest population density, and the major water demand in South America. Considering the important ecological function of this extensive watershed and the implications of MP pollution, we evaluate the spatial variation of MP concentration in the confluence areas and upstream from the confluence. Samples were taken from the superficial layer of the water column in February and June 2022, using manta net with 300 µm mesh size. A total of 19 categories and 2870 plastic particles were determined. The confluences areas of rivers showed the highest concentration of MPs, highlighting the confluences of the Paraiba do Sul and Muriaé rivers (0.71 ± 0.25 MP/m3), followed by Paraíba do Sul and Dois Rios rivers (0.42 ± 0.23 MP/m3) and Paraíba do Sul and Pomba rivers (0.38 ± 0.14 MP/m3). Black fibers were the main category, followed by blue fibers and blue fragments. The MPs in the surface waters of Paraíba do Sul River is significantly influenced by the sampling points spatiality. This result corroborates other studies around the world and reinforces the argument that affluents are important sources for the introduction of MPs in larger rivers. Nevertheless, our results provide a better understanding of the different contributing factors and occurrence of MPs in river basins.

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Constituents and functionality of urban inland waters are significantly perturbed by municipal sewage inputs and tailwater discharge from wastewater treatment plants. However, large knowledge gaps persist in understanding greenhouse gas dynamics in urban inland waters due to a lack of in situ measurements. Herein, via a 3-year field campaign (2018-2020), we report river and lake CO2 emission and related aquatic factors regulating the emission in the municipality of Beijing. Mean pCO2 (546 ± 481 µatm) in the two urban lakes was lower than global non-tropical freshwater lakes and CO2 flux in 47% of the lake observations was negative. Though average pCO2 in urban rivers (3124 ± 3846 µatm) was among the higher range of global rivers (1300-4300 µatm), average CO2 flux was much lower than the global river average (99.7 ± 147.5 versus 358.4 mmol m-2 d-1). The high pCO2 cannot release to the atmosphere due to the low gas exchange rate in urban rivers (average k600 of 1.3 ± 1.3 m d-1), resulting in low CO2 flux in urban rivers. Additionally, eutrophication promotes photosynthetic uptake and aquatic organic substrate production, leading to no clear relationships observed between pCO2 and phytoplankton photosynthesis or dissolved organic carbon. In consistence with the findings, CO2 emission accounted for only 32% of the total greenhouse gas (GHG) emission equivalence (CO2, CH4 and N2O) in Beijing waters, in contrast to a major role of anthropogenic CO2 to anthropogenic GHG in the atmosphere in terms of radiative forcing (66%). These results pointed to unique GHG emission profiles and the need for a special account of urban inland waters in terms of aquatic GHG emissions.

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Studies of plastic contamination in freshwater ecosystems and their biota remain scarce, despite the fact that the vast majority of plastic waste initially passes through lotic ecosystems. Biomonitoring provides valuable information regarding plastic pollution and microplastic threats to biota and human health. The aim of this study was to explore the potential use of a non-indigenous fish species as a bioindicator of microplastic pollution in an Eastern Mediterranean River. Our study area is located in a heavily modified and vastly impacted urban river which flows through the largest part of the Metropolitan area of Athens, Greece. We used an introduced chub species (Squalius vardarensis) to assess microplastic ingestion in the river. The results indicated moderate occurrence and abundance of microplastics in the fish gastrointestinal tracts; one-third of specimens (35%) contained microplastics, although the average number of microplastics per specimen was relatively low (1.7 ± 0.2). Overall, the abundance of microplastics in the water confirmed the moderate level of microplastics contamination in our study area. The major polymer types of microplastics identified by FT-IR analysis were: polyethylene (PE), polyvinyl alcohol (PVA) and polypropylene (PP); reflecting the fragmentation of larger litter from industrial packaging and/or household goods. Surface runoff of the urban environment, via motorways and major road networks, could be the contributing factor to the reported microplastics. Our results suggest that generalist's non-indigenous species such as chubs could be used as bioindicators of microplastics in inland waters. Introduced fishes can be a feasible, nondestructive, and cost-effective option for the assessment of microplastics in freshwater ecosystems, while freshwater chubs' high abundance and omnipresence in European rivers further serve this scope. However, it is worth noting that the suitability of any particular species as a bioindicator of microplastics may depend on a variety of factors, including their feeding behavior, habitat, and exposure to microplastics in their environment.

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Natural, inland alkaline soda waters form a particular type of saline waters, characterized by a permanent alkaline chemical property. In many cases only the total alkalinity by methyl-orange titration is reported, without phenolphthalein titration. Therefore, a reliable estimation of carbonates from total alkalinity is essential for a precise scientific chemical classification. The concentration of bicarbonate [HCO3 ‒] can be reliably estimated in waters using the Advanced Speciation Method (ASM) if methyl-orange total alkalinity titration and pH data are available, while the concentration of carbonate [CO3 2‒] is not reliably estimated by the ASM when interfering factors with acid/base properties (e.g., phosphate, silicate, ammonia, etc.) are present in significant concentrations in natural waters. Therefore, here I present and prove an experimental polynomial function for carbonate estimation with the following equation based on the concentration of bicarbonate: [CO3 2‒] = -2.878E-7 ± 5.438E-8 × [HCO3 ‒]2 + 0.069±0.003 × [HCO3 ‒] This Boros's carbonate estimation method can contribute to a more efficient evaluation of field water samples with several analytical difficulties.•Bicarbonate can be reliably estimated using the Advanced Speciation Method (ASM).•Estimation of the carbonate concentration using ASM in the presence of interfering acid/base factors in alkaline waters.•Experimental polynomial function for reliable carbonate estimation in alkaline soda waters.

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Global eutrophication and climate warming exacerbate production of cyanotoxins such as microcystins (MCs), presenting risks to human and animal health. Africa is a continent suffering from severe environmental crises, including MC intoxication, but with very limited understanding of the occurrence and extent of MCs. By analysing 90 publications from 1989 to 2019, we found that in various water bodies where MCs have been detected so far, the concentrations were 1.4-2803 times higher than the WHO provisional guideline for human lifetime exposure via drinking water (1 µg/L) in 12 of 15 African countries where data were available. MCs were relatively high in the Republic of South Africa (averaged 2803 µg/L) and Southern Africa as a whole (702 µg/L) when compared to other regions. Values were higher in reservoirs (958 µg/L) and lakes (159 µg/L) than in other water types, and much higher in temperate (1381 µg/L) than in arid (161 µg/L) and tropical (4 µg/L) zones. Highly significant positive relationships were found between MCs and planktonic chlorophyll a. Further assessment revealed high ecological risk for 14 of the 56 water bodies, with half used as human drinking water sources. Recognizing the extremely high MCs and exposure risk in Africa, we recommend routine monitoring and risk assessment of MCs be prioritized to ensure safe water use and sustainability in this region.

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Elucidating the sources of particulate organic matter (POM) is the foundation for understanding their fates and the seasonal variation of their movement from the land-to-ocean aquatic continuum (LOAC). The POM from different sources has different reactivity, which determines their fates. However, the key link between the sources and fates of POM, especially in the complex land use watersheds in bays is still unclear. Stable isotopes and contents of organic carbon and nitrogen were applied to reveal them in a complex land use watershed with different gross domestic production (GDP) in a typical Bay, China. Our results showed that the POMs preserved in suspended particulate organic matter (SPM) were weakly controlled by assimilation and decomposition in the main channels. Source apportionments of SPM in the rural area were controlled by soil (46 % ~ 80 %), especially inert soils eroded from land to water due to precipitation. The contribution of phytoplankton resulted from slower water velocity and longer residence time in the rural area. The soil (47 % ~ 78 %) and manure and sewage (10 % ~ 34 %) were the two major contributors to SOMs in the developed and developing urban areas. The manure and sewage were important sources of active POM in the urbanization of different LUI, which showed discrepancies in the three urban areas (10 % ~ 34 %). Due to soil erosion and the most intensive industry supported by GDP, the soil (45 % ~ 47 %) and industrial wastewater (24 % ~ 43 %) were the two major contributors to SOMs in the industrial urban area. This study demonstrated the close relationship between the sources and fates of POM with complex land use patterns, which could reduce uncertainties in future estimates of the LOAC fluxes and secure ecological and environmental barriers in a bay area.

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Eutrophication is one of the major threats to the inland water ecosystem. Satellite remote sensing provides a promising way to monitor trophic state at large spatial scale in an efficient manner. Currently, most satellite-based trophic state evaluation approaches have focused on water quality parameters retrieval (e.g., transparency, chlorophyll-a), based on which trophic state was evaluated. However, the retrieval accuracies of individual parameter do not meet the demand for accurate trophic state evaluation, especially for the turbid inland waters. In this study, we proposed a novel hybrid model to estimate trophic state index (TSI) by integrating multiple spectral indices associated with different eutrophication level based on Sentinel-2 imagery. The TSI estimated by the proposed method agreed well with the in-situ TSI observations, with root mean square error (RMSE) of 6.93 and mean absolute percentage error (MAPE) of 13.77%. Compared with the independent observations from Ministry of Ecology and Environment, the estimated monthly TSI also showed good consistency (RMSE=5.91,MAPE=10.66%). Furthermore, the congruent performance of the proposed method in the 11 sample lakes (RMSE=5.91,MAPE=10.66%) and the 51 ungauged lakes (RMSE=7.16,MAPE=11.56%) indicated the favorable model generalization. The proposed method was then applied to assess the trophic state of 352 permanent lakes and reservoirs across China during the summers of 2016-2021. It showed that 10%, 60%, 28%, and 2% of the lakes/reservoirs are in oligotrophic, mesotrophic, light eutrophic, and middle eutrophic states respectively. Eutrophic waters are concentrated in the Middle-and-Lower Yangtze Plain, the Northeast Plain, and the Yunnan-Guizhou Plateau. Overall, this study improved the trophic state representativeness and revealed trophic state spatial distribution of Chinese inland waters, which has the significant meanings for aquatic environment protection and water resource management.

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Accurate remote sensing of the Secchi disk depth (ZSD) in waters is beneficial for large-scale monitoring of the aquatic ecology of inland lakes. Herein, an improved algorithm (termed as ZSD20 in this work) for retrieving ZSD was developed from field measured remote sensing data and is available for various waters including clear waters, slightly turbid waters, and highly turbid waters. The results show that ZSD20 is robust in estimating ZSD in various inland waters. After further validation with an independent in situ dataset from 12 inland waters (0.1 m < ZSD < 18 m), the developed algorithm outperformed the native algorithm, with the mean absolute square percentage error (MAPE) reduced from 32.8 to 19.4%, and root mean square error (RMSE) from 0.87 to 0.67 m. At the same time, the new algorithm demonstrates its generality in various mainstreaming image data, including Ocean and Land Color Instrument (OLCI), Geostationary Ocean Color Imager (GOCI), and Moderate Resolution Imaging Spectroradiometer (MODIS). Finally, the algorithm's application was implemented in 410 waters of China based on Sentinel-2 MSI imagery to elucidate the spatiotemporal variation of water clarity during 2015 and 2021. The new algorithm reveals great potential for estimating water clarity in various inland waters, offering important support for protection and restoration of aquatic environments.

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Water temperature is one of the main abiotic factors affecting the structure and functioning of aquatic ecosystems and its alteration can have important effects on biological communities. Macroinvertebrates are excellent bio-indicators and have been used for decades to assess the status of aquatic ecosystems as a result of environmental stresses; however, their responses to temperature are poorly documented and have not been systematically evaluated. The aims of this review are: (i) to collate and summarize responses of freshwater macroinvertebrates to different temperature conditions, comparing the results of experimental and theoretical studies; (ii) to understand how the focus of research on the effects of temperature on macroinvertebrates has changed during the last 51 years; and (iii) to identify research gaps regarding temperature responses, ecosystem types, organism groups, spatiotemporal scales, and geographical regions to suggest possible research directions. We performed a comparative assessment of 223 publications that specifically consider freshwater macroinvertebrates and address the effects of temperature. Short-term studies performed in the laboratory and focusing on insects exposed to a range of temperatures dominated. Field studies were carried out mainly in Europe, at catchment scale and almost exclusively in rivers; they mainly investigated responses to water thermal regime at the community scale. The most frequent biological responses tested were growth rate, fecundity and the time and length of emergence, whereas ecological responses mainly involved composition, richness, and distribution. Thermal research on freshwater macroinvertebrates has undergone a shift since the 2000s when studies involving extended spatiotemporal scales and investigating the effects of global warming first appeared. In addition, recent studies have considered the effects of temperature at genetic and evolutionary scales. Our review revealed that the effects of temperature on macroinvertebrates are manifold with implications at different levels, from genes to communities. However, community-level physiological, phenological and fitness responses tested on individuals or populations should be studied in more detail given their macroecological effects are likely to be enhanced by climate warming. In addition, most field studies at regional scales have used air temperature as a proxy for water temperature; obtaining accurate water temperature data in future studies will be important to allow proper consideration of the spatial thermal heterogeneity of water bodies and any effects on macroinvertebrate distribution patterns. Finally, we found an uneven number of studies across different ecosystems and geographic areas, with lentic bodies and regions outside the West underrepresented. It will also be crucial to include macroinvertebrates of high-altitude and tropical areas in future work because these groups are most vulnerable to climate warming for multiple reasons. Further studies on temperature-macroinvertebrate relationships are needed to fill the current gaps and facilitate appropriate conservation strategies for freshwater ecosystems in an anthropogenic-driven era.

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