The activities of microbiomes in river sediments play an important role in sustaining ecosystem functions by driving many biogeochemical cycles. However, river ecosystems are frequently affected by anthropogenic activities, which may lead to microbial biodiversity loss and/or changes in ecosystem functions and related services. While parts of the Atlantic Forest biome stretching along much of the eastern coast of South America are protected by governmental conservation efforts, an estimated 89% of these areas in Brazil are under threat. This adds urgency to the characterization of prokaryotic communities in this vast and highly diverse biome. Here, we present prokaryotic sediment communities in the tropical Juliana River system at three sites, an upstream site near the river source in the mountains (Source) to a site in the middle reaches (Valley) and an estuarine site near the urban center of Ituberá (Mangrove). The diversity and composition of the communities were compared at these sites, along with environmental conditions, the former by using qualitative and quantitative analyses of 16S rRNA gene amplicons. While the communities included distinct populations at each site, a suite of core taxa accounted for the majority of the populations at all sites. Prokaryote diversity was highest in the sediments of the Mangrove site and lowest at the Valley site. The highest number of genera exclusive to a given site was found at the Source site, followed by the Mangrove site, which contained some archaeal genera not present at the freshwater sites. Copper (Cu) concentrations were related to differences in communities among sites, but none of the other environmental factors we determined was found to have a significant influence. This may be partly due to an urban imprint on the Mangrove site by providing organic carbon and nutrients via domestic effluents.

Human welfare and biodiversity are at risk due to the deterioration of water and sediment quality. Particularly, in last few decades, global water and sediment quality degraded due to the rapid industrialization and urbanization. This study aimed to determine the concentration of nine heavy metals and metalloid (Pb, Cr, Cd, Hg, As, Mn, Ni, Cu, and Zn) and assess the ecological risks using different pollution indices (e.g., heavy metal pollution index [HPI], Nemerow pollution index [NI], geo-accumulation index [Igeo], contamination factor [CF], degree of contamination [CD] and pollution load index [PLI], ecological risk index [ERI]) in water and sediment of the Shitalakshya River, an industrially affected urban river of Bangladesh. For the first time, 20 water and sediment samples were collected across a wider geographical area of the Shitalakshya River during both monsoon and dry seasons and analyzed using the atomic absorption spectrometer. Average concentrations of heavy metals and metalloid in water were within the Bangladesh standard except for Cr (51.69 ppb) and Mn (228.20 ppb) during monsoon season, portraying potential ecological and human health risks. Besides, average concentration of Mn (549.75 and 370.93 ppb), Ni (549.75 and 370.93 ppb), and Cu (45.34 and 36.09 ppb) in sediment during both seasons were above international standard, implying risk to aquatic sediment biota. The average HPI values indicated moderate to high contamination, whereas the NI values implied polluted water in monsoon season with severe pollution in port area of the river. Similarly, Igeo, CF, CD, and PLI elucidated different levels of contamination in the sediment, particularly during dry season. The ERI values also referred moderate ecological risk in the sediment during dry season. Overall, our findings highlight the alarming level of heavy metal pollution in the Shitalakshya River, necessitating immediate action to protect the aquatic environment, sediment biota, and human health. PRACTITIONER POINTS: This study determined the concentration of heavy metals and metalloid in water and sediment of the Shitalakshya River, Bangladesh. The study revealed that the average concentration of Cr and Mn in water exceeded national standard, whereas Mn, Ni, and Cu in sediment exceeded international limit. Potential ecological risk of heavy metals was also assessed using different pollution indices. Calculated pollution indices indicated different degree of pollution, implying critical ecological condition due to heavy metal pollution in aquatic environment and sediment biota.

Microplastic (MP) pollution has gained considerable attention in various ecosystems; however, it has received relatively less attention in freshwater-riverine environments than in other ecosystems. The Ganges River Delta, one of the world\'s most densely populated areas, is a potential source of MP pollution in the freshwater ecosystem. MPs were identified throughout the year in the lower Ganges River water. Seasonally, the highest abundance was observed during the monsoon (14.66 ± 2.06 MPs/L), followed by the pre-monsoon (13.46 ± 1.75 MPs/L) and post-monsoon (11.50 ± 0.40 MPs/L). Throughout the year, MP discharge was estimated at 4.12 × 1012 to 2.17 × 1013 MPs/year. Fourier transformed infrared spectroscopy identified plastic polymers in the water, like ethylene vinyl acetate, polystyrene, polypropylene, polyethylene, and nylon. Moderate contamination by MPs was assessed throughout the year. Significant correlations between MP abundance and both rainfall and discharge were observed. It is essential to implement preventative measures in the Ganges River Basin to mitigate MP pollution before the situation worsens. PRACTITIONER POINTS: Throughout the year, MP concentration ranged from 10.67 to 20.33 MPs/L The highest MP occurrence was observed in the monsoon season (14.66 ± 2.06 MPs/L) The lowest abundance was detected in the post-monsoon period (11.50 ± 0.40 MPs/L) There was a moderate level of MP contamination in the lower Ganges River water It was shown that discharge and rainfall were correlated with MP abundance.

Land use change stands as the primary factor influencing habitat quality (HQ). Clarifying the spatiotemporal change and the obstacle factors of the coupling relationship between HQ and urbanization level (UL) can provide imperative references for achieving sustainability in the Yellow River Basin (YRB). This study is based on the InVEST model, spatial autocorrelation, and obstacle factor analysis to measure the spatiotemporal dynamics and impediments of the coupling relationship between HQ and UL from 2000 to 2020 in the YRB. The findings were as follows: (1) From 2000 to 2020, the HQ showed a tendency of rise first and then fall, with the pattern of \"High in the middle and west, low in the east\"; (2) from 2000 to 2020, the UL had an upward trend, with the pattern of \"Low in the west, high in the middle and east\"; (3) the coupling and coordination level of HQ and UL in the YRB changed from extreme incoordination to verge of coordination, and it had a distribution pattern of \"High in the east, low in the west\", with the high-value area expanding to the east and the low-value area shrinking to the west. (4) Location condition, climate, proportion of construction land, vegetation index, and proportion of non-agricultural employment are the main obstacle factors that determined the coupling and coordination of the HQ and UL.

BACKGROUND: Phylogeographic studies have gained prominence in linking past geological events to the distribution patterns of biodiversity, primarily in mountainous regions. However, such studies often focus on plant taxa, neglecting the intricate biogeographical patterns of microbes, particularly soil microbial communities. This article explores the spatial distribution of the nematode-trapping fungus Arthrobotrys oligospora, a widespread microorganism, in a tectonically active region at the southeastern edge of the Qinghai-Tibetan Plateau. By analysing the genetic variation of this fungus alongside the historical structure of major river watersheds, we sought to uncover potential connections between the two. Our study involved sampling 149 strains from 116 sites across six major watersheds in the region.
RESULTS: The resulting haplotype network revealed five distinct clusters, each corresponding closely to a specific watershed. These clusters exhibited high haplotype diversity and low nucleotide diversity, supporting the notion of watershed-based segregation. Further analysis of haplotypes shared across watersheds provided evidence for three proposed past river connections. In particular, we found numerous shared haplotypes between the Yangtze and Mekong basins, as well as between the Yangtze and the Red basins. Evidence for a Irrawaddy-Salween-Red and a Yangtze-Pearl-Red river connections were also portrayed in our mapping exercise.
CONCLUSIONS: These findings emphasize the crucial role of historical geomorphological events in shaping the biogeography of microbial biodiversity, alongside contemporary biotic and abiotic factors. Watershed perimeters emerged as effective predictors of such patterns, suggesting their suitability as analytical units for regional-scale studies. Our study also demonstrates the potential of microorganisms and phylogeographic approaches to complement traditional geological analyses, providing a more comprehensive understanding of past landscape structure and its evolution.

Evaluating the impact of large-scale human activities on carbon storage through land use changes is of growing interest in terrestrial ecosystem assessments. The Huaihe River Basin, a vital Chinese grain production area, has undergone marked land use changes amid socio-economic acceleration. Evaluating the impacts of land use change on carbon storage and future carbon sequestration is imperative for regional ecosystem sustainability and Chinese food security, simultaneously, furnishing data support to regional land use planning and decision-making processes. Nonetheless, the mechanisms linking land use changes to carbon storage and the future carbon reservoir responses remain unclear. We utilized a multi-source dataset and representative scenarios, integrating PLUS, InVEST models, and Geodetector to assess land use change impacts on carbon storage in the Huaihe River Basin (2000-2030). The data indicates the following: (1) from 2000 to 2020, cultivated land decreased by 28,344.69 km2, construction land increased by 26,914.56 km2, and other land types changed little. (2) Land use change resulted a carbon loss of 1.17 × 108 t, primarily due to the expansion of construction land. (3) All four simulation scenarios exhibited diminished carbon storage relative to 2020, with the economic development scenario recording the lowest at 4.98 × 109 t and the ecological protection scenario the highest at 5.06 × 109 t. (4) Elevation predominantly drives carbon storage changes, with its interaction with NPP having the greatest impact. The factors synergistically enhance their explanatory power. The research provides a scientific basis for strategies aimed at augmenting regional carbon sequestration and refining low-carbon land management, safeguarding ecosystem stability.

The Yellow River Basin has been instrumental in advancing ecological preservation and fostering national high-quality development. However, since the advent of China\'s reform and opening-up policies, the basin has faced severe environmental pollution issues. This study leverages remote sensing data from 1998 to 2019. As per the \"Basin Scope and Its Historical Changes\" published by the Yellow River Conservancy Commission of the Ministry of Water Resources, the Yellow River Basin is categorized into upstream, midstream, and downstream regions for analysis of their spatial and temporal distribution traits using spatial autocorrelation methods. Additionally, we employed probes to study the effects of 10 factors, including mean surface temperature and air pressure, on PM2.5. The study findings reveal that (1) the annual average concentration of PM2.5 in the Yellow River Basin exhibited a fluctuating trend from 1998 to 2019, initially increasing, then decreasing, followed by another increase before ultimately declining. (2) The air quality in the Yellow River Basin is relatively poor, making it challenging for large-scale areas with low PM2.5 levels to occur. (3) The PM2.5 concentration in the Yellow River Basin exhibits distinct high and low-value concentration areas indicative of air pollution. Low-value areas are predominantly found in the sparsely populated central and southwestern plateau regions of Inner Mongolia, characterized by a better ecological environment. In contrast, high-value areas are prevalent in the inland areas of Northwest China, with poorer natural conditions, as well as densely populated zones with high energy demand and a relatively developed economy. (4) The overall population density in the Yellow River Basin, as well as in the upstream, midstream, and downstream regions, serves as a primary driving factor. (5) The primary drivers in the middle reaches and the entire Yellow River Basin remain consistent, whereas those in the upper and lower reaches have shifted. In the upstream, air pressure emerges as a primary driver of PM2.5, while in the downstream, NDVI and precipitation become the main influencing factors.

Protecting rivers and lakes from pollution is crucial for maintaining the health of aquatic ecosystems and ensuring the well-being of both wildlife and humans. Present study intends to examine the water quality of the Suna River (Eastern Fennoscandia in the European North of Russia) to assess the ecological risk. Widespread methods for assessing water quality based on macrozoobenthos and phytoperiphoton were applied. It was found that in conditions of ultra-fresh waters with high humus content, biotic indicators may indicate pollution of water bodies that do not actually experience significant anthropogenic impact. Ratings ranging from \'poor\' to \'excellent\' were obtained for different stations, reflecting the influence of natural features of different sections of the river. \'Good\' water quality was noted at the river stones biotopes. In river gravel, sand and silt biotopes, as well as all lake biotopes, \'mediocre\' water quality was found. The low anthropogenic income on the river catchment allows us to conclude that most indices for assessing water quality significantly underestimate the results in the natural conditions of Eastern Fennoscandia. Biotic indices EPT, BBI and EBI are most accurate for assessing the water quality of rivers and lakes in Eastern Fennoscandia.

The inverse problem method can be applied to determine the properties of hydrological phenomena and estimate the parameters, which cannot be measured directly. This type of inverse focus can facilitate the implementation of the kinematic wave model (direct model-DM), to fill gaps for lateral inflow rate and runoff depth in watersheds. Thus, the goal of the study was the application of the inverse problem method (IP). The lateral inflow rate was generally obtained as a Fourier transform to represent any watersheds. The study was developed using a small catchment in the Amazon where intense rainfall events occur, producing runoff and sediments, which affect rural populations. Lateral inflow rate and runoff depth were derived using precipitation data and parameters estimated through the KINEROS2 (K2)/direct model (DM) model and the ensuing solution methods with MCMC (Markov chains Monte Carlo)/Fourier transform. The developed method was applied to four rainfall-runoff events, leading to a good fit between the observed and predicted data (Nash-Sutcliffe coefficients between 0.76 and 0.85 and RMSE values between 1.80 mm and 6.72 mm).