Occurrence and characteristics of microplastics across the watershed of the world's third-largest river.

While rivers as primary conduits for land-based plastic particles transferring to their "ultimate" destination, the ocean, have garnered increasing attention, research on microplastic pollution at the scale of whole large river basins remains limited. Here we conducted a large-scale investigation of microplastic contamination in water and sediment of the world's third-largest river, the Yangtze River. We found concentrations of microplastics in water and sediment to be 5.13 items/L and 113.9 items/kg (dry weight), respectively. Moreover, microplastic pollution levels exhibited a clear decreasing trend from upstream to downstream. The detected microplastics were predominantly transparent in color, with fibrous shapes predominating, sizes mainly concentrated below 1 mm and composed primarily of PP and PE polymers. Our analysis results indicated that compared to geographical and water quality parameters, anthropogenic factors primarily determined the spatial distribution pattern of microplastics. Moreover, the microplastic abundance in sediment upstream of the dam was significantly higher than that in the downstream sediment, while the trend of microplastic concentrations in water was opposite. Therefore, more effort is needed to monitor microplastic contamination and their ecological environmental effects of sediment before dams in future research.

Fast 3D 31P B 1 + mapping with a weighted stack of spiral trajectory at 7 T.

PURPOSE: Phosphorus MRS (31P MRS) enables noninvasive assessment of energy metabolism, yet its application is hindered by sensitivity limitations. To overcome this, often high magnetic fields are used, leading to challenges such as spatial B 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneity and therefore the need for accurate flip-angle determination in accelerated acquisitions with short TRs. In response to these challenges, we propose a novel short TR and look-up table-based double-angle method for fast 3D 31P B 1 + $$ {\mathrm{B}}_1^{+} $$ mapping (fDAM). METHODS: Our method incorporates 3D weighted stack-of-spiral gradient-echo acquisitions and a frequency-selective pulse to enable efficient B 1 + $$ {\mathrm{B}}_1^{+} $$ mapping based on the phosphocreatine signal at 7 T. Protocols were optimized using simulations and validated through phantom experiments. The method was validated in the human brain using a 31P 1Ch-trasmit/32Ch-receive coil and skeletal muscle using a birdcage 1H/31P volume coil. RESULTS: The results of fDAM were compared with the classical DAM. A good correlation (r = 0.95) was obtained between the two B 1 + $$ {\mathrm{B}}_1^{+} $$ maps. A 3D 31P B 1 + $$ {\mathrm{B}}_1^{+} $$ mapping in the human calf muscle was achieved in about 10:50 min using a birdcage volume coil, with a 20% extended coverage (number of voxels with SNR > 3) relative to that of the classical DAM (24 min). fDAM also enabled the first full-brain coverage 31P 3D B 1 + $$ {\mathrm{B}}_1^{+} $$ mapping in approximately 10:15 min using a 1Ch-transmit/32Ch-receive coil. CONCLUSION: fDAM is an efficient method for 31P 3D B 1 + $$ {\mathrm{B}}_1^{+} $$ mapping, showing promise for future applications in rapid 31P MRSI.

Soil erodibility mapping using remote sensing and in situ soil data with random forest model in a mountainous catchment of Indian Himalayas.

Land degradation is accelerating in the Himalayan ecosystem, resulting in the loss of soil nutrients due to severe erosion. Soil erosion presents a significant environmental challenge, resulting in both on-site and off-site consequences, such as reduced soil productivity and siltation in reservoirs. Soil erodibility (K factor), an inherent soil property, determines the susceptibility of soils to erosion. Sampling across hilly and mountainous terrain pose challenges due to its complex landscape. Despite these challenges, it is essential to study K factor variations in different land use/land cover types to comprehend the threat of erosion. Digital soil mapping offers an opportunity to overcome this limitation by providing spatial predictions of soil properties. The objective of our study is to map the spatial distribution of soil erodibility using the Random Forest (RF) model, a machine learning method based on sampled in situ soil data and environmental covariates. We collected 556 surface soil samples from the mountainous catchment (Tehri dam catchment) using the stratified random sampling approach. The model performed satisfactorily in both training (r2 = 0.91; RMSE = 0.00185) and testing (r2 = 0.45; RMSE = 0.00318) phases. Subsequently, we generated a digital map with a resolution of 12.5 m to depict the distribution of the K factor. Our analysis revealed that key environmental variables influencing the prediction of the K factor included geology, mean NDVI, and climatic factors. The average K factor value was estimated at 0.0304 and ranging from 0.0251 to 0.0400 t ha h ha-1 MJ-1 mm-1. A higher K factor was observed in the barren land (0.0344) primarily located in the higher and trans-Himalayan region of seasonally snow-covered areas. These areas typically feature young soils with weak soil formation and unstable soil aggregates. Subsequently cropland/cultivated soils (0.0307) exhibited higher K factor values due to the breakdown of soil aggregates by ploughing activities and exposing carbon to decomposition. The average K factor value of evergreen (0.0294) and deciduous (0.0295) forests were the lowest compared to other land use/land cover types indicating the role of forests in resisting soil erosion. By assessing and predicting soil erodibility, land planners and farmers can implement erosion control measures to protect soil health, prevent sedimentation in water bodies, and sustain agricultural productivity in the Himalayas.

Incorporating Implicit Information to Disentangle the Impacts of Hydropower Dams and Climate Change on Basin-Scale Fish Habitat Distribution.

The loss of freshwater fish habitats, exacerbated by climate change and dam constructions, poses a critical environmental concern. The upper Yangtze River basin, noted for its abundant fish fauna and concentrated dam development, serves as a crucial locale for investigating the impacts of climate shifts and dam construction. This study aims to disentangle the impacts of hydroelectric dams and climate change on fish habitat distribution by analyzing species presence data across different periods. Species distribution models were constructed using Maxent for Coreius guichenoti (a warm-water endangered fish) and Schizopygopsis malacanthus (a cold-water endangered fish). The model accuracy was assessed using the area under the curve of the receiver operating characteristic. Habitat distribution modeling and prediction for the pre-dam period (1970-2000) and post-dam period (2001-2020), as well as future climate change under two shared socioeconomic pathways scenarios, were conducted. The impacts of climate change and dam construction on the habitat suitability of two fish species were quantified. The results revealed dam construction predominantly diminished habitat suitability and range, with high-suitability habitats in the post-dam period decreasing by 56.3% (720.18 km) and 67.0% (1665.52 km) for the two fishes, respectively. Climate change would enhance the habitat suitability of Coreius guichenoti, while it would decrease the habitat suitability of Schizopygopsis malacanthus. The impact of dam construction is greater that of climate change for them. This study underscores the profound impacts of dam construction on fish habitats, particularly for cold-water species, and highlights the critical need for habitat restoration in sustainable hydropower development. Our method of disentangling these factors also provides a new approach to evaluating environmental impacts in large river basins.

Impact of parametric seasonal variations on water quality in the Crocodile River and Inyaka Dam in the Mpumalanga Province, South Africa.

This study assessed seasonal variations in water quality and their impact on the Inyaka Dam and Crocodile River in Mpumalanga Province, South Africa. A total of 206 water samples were collected across four seasons to analyse parameters including pH, turbidity, electrical conductivity (EC), temperature, Manganese (Mn), Iron (Fe), phosphate (PO4 3-), nitrate-nitrogen (NO3-N), E. coli, total coliforms, faecal streptococci, and Bifidobacteria. Principal component analysis (PCA) and Pearson correlation identified major pollutants and their seasonal variations, while cluster analysis grouped water quality by parameter fluctuations. Findings indicated that water quality in both the Inyaka Dam and the Crocodile River exceeded permissible limits. In the Inyaka Dam, summer rainfall (202.68 mm) spurred microbial growth, including E. coli and Bifidobacteria, while winter saw elevated levels of PO4 3-, EC, Fe, and NO3-N. The Crocodile River exhibited its poorest water quality in summer, with high levels of conductivity, turbidity, Fe, Mn, and NO3-N, driven largely by rainfall. Winter pollution in the river was marked by E. coli, PO4 3-, total coliforms, NO3-N, and Bifidobacteria. The study highlights significant pollution in the Crocodile River, particularly in summer, linked to rainfall and effluent discharges. Microbial pollution persisted across seasons, influenced by both weather and point-source contamination. The winter season exacerbated water quality deterioration in the Crocodile River due to reduced flow, while Inyaka Dam's winter pollution was attributed to lake stratification.

Relationship of Salmonella Typhimurium 14028 strain and its dam and seqA mutants with gut microbiota dysbiosis in rats.

Introduction. Disruptions in gut microbiota, known as dysbiosis, have been increasingly linked to pathogenic infections, with Salmonella Typhimurium being a notable contributor to these disturbances.Hypothesis. We hypothesize that the S. Typhimurium 14028 WT strain induces significant dysbiosis in the rat gut microbiota and that the dam and seqA genes play crucial roles in this process.Aim. In this study, it was aimed at investigating the dysbiotic activity of the S. Typhimurium 14028 WT strain on the rat gut microbiota and the roles of dam and seqA genes on this activity.Method. Changes in the rat gut microbiota were determined by examining the anal swap samples taken from the experimental groups of these animals using 16S rRNA high-throughput sequencing technology.Results. In the experimental groups, the dominant phyla were determined to be Firmicutes and Bacteroidetes (P<0.05). However, while the rate of Bacteroidetes was significantly reduced in those treated with the WT and seqA mutants, no significant difference was observed in the dam mutant compared to the control group (P<0.05). In all experimental animals, the dominant species was determined to be Prevotella copri, regardless of the experiment time and application. The analysis results of the samples taken on the third day from the rat groups infected with the S. Typhimurium 14028 WT strain (W2) presented the most striking data of this study.Conclusion. Through distance analysis, we demonstrated that a successful Salmonella infection completely changes the composition of the microbiota, dramatically reduces species diversity and richness in the microbiota and encourages the growth of opportunistic pathogens.

Effects of whole-day versus half-day cow-calf contact on cows' and calves' performance.

Cow-calf contact systems (CCCs), where dairy cows nurse their own calves for several weeks while being milked, have some advantages in terms of animal welfare. However, one major challenge is the loss of collected milk due to suckling and milk ejection problems during milking. Reducing daily CCC can decrease milk losses. Our study investigated the effect of half-day CCC during daytime (HC, n = 11 cows) compared to whole-day contact (WC, n = 13) and no contact (NC, n = 14) on harvested milk yield, milk content, udder health, calving interval, and calf weight gain in a dual purpose breed-herd with concentrate-free feeding. 'Nursing' (9 weeks postpartum) was followed by separation of cow and calf, but still with visual CCC and twice daily milk feeding by nipple buckets (6 l per day, 'in sight/milk feeding'). During the 11th-12th week, calves were housed out of sight and gradually weaned. Calves of NC were separated from their mothers 1 day postpartum, obtained 6 l whole-milk per day and were gradually weaned. During 'nursing', NC and HC cows gave more milk than WC in the morning. In the evening, HC and WC gave less milk than NC, but HC cows had also a slightly lower milk yield than WC. During 'nursing', a reduced fat content (-1% point) pointed at milk ejection problems in both CCC treatments independent from daytime. After separation from the calf (periods: 'in sight/milk feeding' and 'out of sight/weaning') and over the whole lactation, milk yield between HC and the other treatments did not significantly differ while WC cows gave less milk than NC cows. Protein contents were higher in dams than in NC. There were no indications of differences in the incidence of mastitis, somatic cell score or calving interval between treatments. During 'nursing', NC calves gained about 0.3 kg less per day than CCC-calves (nNC = 12, nHC = 7, nWC = 10). After separation from the mother, there was a growth check in both CCC groups. During 'in sight/milk feeding', HC gained less weight than NC and WC (nNC = 11, nHC = 9, nWC = 10). Hereafter, weight development did not differ. Two weeks after weaning, nursed calves were still significantly heavier than NC (n  =  5-8). Nine weeks of HC during the day compared to WC helped to reduce losses of sellable milk during the nursing period and over the whole lactation while calf development was similar.

DRA-UNet for Coal Mining Ground Surface Crack Delineation with UAV High-Resolution Images.

Coal mining in the Loess Plateau can very easily generate ground cracks, and these cracks can immediately result in ventilation trouble under the mine shaft, runoff disturbance, and vegetation destruction. Advanced UAV (Unmanned Aerial Vehicle) high-resolution mapping and DL (Deep Learning) are introduced as the key methods to quickly delineate coal mining ground surface cracks for disaster prevention. Firstly, the dataset named the Ground Cracks of Coal Mining Area Unmanned Aerial Vehicle (GCCMA-UAV) is built, with a ground resolution of 3 cm, which is suitable to make a 1:500 thematic map of the ground crack. This GCCMA-UAV dataset includes 6280 images of ground cracks, and the size of the imagery is 256 × 256 pixels. Secondly, the DRA-UNet model is built effectively for coal mining ground surface crack delineation. This DRA-UNet model is an improved UNet DL model, which mainly includes the DAM (Dual Dttention Dechanism) module, the RN (residual network) module, and the ASPP (Atrous Spatial Pyramid Pooling) module. The DRA-UNet model shows the highest recall rate of 77.29% when the DRA-UNet was compared with other similar DL models, such as DeepLabV3+, SegNet, PSPNet, and so on. DRA-UNet also has other relatively reliable indicators; the precision rate is 84.92% and the F1 score is 78.87%. Finally, DRA-UNet is applied to delineate cracks on a DOM (Digital Orthophoto Map) of 3 km2 in the mining workface area, with a ground resolution of 3 cm. There were 4903 cracks that were delineated from the DOM in the Huojitu Coal Mine Shaft. This DRA-UNet model effectively improves the efficiency of crack delineation.

Self-Supervised Dam Deformation Anomaly Detection Based on Temporal-Spatial Contrast Learning.

The detection of anomalies in dam deformation is paramount for evaluating structural integrity and facilitating early warnings, representing a critical aspect of dam health monitoring (DHM). Conventional data-driven methods for dam anomaly detection depend extensively on historical data; however, obtaining annotated data is both expensive and labor-intensive. Consequently, methodologies that leverage unlabeled or semi-labeled data are increasingly gaining popularity. This paper introduces a spatiotemporal contrastive learning pretraining (STCLP) strategy designed to extract discriminative features from unlabeled datasets of dam deformation. STCLP innovatively combines spatial contrastive learning based on temporal contrastive learning to capture representations embodying both spatial and temporal characteristics. Building upon this, a novel anomaly detection method for dam deformation utilizing STCLP is proposed. This method transfers pretrained parameters to targeted downstream classification tasks and leverages prior knowledge for enhanced fine-tuning. For validation, an arch dam serves as the case study. The results reveal that the proposed method demonstrates excellent performance, surpassing other benchmark models.

Establishment of quadratic exponential quality gain-loss function model and design of process mean.

Taking into account the fluctuation of the growth rate on the left and right sides of the classic QGLF, a quadratic exponential quality gain-loss function (QGLF) is created based on the asymmetric QGLF. The two scenarios of non-normal distribution (triangular distribution) and truncated normal distribution of quality characteristic values are optimized using the quadratic exponential quality gain-loss process mean. Through the case study approaches, the empirical validity and applicability of the quadratic exponential QGLF model are thoroughly assessed, confirming its effectiveness in improving quality management practices.

Non-native plants tend to be phylogenetically distant but functionally similar to native plants under intense disturbance at the Three Gorges Reservoir Area.

Darwin's two opposing hypotheses, proposing that non-native species closely or distantly related to native species are more likely to succeed, are known as 'Darwin's Naturalization Conundrum'. Recently, invasion ecologists have sought to unravel these hypotheses. Studies that incorporate rich observational data in disturbed ecosystems that integrate phylogenetic and functional perspectives have potential to shed light on the conundrum. Using 313 invaded plant communities including 46 invasive plant species and 531 native plant species across the Three Gorges Reservoir Area in China, we aim to evaluate the coexistence mechanisms of invasive and native plants by integrating phylogenetic and functional dimensions at spatial and temporal scales. Our findings revealed that invasive plants tended to co-occur more frequently with native plant species that were phylogenetically distant but functionally similar in the reservoir riparian zone. Furthermore, our study demonstrated that the filtering of flood-dry-flood cycles played a significant role in deepening functional similarities of native communities and invasive-native species over time. Our study highlights the contrasting effects of phylogenetic relatedness and functional similarity between invasive and native species in highly flood-disturbed habitats, providing new sights into Darwin's Naturalization Conundrum.

A reliable method to prepare milligram size environmental samples to quantify metal(loid)s by high-resolution graphite furnace atomic absorption spectrometry.

We searched for an extraction method that would allow a precise quantification of metal(loid)s in milligram-size samples using high-resolution graphite furnace atomic absorption spectrometry (HR-GFAAS). We digested biological (DORM-4, DOLT-5 and TORT-3) and sediment (MESS-4) certified reference materials (CRMs) using nitric acid in a drying oven, aqua regia in a drying oven, or nitric acid in a microwave. In addition, we digested MESS-4 using a mixture of nitric and hydrofluoric acids in a drying oven. We also evaluated the effect of sample size (100 and 200 mg) on the extraction efficiency. Nitric acid extraction in a drying oven yielded the greatest recovery rates for all metal(loid)s in all tested CRMs (80.0 %-100.0 %) compared with the other extraction methods tested (67.3 %-99.2 %). In most cases, the sample size did not have a significant effect on the extraction efficiency. Therefore, we conclude that nitric acid digestion in a drying oven is a reliable extraction method for milligram-size samples to quantify metal(loid)s with HR-GFAAS. This validated method could provide substantial benefits to environmental quality monitoring programs by significantly reducing the time and costs required for sample collection, storage, transport and preparation, as well as the amount of hazardous chemicals used during sample extraction and analysis. •Sample digestion with nitric acid in a drying oven yielded the greatest recovery rates of metal(loid)s from biological and sediment certified reference materials.•The recovery rates of metal(loid)s from biological and sediment certified reference materials using nitric acid digestion in a drying oven ranged from 73 % to 100 %.•Digestion with nitric acid in a drying oven is a simple and reliable method to extract small size environmental samples for metal(loid)s quantification by high-resolution graphite furnace atomic absorption spectrometry.

Influence of Infill Patterns on the Shape Memory Effect of Cold-Programmed Additively Manufactured PLA.

In four-dimensional additive manufacturing (4DAM), specific external stimuli are applied in conjunction with additive manufacturing technologies. This combination allows the development of tailored stimuli-responsive properties in various materials, structures, or components. For shape-changing functionalities, the programming step plays a crucial role in recovery after exposure to a stimulus. Furthermore, precise tuning of the 4DAM process parameters is essential to achieve shape-change specifications. Within this context, this study investigated how the structural arrangement of infill patterns (criss-cross and concentric) affects the shape memory effect (SME) of compression cold-programmed PLA under a thermal stimulus. The stress-strain curves reveal a higher yield stress for the criss-cross infill pattern. Interestingly, the shape recovery ratio shows a similar trend across both patterns at different displacements with shallower slopes compared to a higher shape fixity ratio. This suggests that the infill pattern primarily affects the mechanical strength (yield stress) and not the recovery. Finally, the recovery force increases proportionally with displacement. These findings suggest a consistent SME under the explored interval (15-45% compression) despite the infill pattern; however, the variations in the mechanical properties shown by the stress-strain curves appear more pronounced, particularly the yield stress.

Estimation of breed effects and non-additive genetic variation for ostrich slaughter and skin traits.

The study quantified breed effects and putative non-additive genetic variation for quantitative and qualitative slaughter and skin traits involving three ostrich breeds: South African Black (SAB), Zimbabwean Blue (ZB), and Kenyan Red (KR) ostriches. Such data from contemporary slaughter groups with all three pure breeds represented were analyzed together (SAB: n = 457; ZB: n = 74; KR: n = 50). Two 2 × 2 diallel crossbreeding designs were used to assess crosses of ZB and KR birds with the SAB strain. Subsequently, the data from SAB, ZB and their reciprocal crosses, slaughtered together; as well as the data from SAB and KR ostriches, along with their reciprocal crosses, respectively, were analyzed separately. ZB and KR birds outperformed SAB birds for most size-related slaughter and skin traits. Linear contrasts were used to distinguish the effects of breed, heterosis, and the dam line. For the ZB x SAB design, additive breed effects were significant for slaughter weight (10.4%), crust skin size (3.9%) and nodule shape score (1.6%) (all P < 0.05). Significant heterosis were found for slaughter weight (4.3%), crust skin size (1.7%) and nodule size score (3.7%) (P < 0.05). Dam line effects were observed for skin weight (4.1%) and hair follicle score (4.1%). In the KR x SAB design, additive breed effects were like outcomes for the ZB x SAB design. Heterosis estimates were significant (P < 0.05) for slaughter weight (5.8%), crust skin size (2.9%), crown length (1.7%) and nodule size score (4.4%). Dam line effects were significant for slaughter weight (3.7%) and nodule size score (3.8%). In conclusion, ZB and KR birds outperformed their SAB contemporaries for size and size-related traits. Crossbreeding with these genotypes could improve some size-related traits over the mid-parent value of purebreds.

Dam construction alters the traits of health-related microbes along the Yangtze River.

Dams, constructed globally for energy production and water conservation, fragment rivers, and modify flow regimes, thereby altering the composition of biological communities and ecosystem functions. Despite the extensive use of dams, few studies have explored their potential health impacts, particularly concerning changes in health-related genes, such as antibiotic resistance genes (ARGs) and virulence factor genes (VFGs), and their hosts (i.e., ARB and potential pathogens). Understanding these health-related effects is crucial because they can impact human health through water quality and pathogen prevalence. In this study, we investigated the planktonic microbial community in the Three Gorges Reservoir (TGR) and adjacent upstream and downstream areas of the Yangtze River during both the dry and wet season. Our metagenomic analysis showed that dam construction significantly decreased the abundance of ARGs, but it had an insignificant effect on VFGs. The observed reduction in ARGs abundance could be mainly attributed to the decrease abundance of the major ARGs carrier - Limnohabitansin the TGR and downstream areas due to high grazing pressure and fitness cost. Conversely, the abundance of microbes carrying VFGs (potential pathogens) remained stable from upstream to the dam reservoir, which may explain the negligible impact on VFG abundance. Overall, our results provide a detailed understanding of the ecological health implications of dam construction in large river ecosystems.

Impact of run-of-river damming on increasing phytoplankton biomass and species shift in a large Amazonian river.

Run-of-river (ROR) dams, often perceived as having minimal environmental impact, can induce significant hydrodynamic changes that alter aquatic ecosystems. We investigated the impacts of an ROR dam on the Madeira River, the largest Amazon tributary, focusing on phytoplankton communities, their ecological implications, and related environmental factors. Our study examined changes in biomass and environmental factors (using General Linear Mixed Models - GLMM), species composition (using PERMANOVA) before and after damming, in both the main channel and tributaries (N = 549 samples). We also identified indicator species associated with different damming phases and regions through an indicator value analysis. The results showed that, following dam construction, the phytoplankton community changed in both the main channel and tributaries, with a shift from lotic diatoms to lentic phytoflagellates. This transition was likely facilitated by altered hydrodynamics and possibly influenced by the decomposition of flooded vegetation in the dam's influence zone. The decomposition of this vegetation could explain both the observed increase in oxygen consumption and the subsequent rise in phytoflagellate biomass after damming. However, despite the overall increase in phytoplankton biomass, the values remained within oligotrophic to mesotrophic conditions, consistent with the low nutrient concentrations recorded. However, we caution that the dam-created hydrodynamic conditions are optimal for phytoplankton growth, potentially exacerbating nutrient-related issues in the future. We recommend proactive management strategies to prevent nutrient enrichment from activities such as agriculture and livestock in isolated Amazon areas affected by dams, thereby mitigating potential degradation of water quality linked to increased phytoplankton biomass.

Major recent failures in Brazilian mine waste containment facilities, current cases of maximum emergency level and imminent risk of rupture, and a brief sustainability analysis.

Waste is the materials left over after the processing of ores. Significant disasters involving waste disposal structures have occurred in Brazil in recent years and caused severe damage by contaminating soil, rivers and coastal areas, destroying native fauna and flora, interrupting the water supply and compromising its potability, putting the population's health, livelihoods and economy at risk, as well as causing 289 irreparable human deaths. Regulatory laws have become stricter, and since 2019, after the tailings dam tragedies occurred in 2015 and 2019 in Mariana and Brumadinho, in Minas Gerais, the operation of  upstream-raised tailings dams has been prohibited in Brazil. In 2022, a waste slide from a sterile pile at the Pau Branco Mine in Nova Lima promoted a dike overflow. There was the death of five people whose car was buried by a landslide on a hillside. New strategies and technologies, such as reprocessing and recycling, can be tested to ascertain whether they can help improve practices in tailings management. Indeed, mining companies' corporate responsibility and sustainability practices need to be evaluated to verify whether they better match expectations. On the other hand, more specific and detailed regulations and resolutions are required to ensure the safe monitoring and management of sterile waste piles. This paper presents a review of the facts, a discussion of the literature (mainly on recent tailings dam disasters), the current situation of mining-containing waste structures in Brazil, a brief sustainability analysis and perspectives aimed at preventing/minimising catastrophes in the future.

Dormancy regulator Prunus mume DAM6 promotes ethylene-mediated leaf senescence and abscission.

Leaf senescence and abscission in autumn are critical phenological events in deciduous woody perennials. After leaf fall, dormant buds remain on deciduous woody perennials, which then enter a winter dormancy phase. Thus, leaf fall is widely believed to be linked to the onset of dormancy. In Rosaceae fruit trees, DORMANCY-ASSOCIATED MADS-box (DAM) transcription factors control bud dormancy. However, apart from their regulatory effects on bud dormancy, the biological functions of DAMs have not been thoroughly characterized. In this study, we revealed a novel DAM function influencing leaf senescence and abscission in autumn. In Prunus mume, PmDAM6 expression was gradually up-regulated in leaves during autumn toward leaf fall. Our comparative transcriptome analysis using two RNA-seq datasets for the leaves of transgenic plants overexpressing PmDAM6 and peach (Prunus persica) DAM6 (PpeDAM6) indicated Prunus DAM6 may up-regulate the expression of genes involved in ethylene biosynthesis and signaling as well as leaf abscission. Significant increases in 1-aminocyclopropane-1-carboxylate accumulation and ethylene emission in DEX-treated 35S:PmDAM6-GR leaves reflect the inductive effect of PmDAM6 on ethylene biosynthesis. Additionally, ethephon treatments promoted autumn leaf senescence and abscission in apple and P. mume, mirroring the changes due to PmDAM6 overexpression. Collectively, these findings suggest that PmDAM6 may induce ethylene emission from leaves, thereby promoting leaf senescence and abscission. This study clarified the effects of Prunus DAM6 on autumn leaf fall, which is associated with bud dormancy onset. Accordingly, in Rosaceae, DAMs may play multiple important roles affecting whole plant growth during the tree dormancy induction phase.

Experimental study of interception effect by submerged dam on microplastics.

Submerged dam can alter microplastic (MP) transport, and act as a sink for MPs. In this paper, we investigated the interception rates of Polyvinyl chloride (PVC) and Polystyrene (PS) by an artificial submerged dam in a flow flume at first, and found that most of the un-intercepted PVC and PS particles by the dam accumulated behind it under the subcritical (Fr < 1) and turbulent (Re > 500) flows. PVC particles behind the dam mainly concentrated within two dam widths, and the concentration of PS particles decreased with the distance behind the dam lengthening. Then, we performed linear regression fitting and Redundancy Analysis (RDA) between the interception rates collected in 162 experiment tests and environmental factors, including flow velocity, distance to dam and MP concentration. The results showed that the interception rate of PVC and PS particles increased with the distance to dam lengthening, but decreased with the flow velocity and MP concentration heightening. RDA revealed that the interception rate was influenced by flow velocity, distance to dam, and MP concentration from the most to the least. Our findings are believed to contribute to understanding the mechanism of the interception effect of submerged dam on microplastics.

Study on the key ecological factors for the reproduction of Gymnocypris eckloni in the upper reaches of the Yellow River.

The development of hydroelectric projects has adversely affected the reproductive activities of downstream fish species. To facilitate the natural reproduction of fish and restore spawning grounds post-dam construction, it is imperative to explore the ecological factors crucial for their reproduction. Currently, various research methods with different advantages and limitations are employed for this purpose. Using identified spawning locations and periods as clues, we quantitatively investigate the flow velocity, water depth, water temperature, and riverbed substrate required for spawning. The results are validated using habitat simulation methods, aiming to establish a more scientific approach to explore ecological factors affecting fish reproduction. This study provides a more scientific, systematic, and detailed report on the ecological factors required for the spawning of Gymnocypris eckloni: flow velocity ranging from 0.19 to 0.97 m/s, water depth from 0.28 to 1.12 m, water temperature between 11.4 and 15.2°C, and predominantly gravel substrate. The reliability of the results was verified in another spawning ground, with good verification results. This research provides crucial data for the bio-mimetic reproductive technology of Gymnocypris eckloni and the restoration of spawning grounds for natural fish reproduction post-dam construction. It addresses the lack of suitable ecological factor data for protective fish species in the upper reaches of the Yellow River. The method exhibits strong scientific, accurate, and implementable characteristics.