Multiscale land use impacts on water quality: Assessment, planning, and future perspectives in Brazil

Research on provincial water resources carrying capacity and coordinated development in China based on combined weighting TOPSIS model

With the continuous development of the economy and society, along with the sustained population growth, the issue of water resources carrying capacity in China has attracted increasing attention. This paper constructs a model for evaluating the provincial water resources carrying capacity in China from four dimensions: water, economy, society, and ecology. Utilizing this model, we analyze the spatiotemporal variations in water resources carrying capacity among 31 provinces in China from 2005 to 2021. Additionally, we delve into the coupling coordination and influencing factors of water resources carrying capacity. The study reveals an overall increasing trend in China's water resources carrying capacity index, with the ecological indicator exhibiting the most significant growth while the water resources sub-indicator lags behind. There are notable regional differences, with higher water resources carrying capacity observed in the eastern coastal areas and relatively lower capacity in the western regions. The ecological criterion becomes a core factor constraining water resources carrying capacity from 2005 to 2015, gradually giving way to the prominence of the social criterion since 2015. The coordination degree is relatively higher in the eastern regions, more scattered in the western regions, and relatively stable in the central regions. Based on the research findings, a series of recommendations are proposed, including strengthening environmental protection policies, optimizing water resources management mechanisms, improving water use efficiency, and promoting economic structural diversification. These suggestions aim to facilitate the sustainable development of water resources carrying capacity in China.

Modelling relationships between land use and water quality using statistical methods: A critical and applied review

Land use/land cover (LULC) can have significant impacts on water quality and the health of aquatic ecosystems. Consequently, understanding and quantifying the nature of these impacts is essential for the development of effective catchment management strategies. This article provides a critical review of the literature in which the use of statistical methods to model the impacts of LULC on water quality is demonstrated. A survey of these publications, which included hundreds of original research and review articles, revealed several common themes and findings. However, there are also several persistent knowledge gaps, areas of methodological uncertainty, and questions of application that require further study and clarification. These relate primarily to appropriate analytical scales, the significance of landscape configuration, the estimation and application of thresholds, as well as the potentially confounding influence of extraneous variables. Moreover, geographical bias in the published literature means that there is a need for further research in ecologically and climatically disparate regions, including in less developed countries of the Global South. The focus of this article is not to provide a technical review of statistical techniques themselves, but to examine important practical and methodological considerations in their application in modelling the impacts of LULC on water quality.

3D human pose data augmentation using Generative Adversarial Networks for robotic-assisted movement quality assessment

In the realm of human motion recognition systems, the augmentation of 3D human pose data plays a pivotal role in enriching and enhancing the quality of original datasets through the generation of synthetic data. This augmentation is vital for addressing the current research gaps in diversity and complexity, particularly when dealing with rare or complex human movements. Our study introduces a groundbreaking approach employing Generative Adversarial Networks (GANs), coupled with Support Vector Machine (SVM) and DenseNet, further enhanced by robot-assisted technology to improve the precision and efficiency of data collection. The GANs in our model are responsible for generating highly realistic and diverse 3D human motion data, while SVM aids in the effective classification of this data. DenseNet is utilized for the extraction of key features, facilitating a comprehensive and integrated approach that significantly elevates both the data augmentation process and the model's ability to process and analyze complex human movements. The experimental outcomes underscore our model's exceptional performance in motion quality assessment, showcasing a substantial improvement over traditional methods in terms of classification accuracy and data processing efficiency. These results validate the effectiveness of our integrated network model, setting a solid foundation for future advancements in the field. Our research not only introduces innovative methodologies for 3D human pose data enhancement but also provides substantial technical support for practical applications across various domains, including sports science, rehabilitation medicine, and virtual reality. By combining advanced algorithmic strategies with robotic technologies, our work addresses key challenges in data augmentation and motion quality assessment, paving the way for new research and development opportunities in these critical areas.

Effect of urbanization and water quality on microplastic distribution in Conceição Lagoon watershed, Brazil

Urbanization in watersheds leads to the introduction of sources of microplastics and other pollutants in water bodies. However, the effect of urbanization on microplastic pollution and the relationship between microplastics and water quality are not well understood. We assessed the distribution of microplastics in tributaries urbanized, non-urbanized and in the receiving lagoon body of Conceição Lagoon watershed. The results show that urbanization significantly affects water quality but does not differentiate tributaries in terms of microplastic concentrations. Microplastic concentrations were lower in the receiving lagoon body compared with the tributaries, highlighting their importance in microplastic pollution in the studied lagoon. Microplastic concentration was correlated with low N:P ratios in the lagoon and associated with high levels of total phosphorus, which indicate the discharge of effluents. The correlations between microplastic concentration, water temperature, and dissolved oxygen in the lagoon were based on the temporal variations of these variables. Precipitation and wind velocity had influence on microplastic distribution in the watershed. Our findings underscore the importance of evaluating water quality parameters and meteorological variables to comprehend the microplastic distribution at small watersheds.

Effects of landscape pattern on water quality at multi-spatial scales in Wuding River Basin, China

Urbanization and agricultural land use have led to water quality deterioration. Studies have been conducted on the relationship between landscape patterns and river water quality; however, the Wuding River Basin (WDRB), which is a complex ecosystem structure, is facing resource problems in river basins. Thus, the multi-scale effects of landscape patterns on river water quality in the WDRB must be quantified. This study explored the spatial and seasonal effects of land use distribution on river water quality. Using the data of 22 samples and land use images from the WDRB for 2022, we quantitatively described the correlation between river water quality and land use at spatial and seasonal scales. Stepwise multiple linear regression (SMLR) and redundancy analyses (RDA) were used to quantitatively screen and compare the relationships between land use structure, landscape patterns, and water quality at different spatial scales. The results showed that the sub-watershed scale is the best spatial scale model that explains the relationship between land use and water quality. With the gradual narrowing of the spatial scale range, cultivated land, grassland, and construction land had strong water quality interpretation abilities. The influence of land use type on water quality parameter variables was more distinct in rainy season than in the dry season. Therefore, in the layout of watershed management, reasonably adjusting the proportion relationship of vegetation and artificial building land in the sub-basin scale and basin scope can realize the effective control of water quality optimization.

The multiscale nexus among land use-land cover changes and water quality in the Suquía River Basin, a semi-arid region of Argentina

Agricultural intensification and urban sprawl have led to significant alterations in riverscapes, and one of the critical consequences is the deterioration of water quality with significant implications for public health. Therefore, the objectives of this study were the assessment of the water quality of the Suquía River, the assessment of LULC change at different spatial scales, and the analysis of the potential seasonal correlation among LULC change and Water Quality Index (WQI). The Sample Sites (SS) 1 and 2 before Cordoba city had the highest WQI values while from SS3 the WQI decreased, with the lowest WQI close to the wastewater treatment plant (SS7) after Cordoba city. From SS8 in a agricultural context, the WQI increases but does not reach the original values. In light of analysis carried out, the correlation between water quality variables and the different LULC classes at the local and regional scales demonstrated that WQI is negatively affected by agricultural and urban activities, while natural classes impacted positively. The spatialization of the results can help strongly in assessing and managing the diffusion of point and non-point pollution along the riverscape. The knowledge gained from this research can play a crucial role in water resources management, which supports the provision of river ecosystem services essential for the well-being of local populations.

Assessment of water quality based on statistical analysis of physical-chemical, biomonitoring and land use data: Manso River supply reservoir

Preserving the quality of surface water has become increasingly difficult due to the intensification of human activities in watersheds. This study assessed the water quality of the Manso River reservoir, which supplies water to Brazil's third largest metropolitan region. The integration of >10,000 secondary data, comprising physico-chemical parameters, metals and microbiological indicators, together with biomonitoring and land use and occupation data, were analyzed by using statistical tools, the Water Quality Index (WQI) and the Trophic State Index (TSI). The results showed higher concentrations for solids and metals (Fe and Mn) characteristic of local geochemistry and also related to the mining activity in the region. Parameters associated with organic pollution, such as total phosphorus and Escherichia coli, were also elevated, probably due to contamination by untreated or insufficiently treated domestic sewage. The water at the tributary watercourses presented worse quality, predominantly medium WQI, compared with the stations inside the reservoir (predominantly good WQI). The TSI indicated a predominance of ultra-oligotrophic conditions for stations located in the lotic environment and mesotrophic conditions for those located in the lentic environment. In general, the same pattern was observed for the occurrence of the phytoplankton and zooplankton classes, indicating the relationship between the degree of trophy and the composition of these groups. In quantitative terms, for phytoplankton, the Euchlorophyceae and Cyanophyceae classes stood out, mainly in the rainy period (summer), whereas for zooplankton, the Crustacea and Monogonta classes were dominant. Regarding land use and occupation in the reservoir sub-basin, the positive impact of the surrounding forest cover was observed. It was also identified the effect of seasonality on the quality of aquatic environments. The integrated evaluation of the results proved to be efficient in assessing the environmental conditions of the reservoir and the tributaries, providing information for better management of these water resources.

Effect of urbanization and urban forests on water quality improvement in the Yangtze River Delta: A case study in Hangzhou, China

In the context of rapid global urbanization, the sustainable development of ecosystems should be considered. Accordingly, the Planetary Boundaries theory posits that reducing the amount of nitrogen and phosphorus pollutants entering bodies of water is necessary as excess levels may harm the aquatic environment and reduce in water quality. Thus, based on the long-term monitoring data of representative urban rivers in the Yangtze River Delta region, we evaluated the nitrogen and phosphorus pollution of water bodies in different urbanization stages and further quantified the effect of urban forests on water quality improvement. The results showed that, with the continuous progression of urbanization, the proportion of impervious surface area increased, along with the levels of nitrogen and phosphorus pollution in water bodies. The critical period of water quality deterioration in urban rivers occurred during the medium urbanization level when the proportion of impervious surface area reached 55-65 %, and the probability of an abrupt increase in total nitrogen (TN) and total phosphorus (TP) concentration exceeded 95 %. However, increasing the area of urban forests during this period reduced TN pollution by 36.64 % and TP pollution by 49.03 %. The results of this study support the expansion of urban forests during the medium urbanization stage to improve water quality. Furthermore, our results provide a reference and theoretical basis for urban forest construction as a key aspect of the sustainable development of the urban ecosystem in the Yangtze River Delta and similar regions around world.

Spatiotemporal patterns of multiple pesticide residues in central Argentina streams

Pollution of surface waters is a global threat, with particular concern about pesticides due to their severe negative effects on ecosystem functioning and human health. The aims of this study were to identify the spatiotemporal patterns of water and sediment quality, and the key variables related to the variation in pesticide pollution (122 compounds), in headwater streams (surrounding land uses: crop or mixed crop-livestock systems) and floodplain streams (surrounding land uses: urban development or natural wetland) of the Paraná River basin in the central area of Argentina. We found significant differences in water and sediment quality related to local land uses among headwater streams, but not among floodplain streams. These differences were more noticeable during spring than during autumn. Pesticides were widespread in all the streams, independently of the surrounding land use, reflecting the combination of local inputs and the role of floodplain hydrological connectivity in transporting pollutants from upstream sources. The most frequently detected compound was atrazine (75 %), whereas the highest concentration of an individual compound was observed for the glyphosate metabolite aminomethylphosphonic acid (AMPA, up to 4 μg L-1). The significant explanatory variables for pesticide pollution were turbidity, chromophoric dissolved organic matter (CDOM), sub-basin area, side slope of streams (positive relations), wetland cover, and precipitations (negative relations). Our results can be useful for the design of monitoring programs that capture the spatial and temporal variability of pesticide pollution.

Dynamics of the wetland ecosystem health in urban and rural settings in high altitude ecoregion

The focus of the present study was to assess the dynamics of wetland ecosystem health in both urban and rural settings situated in the high-altitude Kashmir Himalayan ecoregion. The basic aim was to identify the drivers responsible for wetland degradation in order to sustain ecosystem services effectively. To achieve this, we examined water quality, trophic status, fish species diversity and human disturbances by analyzing changes in land use and land cover (LULC) since 1980. For the limnological characterization of the two wetlands, we evaluated a total of 21 physico-chemical parameters at 24 sites. Two-way analysis of variance revealed significant (p < 0.05) spatial and temporal variability in the water quality parameters. The trophic state index values of 67.7 and 76.7 indicated that the rural and urban wetlands were in eutrophic and hypertrophic status, respectively, signifying potential environmental stress. The data on fish fauna indicated a decline in fish species over the past 40 years, particularly the schizothoracine species. Urban wetlands showed a more significant decrease in species (06) compared to rural wetlands (01). LULC mapping and change analysis employing the visual interpretation technique showed significant transformations in the immediate catchment of wetlands. Substantial growth in the built-up (433.2 % and 2620 %) and decrease in aquatic vegetation (-83.4 % and - 97.5 %) in the immediate catchment was recorded in both the urban and rural wetlands respectively from 1980 to 2020. Our findings demonstrated a relationship between LULC classes and water quality parameters, with an increase in built-up and road areas showing a significant positive correlation with the rise in decadal mean values of total phosphorus, orthophosphorus, nitrate nitrogen, ammonical nitrogen, and calcium content. Based on these observations, we concluded that changes in land use and land cover within the immediate catchment areas of the wetlands were the primary drivers responsible for the deterioration of wetland ecosystem health.

Multi-spatial-scale land/use land cover influences on seasonally dominant water quality along Middle Ganga Basin

Studying spatiotemporal water quality characteristics and their correlation with land use/land cover (LULC) patterns is essential for discerning the origins of various pollution sources and for informing strategic land use planning, which, in turn, requires a comprehensive analysis of spatiotemporal water quality data to comprehend how surface water quality evolves across different time and space dimensions. In this study, we compared catchment, riparian, and reach scale models to assess the effect of LULC on WQ. Using various multivariate techniques, a 14-year dataset of 20 WQ variables from 20 monitoring stations (67,200 observations) is studied along the Middle Ganga Basin (MGB). Based on the similarity and dissimilarity of WQPs, the K-means clustering algorithm classified the 20 monitoring stations into four clusters. Seasonally, the three PCs chosen explained 75.69% and 75% of the variance in the data. With PCs > 0.70, the variables EC, pH, Temp, TDS, NO2 + NO3, P-Tot, BOD, COD, and DO have been identified as dominant pollution sources. The applied RDA analysis revealed that LULC has a moderate to strong contribution to WQPs during the wet season but not during the dry season. Furthermore, dense vegetation is critical for keeping water clean, whereas agriculture, barren land, and built-up area degrade WQ. Besides that, the findings suggest that the relationship between WQPs and LULC differs at different scales. The stacked ensemble regression (SER) model is applied to understand the model's predictive power across different clusters and scales. Overall, the results indicate that the riparian scale is more predictive than the watershed and reach scales.

Response of streamflow and nutrient loads in a small temperate catchment subject to land use change

The aim of this study was to quantify the effect of land use change (LUC) implemented to meet nutrient load targets for a freshwater lake in New Zealand. We used the Soil and Water Assessment Tool (SWAT) model in combination with a non-parametric statistical test to determine whether afforestation of 15% of a subcatchment area was adequate to meet assigned nutrient load targets. A regional management authority set nutrient load targets of reduction in total nitrogen (TN) by 0.9 t yr-1 and reduction in total phosphorus (TP) by 0.05 t yr-1 to avoid eutrophication in the receiving waters of a freshwater lake. The load reduction was designed to be achieved through 200 ha of LUC from pasture to trees. Analysis of nutrient loads before, during, and following LUC shows that a 15% increase in forest cover decreased the annual flow (7.2%), TP load (33.3%), and TN load (13.1%). As flow and water quality observations were discrete and at irregular intervals, we used a parametric test and the SWAT model as different lines of evidence to demonstrate the effect of afforestation on flow and water quality. Policymakers concerned with decisions about LUC to improve the quality of receiving waters can benefit from applying our findings and using a statistical and numerical modelling framework to evaluate the adequacy of land use change to support improvements in water quality.

Micropollutants but high risks: Human multiple stressors increase risks of freshwater ecosystems at the megacity-scale

Micropollutants in water environments have attracted widespread attention, but how human and natural stressors influence the risks of micropollutants has not been comprehensively revealed. A megacity-scale study of the ecological risks of micropollutants in the surface water of Beijing, China is presented to illustrate the magnitudes of the influences of multiple anthropogenic and natural stressors. A total of 133 micropollutants representing typical land use patterns in Beijing, were quantified with the mean concentration range of ND (not detected) to 272 ng·L-1. The micropollutant concentrations in the south were obviously higher than those detected in the northern areas, and neonicotinoid pesticides showed the highest mean concentration of 311 ng·L-1. The chronic and acute risks of micropollutants to algae, invertebrates, and fishes were determined, and herbicides, organophosphorus esters, and insecticides account for the primary risks to algae, invertebrates, and fishes, respectively. The cropland and impervious cover cause the differences in the pollution and risks of micropollutants. The land use in riparian zones greater than 2 km shows a great influence on the chronic chemical risks (CCRs) for the three groups of species, indicating that too local scale does not explain the local pollution status. Climate conditions and human land use are important drivers explaining the CCRs to which various trophic levels of species are exposed. Results demonstrate that multiple categories of micropollutants pose adverse risks to freshwater in the megacity of Beijing, while climate conditions, pollution discharge, and human land use induce the chemical risk of micropollutants to aquatic organisms, and the land use in different riparian zones show different effects on the risks.

Linking above and belowground carbon sequestration, soil organic matter properties, and soil health in Brazilian Atlantic Forest restoration

Forest restoration mitigates climate change by removing CO2 and storing C in terrestrial ecosystems. However, incomplete information on C storage in restored tropical forests often fails to capture the ecosystem's holistic C dynamics. This study provides an integrated assessment of C storage in above to belowground subsystems, its consequences for greenhouse gas (GHG) fluxes, and the quantity, quality, and origin of soil organic matter (SOM) in restored Atlantic forests in Brazil. Relations between SOM properties and soil health indicators were also explored. We examined two restorations using tree planting ('active restoration'): an 8-year-old forest with green manure and native trees planted in two rounds, and a 15-year-old forest with native-planted trees in one round without green manure. Restorations were compared to reformed pasture and primary forest sites. We measured C storage in soil layers (0-10, 10-20, and 20-30 cm), litter, and plants. GHG emissions were assessed using CH4 and CO2 fluxes. SOM quantity was evaluated using C and N, quality using humification index (HLIFS), and origin using δ13C and δ15N. Nine soil health indicators were interrelated with SOM attributes. The primary forest presented the highest C stocks (107.7 Mg C ha-1), followed by 15- and 8-year-old restorations and pasture with 69.8, 55.5, and 41.8 Mg C ha-1, respectively. Soil C stocks from restorations and pasture were 20% lower than primary forest. However, 8- and 15-year-old restorations stored 12.3 and 28.3 Mg ha-1 more aboveground C than pasture. The younger forest had δ13C and δ15N values of 2.1 and 1.7‰, respectively, lower than the 15-year-old forest, indicating more C derived from C3 plants and biological N fixation. Both restorations and pasture had at least 34% higher HLIFS in deeper soil layers (10-30 cm) than primary forest, indicating a lack of labile SOM. Native and 15-year-old forests exhibited higher soil methane influx (141.1 and 61.9 μg m-2 h-1). Forests outperformed pasture in most soil health indicators, with 69% of their variance explained by SOM properties. However, SOM quantity and quality regeneration in both restorations approached the pristine forest state only in the top 10 cm layer, while deeper soil retained agricultural degradation legacies. In conclusion, active restoration of the Atlantic Forest is a superior approach compared to pasture reform for GHG mitigation. Nonetheless, the development of restoration techniques to facilitate labile C input into deeper soil layers (>10 cm) is needed to further improve soil multifunctionality and long-term C storage.

Identifying the influence of natural and human factors on seasonal water quality in China: current situation of China's water environment and policy impact

Agricultural production, urbanization, and other anthropogenic activities, the major causes of surface water pollution in China, have dramatically altered hydrological processes and nutrient cycles. Identifying and quantifying the key factors affecting water quality are essential for the better prevention and management of water pollution. However, due to the limitations of traditional statistical analysis methods, it is difficult to evaluate the spatial changes and interactions of influencing factors on water quality. In addition, research on a national scale is difficult, as it involves large-scale and long-term water quality monitoring work. In this study, we collected and collated the monthly average concentrations of four water quality parameters, dissolved oxygen, ammonia nitrogen, chemical oxygen demand, and total phosphorous, based on data from 1547 water quality monitoring stations in China. The combined pollution level of the water quality was assessed using the water quality index. Based on the water quality characteristics, water quality monitoring sites in the dry and wet seasons were grouped using k-means clustering. Eleven environmental factors were evaluated using geodetector software, including six human factors and five natural factors. The results showed that there are high-risk areas for water quality pollution in the eastern and southeastern coastal regions of China in both the dry and wet seasons and that surface water pollution in China is highly spatial heterogenous in both the dry and wet seasons. Among the anthropogenic factors, urban land area is the main factor of water quality pollution in the dry season, and the explanation rate of spatial heterogeneity of integrated water quality pollution index is 20.3%. The number of poultry farms and the area of farmland explained 12.4% and 12.1% of the integrated water quality pollution index in the wet season. The nonlinear relationship between these three anthropogenic and natural factors and their interaction exacerbated water quality pollution. Based on this analysis, we identified the key factors affecting surface water quality in China during the dry and wet seasons, evaluated the achievements of the water environmental protection policies in China in recent years, and proposed future management measures for the effective prevention and control of water quality pollution in high-risk areas.

The acute effects of fipronil and 2,4-D, individually and in mixture: a threat to the freshwater Calanoida copepod Notodiaptomus iheringi

The magnitude of copepods' responses to pesticides, individually and in mixture, is little understood. The aims of this study were to evaluate: (i) the effects of the pesticides fipronil and 2,4-D, individually and in mixture, on the freshwater copepod Notodiaptomus iheringi; and (ii) the survival and the feeding rate of copepods after the exposure. Acute toxicity tests using the commercial formulations of fipronil and 2,4-D, individually and in mixture, were performed. The LC10-48h, LC20-48h, and LC50-48h of fipronil to N. iheringi were 2.38 ± 0.48, 3.08 ± 1.14, and 4.97 ± 3.30 μg L-1, respectively. For 2,4-D the LC10-48h, LC20-48h, and LC50-48h were 371.18 ± 29.20, 406.93 ± 53.77, and 478.24 ± 107.77 mg L-1, respectively. Morphological damages on the copepods exposed to pesticides were observed at all concentrations. Fungal filaments covering dead organisms were presented at the treatment highest concentration (R5:7.43 ± 2.78 μg L-1 fipronil). The mixture of the pesticides presented synergistic effects on the mortality of N. iheringi. Post-exposure tests showed no difference between the treatments and the control on the mortality and on the feeding rate for 4 h. However, since delayed toxicity of pesticides can occur, longer post-exposure tests using N. iheringi should be tested. N. iheringi is a key species in the aquatic Brazilian ecosystem and showed sensitivity to fipronil and 2,4-D; thus, more studies with this species assessing other responses are recommended.

Exploration of the factors that influence total phosphorus in surface water and an evaluation of surface water vulnerability based on an advanced algorithm and traditional index method

Due to the continuous influence of human activities, phosphorus pollution in surface water has become a persistent problem that needs to be addressed since phosphorous entails certain risks and degrees of damage to ecosystems and humans. The presence and accumulation of total phosphorus (TP) concentrations in surface waters is the result of a combined effect of many natural and anthropogenic factors, and it is often difficult to intuitively identify the individual importance of each factor in regard to the pollution of the aquatic environment. Considering these issues, this study provides a new methodology to better understand the vulnerability of surface water to TP pollution and the factors that influence TP pollution through the application of two modeling approaches. This includes the boosted regression tree (BRT), an advanced machine learning method, and the traditional comprehensive index method (CIM). Different factors, such as natural variables (including slope, soil texture, normalized difference vegetation index (NDVI), precipitation, and drainage density) and point and nonpoint source anthropogenic factors were included to model the vulnerability of surface water to TP pollution. Two methods were used to produce a vulnerability map of surface water to TP pollution. Pearson correlation analysis was used to validate the two vulnerability assessment methods. The results showed that BRT was more strongly correlated than CIM. In addition, the importance ranking results showed that slope, precipitation, NDVI, decentralized livestock farming and soil texture had a greater influence on TP pollution. Industrial activities, scale livestock farming and population density, which are all contributing sources of pollution, were all relatively less important. The introduced methodology can be used to quickly identify the area most vulnerable to TP pollution and to develop problem specific adaptive policies and measures to reduce the damage from TP pollution.

Effects of rainfall and land use on nutrient responses in rivers in the Brazilian semiarid region

This paper investigated whether rainfall promotes dilution or increase in nutrient concentrations and which land use indicators are the main predictors of nutrients in intermittent rivers in a large Brazilian semiarid region. The total phosphorus (TP) and total inorganic nitrogen (TIN) were monitored between 2013 and 2018 at 92 river water quality monitoring sites. The monthly rainfall (Rn) was obtained from 575 rain gauges. Pearson's correlation (R) between Rn and nutrient concentration was performed. The correlation patterns were also analysed based on land use data: urban area (%), agricultural field area (%), demographic density (inhabitants/km2), sewer system coverage (%), and reservoir density (reservoir/km2). Backward stepwise regression was performed to identify predictors of nutrient concentrations. The results revealed a marginal effect of rainfall on nutrients when the effects of urbanisation outweigh all other aspects. However, in regions with greater accumulated rainfall and lower reservoir density, the rainfall was related to a linear increase in nutrient concentrations (R > 0.8). Contrastingly, in the basins with less accumulated rainfall and greater inter-basin hydrological disconnection, there was a linear reduction in nutrient concentration (R < - 0.5). In the backward stepwise regression, sewer system coverage and Rn had the greatest influence for TP, and the urban area was the strongest predictor for TIN. Importantly, our results demonstrated that in semiarid rivers in densely populated regions, there is no single pattern of variability in nutrient concentration, on a wide scale of assessment. Therefore, adaptative and decentralised management can be more effective in improving water quality in these regions.

Land use as a critical determinant of faecal and antimicrobial resistance gene pollution in riverine systems

The WHO recognises antimicrobial resistance (AMR) as a global health threat. The environment can act as a reservoir, facilitating the exchange and the physical movement of resistance. Aquatic environments are at particular risk of pollution, with large rivers subject to pollution from nearby human, industrial or agricultural activities. The land uses associated with these activities can influence the type of pollution. One type of pollution and a likely contributor to AMR pollution that lowers water quality is faecal pollution. Both pose an acute health risk and could have implications for resistance circulating in communities. The effects of land use are typically studied using physiochemical parameters or in isolation of one another. However, this study aimed to investigate the impact of different land uses on riverine systems. We explored whether differences in sources of faecal contamination are reflected in AMR gene concentrations across agricultural and urban areas. Water quality from three rivers impacted by different land uses was assessed over one year by quantifying faecal indicator bacteria (FIB), microbial source tracking markers (MST) and AMR genes. In addition, a multiparametric analysis of AMR gene pollution was carried out to understand whether agricultural and urban areas are similarly impacted. Faecal indicators varied greatly, with the highest levels of FIB and the human MST marker observed in urban regions. In addition, these faecal markers correlated with AMR genes. Similarly, significant correlations between the ruminant MST marker and AMR gene levels in agriculture areas were observed. Overall, applying multiparametric analyses to include AMR gene levels, separation and clustering of sites were seen based on land use characterisation. This study suggests that differences in prescription of antimicrobials used in animal and human healthcare may influence environmental resistomes across agricultural and urban areas. In addition, public health risks due to exposure to faecal contamination and AMR genes are highlighted.

Toxicity of fipronil and 2,4-D pesticides in Daphnia similis: a multiple endpoint approach

In Brazil, among the pesticides widely applied simultaneously in sugarcane monocultures are the Regent® 800 WG insecticide (active ingredient (a.i.) fipronil) and the DMA® 806 BR herbicide (a.i. 2,4-D). Thus, this study aimed to investigate, through different endpoints, the effects of the fipronil and 2,4-D pesticides, isolated and as mixtures, on the cladoceran Daphnia similis. To do this, acute toxicity tests were carried out with the compounds acting in isolation and in mixture, where the survival of the organisms was evaluated, and chronic toxicity tests with the isolated compounds, where reproduction and maternal and neonatal body length were evaluated. In this study, the physiological endpoints of D. similis were also analyzed, through the analysis of feeding rates (filtration and ingestion) in exposure and post-exposure scenarios, in order to verify the cladoceran food recovery capacity. In addition, D. similis data were compared with other species when exposed to the studied pesticides, using species sensitivity distribution curves. Acute toxicity tests of the fipronil and 2,4-D showed an average EC₅₀-48 h of 66.68 μg a.i./L and 327.07 mg a.i./L, respectively. In both cases, D. similis showed lower sensitivity compared to other species. For the mixture test, the evaluation by the IA model (independent action) and deviation DR (dose ratio dependent) indicated the occurrence of mostly antagonistic effects. The chronic test with fipronil showed a decrease in the fecundity of the organism at a concentration of 16 μg a.i./L, a concentration already found in aquatic environments. For 2,4-D, no significant differences were observed for reproduction at the concentrations tested. Regarding the maternal body length, there were no significant changes when D. similis were exposed to both fipronil and 2,4-D, but these differences were observed in the body length of the neonates only for 2,4-D. There were no significant changes in the feeding rates of the organisms when exposed to both pesticides.

Effect of three commercial algaecides on cyanobacteria and microcystin-LR: implications for drinking water treatment using activated carbon

Toxic cyanobacterial blooms in aquatic ecosystems are associated to both public health and environmental concerns worldwide. Depending on the treatment technologies used, the removal capacity of cyanotoxins by drinking water treatment plants (DWTPs) is not sufficient to reach safe levels in drinking water. Likewise, controlling these blooms with algaecide may impair the efficiency of DWTPs due to the possible lysis of cyanobacterial cells and consequent release of cyanotoxins. We investigated the effects of three commercial algaecides (cationic polymer, copper sulfate, and hydrogen peroxide) on the growth parameters of the cyanobacterium Microcystis aeruginosa and the release of microcystin-LR (MC-LR). The potential interference of each algaecide on the MC-LR removal by adsorption on activated carbon (AC) was also tested through adsorption isotherms and kinetics experiments. Most algaecides significantly decreased the cell density and biovolume of M. aeruginosa, as well as increased the release of MC-LR. Interestingly, the presence of the algaecides in binary mixtures with MC-LR affected the adsorption of the cyanotoxin. Relevant adsorption parameters (e.g., maximum adsorption capacity, adsorption intensity, and affinity between MC-LR and AC) were altered when the algaecides were present, especially in the case of the cationic polymer. Also, the algaecides influenced the kinetics (e.g., by shifting the initial adsorption and the desorption constant), which may directly affect the design and operation of DWTPs. Our study indicated that algaecides can significantly impact the fate and the removal of MC-LR in DWTPs when the adsorption process is employed, with important implications for the management and performance of such facilities.

Fish biomarker responses reflect landscape anthropic disturbance in savanna streams

Disturbance in the landscape surrounding streams can interfere with water quality and cause harm to aquatic organisms. In this study, we evaluate the influence of land use on the genetic and biochemical biomarkers of fish in streams of Brazilian savanna (Cerrado). We also evaluated whether biomarker responses are seasonally consistent. For this purpose, individuals of the Neotropical tetra fish Astyanax lacustris were exposed in cages for 96 h, in 13 streams draining agroecosystems with different degrees of disturbance during the dry and wet seasons. After exposure, blood, liver, and gills were collected for multibiomarker analyses (micronuclei, erythrocytic nuclear abnormalities, lipid peroxidation, antioxidant enzymes, and biotransformation enzyme). The results showed that the gradient of anthropic disturbance was positively associated with genotoxic damage (erythrocytic nuclear abnormalities) and negatively associated with antioxidant and biotransformation enzymes of the liver in both seasons. No association of the gradient of anthropic disturbance with the frequency of micronuclei and for most gill enzymes was found for both seasons. Landscape disturbance was also negatively associated with water quality in the wet season. These results indicate that changes in land use interfere with the genetic and biochemical processes of organisms. Thus, the multibiomarker approach may represent an effective strategy for assessing and monitoring terrestrial landscape disturbance.

Multiscale spatial analysis of headwater vulnerability in South-Central Chile reveals a high threat due to deforestation and climate change

Headwaters represent an essential component of hydrological, ecological, and socioeconomical systems, by providing constant water streams to the complete basin. However, despite the high importance of headwaters, there is a lack of vulnerability assessments worldwide. Identifying headwaters and their vulnerability in a spatially explicit manner can enable restauration and conservation programs. In this study, we assess the vulnerability of headwaters in South-Central Chile (38.4 to 43.2°S) considering multiple degradation factors related to climate change and land cover change. We analyzed 2292 headwaters, characterizing multiple factors at five spatial scales by using remote sensing data related to Land Use and Cover Change (LUCC), human disturbances, vegetation cover, climate change, potential water demand, and physiography. We then generated an index of vulnerability by integrating all the analyzed variables, which allowed us to map the spatial distribution of headwater vulnerability. Finally, to estimate the main drivers of degradation, we performed a Principal Components Analysis with an Agglomerative Hierarchical Clustering, that allowed us to group headwaters according to the analyzed factors. The largest proportion of most vulnerable headwaters are located in the north of our study area with 48.1 %, 62.1 %, and 28.1 % of headwaters classified as highly vulnerable at 0, 10, and 30 m scale, respectively. The largest proportion of headwaters are affected by Climate Change (63.66 %) and LUCC (23.02 %) on average across all scales. However, we identified three clusters, in which the northern cluster is mainly affected by LUCC, while the Andean and Coastal clusters are mainly affected by climate change. Our results and methods present an informative picture of the current state of headwater vulnerability, identifying spatial patterns and drivers at multiple scales. We believe that the approach developed in this study could be useful for new studies in other zones of the world and can also promote Chilean headwater conservation.

Multi-spatial scale effects of multidimensional landscape pattern on stream water nitrogen pollution in a subtropical agricultural watershed

Multidimensional (coupled land use, soil properties, and topography) landscape effects on stream water nitrogen (N) are complex and scale-dependent. However, studies that identify critical buffer zones that explain large variations in riverine N, and estimate specific thresholds of multidimensional landscape patterns at the class level, result in a sudden changes in riverine N pollution, are still limited. Here, a new multidimensional landscape metric that combined land use, soil properties, and topography effects was applied to various riparian buffer zones and sub-watershed scales, and their relationships to riverine N levels were investigated. We used stream water ammonium-N, nitrate-N, and total-N concentrations datasets, from 2010 to 2017, in the nine subtropical sub-watersheds in China. The results of model selection and model averaging in ordinary least squares regressions, indicated that the riparian buffer zone with widths of 400 m, had more pronounced influence on water NH₄-N and TN levels than at other scales. Within the 400 m buffer zone, the key landscape metrics for NH₄-N, NO₃-N and TN concentrations in stream water were different, and explained up to 43.35%-76.55% (adjusted R²) of the total variation in river N levels. When ENN_MN_Class17 below 39-56 m, PD_Class8 above 4.63-6.55 n/km², PLAND_Class27 above 23-29%, and CONTIG_MN_Class42 below 0.35-0.37% within the 400 m buffer zone, riverine NH₄-N and TN would be abruptly increased. This study provided practical ideas for regulation regarding landscape management linked to watershed structure, and identified reference thresholds for multidimensional landscape metrics, which should help reduce riverine N pollution in subtropical China.

Methane concentrations and fluxes in agricultural and preserved tropical headwater streams

Tropical streams have been intensively impacted by agricultural activities. Among the most important agricultural activities in Brazil, sugarcane production represents a large impact for economic development and for environmental conditions. Permeating sugarcane fields, several headwater streams can be affected by sugarcane cultivation, in special, aquatic biogeochemical cycles because of the deforestation, fertilization, crop residues and higher temperatures in the tropics. In this study, we analyzed the effects of sugarcane cultivation on methane fluxes and concentrations, assuming that carbon cycles are influenced by agricultural activities in headwater streams. Our study aimed to (1) measure methane fluxes and concentrations in tropical streams located in Southeastern Brazil, (2) Analyze whether seasonal cycles influence methane fluxes and concentrations, (3) Evaluate the influence of sugarcane cultivation on methane fluxes and (4) Analyze the association between water chemistry in the methane concentrations in tropical streams. We found mean fluxes of CH₄ of 0.280 mmol m^-2 d^-1, with higher fluxes during the summer and in streams draining preserved catchments. The average CH₄ concentrations were 0.695 μmol L^-1, with higher values during the summer and in streams draining preserved catchments. Methane concentrations in the studied streams was influenced by dissolved oxygen (negatively), dissolved organic carbon (negatively), water velocity (positively) and conductivity (negatively). Methane concentrations were significantly higher than concentrations found in Temperate Grasslands, Savannas & Shrublands and similar to concentrations found in other tropical biomes (excluding Tropical & Subtropical Moist Broadleaf Forests which receives large amounts of organic inputs). We conclude that sugarcane influence methane concentrations and fluxes in tropical streams by reducing the organic matter availability provided by the native vegetation in soil and water.

Does land use and land cover affect adult communities of Ephemeroptera, Plecoptera and Trichoptera (EPT)? A systematic review with meta-analysis

We conducted a systematic review to better understand this gap and analyzed i) in which global regions are studies usually conducted, ii) the taxon studied, iii) sampling methods and iv) how authors collaborated in these studies. We also tested the relationship between different types of land use and land cover and adult EPT communities using a meta-analysis. We searched for relevant articles on the website Web of Science, using specific words related to the subject. We found 454 papers and selected 31 of them for the scientometric analysis, as they were in accordance with our objectives, and eight for the meta-analysis. Among this subset, we observed that study areas and collaborations among authors were largely restricted to a few countries in Europe and North America. Most studies used the group Trichoptera, probably due to its diversity and the longevity of the adults compared to other groups. Light traps were the most common sampling method, most likely due to their efficiency in capturing flying insects with nocturnal habits. The greatest differences in adult EPT communities were found between open areas (moorland and prairie) and forest areas. This result indicated that the conversion of forest habitats into open areas negatively impacts adult EPT communities. Our systematic review can be an important tool to help researchers choose appropriate collection methods and taxonomic groups to work with in studies on impacts of land use change on adult EPT communities.

Linking land-use and land-cover transitions to their ecological impact in the Amazon

Human activities pose a major threat to tropical forest biodiversity and ecosystem services. Although the impacts of deforestation are well studied, multiple land-use and land-cover transitions (LULCTs) occur in tropical landscapes, and we do not know how LULCTs differ in their rates or impacts on key ecosystem components. Here, we quantified the impacts of 18 LULCTs on three ecosystem components (biodiversity, carbon, and soil), based on 18 variables collected from 310 sites in the Brazilian Amazon. Across all LULCTs, biodiversity was the most affected ecosystem component, followed by carbon stocks, but the magnitude of change differed widely among LULCTs and individual variables. Forest clearance for pasture was the most prevalent and high-impact transition, but we also identified other LULCTs with high impact but lower prevalence (e.g., forest to agriculture). Our study demonstrates the importance of considering multiple ecosystem components and LULCTs to understand the consequences of human activities in tropical landscapes.

Spatiotemporal Variability of Human Disturbance Impacts on Ecosystem Services in Mining Areas

Human activities pose significant impacts on ecosystem services (ESs) in mining areas, which will continually increase over time and space. However, the mechanism of ES change on spatiotemporal scales post-disturbance remains unclear, especially in the context of global climate change. Here, we conducted a global literature review on the impact of two of the most frequent disturbance factors (mining and restoration) on 27 different ESs, intending to synthesize the impacts of human disturbance on ESs in mining areas via a meta-analysis, and analyze the spatiotemporal variability of ESs after disturbance. We screened 3204 disturbance studies published on the Web of Science between 1950 and 2020 and reviewed 340 in detail. The results of independence test showed that human disturbance had a significant impact on ESs in the mining areas (p < 0.001). The impacts (positive and/or negative) caused by mining and restoration differed considerably among ESs (even on the same ESs). Additionally, spatiotemporal scales of human disturbance were significantly related to spatiotemporal scales of ES change (p < 0.001). We found that the positive and negative impacts of disturbances on ESs may be interconversion under specific spatiotemporal conditions. This seems to be associated with spatiotemporal variability, such as the temporal lag, spatial spillover, and cumulative spatiotemporal effects. Climate changes can lead to further spatiotemporal variability, which highlights the importance of understanding the changes in ESs post-disturbance on spatiotemporal scales. Our research presents recommendations for coping with the twofold pressure of climate change and spatiotemporal variability, to understand how ESs respond to human disturbance at spatiotemporal scales in the future, and manage disturbances to promote sustainable development in mining areas.

Land Use Dynamic Changes in an Arid Inland River Basin Based on Multi-Scenario Simulation

The Tarim River Basin is the largest inland river basin in China. It is located in an extremely arid region, where agriculture and animal husbandry are the main development industries. The recent rapid rise in population and land demand has intensified the competition for urban land use, making the water body ecosystem increasingly fragile. In light of these issues, it is important to comprehensively grasp regional land structure changes, improve the degree of land use, and reasonably allocate water resources to achieve the sustainable development of both the social economy and the ecological environment. This study uses the CA-Markov model, the PLUS model and the gray prediction model to simulate and validate land use/cover change (LUCC) in the Tarim River Basin, based on remote sensing data. The aim of this research is to discern the dynamic LUCC patterns and predict the evolution of future spatial and temporal patterns of land use. The study results show that grassland and barren land are currently the main land types in the Tarim River Basin. Furthermore, the significant expansion of cropland area and reduction in barren land area are the main characteristics of the changes during the study period (1992–2020), when about 1.60% of grassland and 1.36% of barren land converted to cropland. Over the next 10 years, we anticipate that land-use types in the basin will be dominated by changes in grassland and barren land, with an increasing trend in land area other than for cropland and barren land. Grassland will add 31,241.96 km2, mainly in the Dina River and the lower parts of the Weigan-Kuqu, Kashgar, Kriya, and Qarqan rivers, while barren land will decline 2.77%, with significant decreases in the middle and lower reaches of the Tarim River Basin. The findings of this study will provide a solid scientific basis for future land resource planning.

Environmental Fragility Zoning Using GIS and AHP Modeling: Perspectives for the Conservation of Natural Ecosystems in Brazil

The degradation of natural ecosystems triggers global environmental, economic, and social problems. To prevent this, it is necessary to identify the aptitude of priority areas for conservation or use by considering land fragility from multiple environmental and spatial perspectives. We applied the concept of environmental fragility to a hydrographic basin in southeastern Brazil that establishes (i) potential fragility levels according to slope, soil classes, geological domains, drainage hierarchy, and rainfall information using an algebraic map, and (ii) emerging fragility levels via the addition of the land-use parameters. The methodological approach involved the integration of the analytic hierarchy process (AHP) and weighted linear combination (WLC) into a geographic information system (GIS). The medium and slightly low fragility classes predominated in terms of potential (~60%), and emerging (~70%) environmental fragility models used to model the basin. The model indicated that high and extremely high potential fragilities were concentrated in the upper basin, a region that is considered a global biodiversity hotspot. The areas with high/extremely high classes of emerging fragility in the upper basin decreased, indicating that the natural cover classes and land-use types are not in danger. We also introduce acceptable conservation practices for land management and use according to the environmental fragility categories established in the present work. The methodology applied in this study can be replicated in other global ecoregions. It provides low-cost territorial and environmental zoning and flexible replication and can be adjusted by administrators who are interested in land-use planning.

Landscape composition and inorganic contaminants in water and muscle tissue of Plagioscion squamosissimus in the Araguari River (Amazon, Brazil)

Amazonian aquatic environments are seriously impacted by dam-building and deforestation, among other threats. Therefore, the present study aimed to examine water quality in the middle and lower course of the Araguari River with respect to the composition of vegetative cover and the concentration of As, Cd and Hg in order to determine risks to the preservation of biota and risks to human health from consumption of P. squamosissimus contaminated with these inorganic elements. To accomplish this, water samples and fish specimens were collected in the middle and lower Araguari River in 2019. The concentration of inorganic contaminants was analyzed by atomic absorption spectrophotometry. These stretches of the Araguari River presented higher proportions of forest fragments and evident expansion of buffalo pastures. According to Brazilian legislation, the concentrations of Cd and Hg in the water samples represented risk quotient values > 1, indicating risk to the preservation of aquatic biota. In particular, the concentrations of Cd in the muscle tissue of P. squamosissimus in the lower Araguari River also indicated risks to human health. The bioaccumulation factor indicated that Hg is bioavailable in the water. It can be concluded that water imbalances in the middle and lower Araguari River compromise the health of both aquatic and human life.

Inner Dynamic Detection and Prediction of Water Quality Based on CEEMDAN and GA-SVM Models

Urban water quality is facing strongly adverse degradation in rapidly developing areas. However, there exists a huge challenge to estimating the inner features and predicting the variation of long-term water quality due to the lack of related monitoring data and the complexity of urban water systems. Fortunately, multi-remote sensing data, such as nighttime light and evapotranspiration (ET), provide scientific data support and reasonably reveal the variation mechanisms. Here, we develop an integrated decomposition-reclassification-prediction method for water quality by integrating the CEEMDN method, the RF method mothed, and the genetic algorithm-support vector machine model (GA-SVM). The degression of the long-term water quality was decomposed and reclassified into three different frequency terms, i.e., high-frequency, low-frequency, and trend terms, to reveal the inner mechanism and dynamics in the CEEMDAN method. The RF method was then used to identify the teleconnection and the significance of the selected driving factors. More importantly, the GA-SVM model was designed with two types of model schemes, which were the data-driven model (GA-SVMd) and the integrated CEEMDAN-GA-SVM model (defined as GA-SVMc model), in order to predict urban water quality. Results revealed that the high-frequency terms for NH3-N and TN had a major contribution to the water quality and were mainly dominated by hydrometeorological factors such as ET, rainfall, and the dynamics of the lake water table. The trend terms revealed that the water quality continuously deteriorated during the study period; the terms were mainly regulated by the land use and land cover (LULC), land metrics, population, and yearly rainfall. The predicting results confirmed that the integrated GA-SVMc model had better performance than single data-driven models (such as the GA-SVM model). Our study supports that the integrated method reveals variation rules in water quality and provides early warning and guidance for reducing the water pollutant concentration.

Urban Land-Use Type Influences Summertime Water Quality in Small- and Medium-Sized Urban Rivers: A Case Study in Shanghai, China

(1) Background: Small- and medium-sized rivers in urban areas are unique environments that serve as blue-green corridors for urban residents. The relationship between land-use types and water quality in these rivers provides important information for effectively addressing urban river restoration and pollution management. However, not much attention has been paid on these small- and medium-sized rivers, especially in large urban agglomerations with dense river networks. (2) Methods: This study undertook a field investigation on 130 sampling small- and medium-sized rivers during the late summer and applied data-driven water quality index and landscape analysis techniques to evaluate the direct impacts of riparian land-use types on the summertime water quality in Shanghai’s small- and medium-sized rivers. Riparian land-use types were derived from OpenStreetMap (OSM) datasets, including industrial, commercial, residential, and green spaces. (3) Results: Residential and green space are located closer to these sampled rivers than industrial and commercial land types, suggesting a tentative link between anthropogenic activities and water quality. Further analysis concluded that urban resident settlements, characterized by specific land-use types, DMSP-OLS nighttime lights, OSM road density, and OSM river density, strongly affected the water quality at the sub-catchment scale. We further determined the critical radii for impacts of land use types on urban rivers. Industrial types may influence water quality within a maximum radius of 5 km, followed by green space (4 km), residential areas (3 km), and commercial developments (2 km). These mathematically and statistically computed radii provide updated visions for river health assessment. For a specific land-use type, the assessed water quality index will be biased by using an assessment area with a radius higher or lower than the above-estimated radii. The study also quantified the spatial extent and transmission efficiency of non-point source pollution in a super built-up area of central Shanghai. We observed that contaminants transported by river pathways can reach a larger area than those transported by roads. (4) Conclusions: The high-quality environments in small- and medium-sized rivers are tightly linked to riparian landscape patterns. It is therefore urgent to control domestic pollutions as part of the restoration of megacity’s urban rivers and grapple with the complex challenges of risks to water supply. This study elaborates the importance of integrating land-use planning and water-quality management to maintain the functions and services of small- and medium-sized urban rivers.

Manganese Pollution in Mining-Influenced Rivers and Lakes: Current State and Forecast under Climate Change in the Russian Arctic

Mining regions in different parts of the world have been associated with the significant pollution of water, sediments, and soils by manganese and other chemical elements. This study assessed the degree of geochemical transformation caused by open-pit extraction and processing of mineral resources in the Kovdorsky District of Murmansk Oblast, 20 km from the Russia–Finland border. A second objective was to predict further changes co-driven by industrial pressure and high climatic instability in the polar region. The field study involved sampling water and sediments from virgin background streams and from the tailings storage facility, settling ponds, rivers, and lakes affected by ore mining and disintegration. Laboratory analyses included the study of elemental composition, redox potential, alkalinity and acidity, organic matter content, and other geochemical characteristics for a better understanding of pollutant migration patterns. We revealed elevated levels of potentially toxic elements in surface waters and bottom sediments which pose a risk to the human health via the household and drinking water supply. Pollution with manganese (Mn) was found to be the major environmental issue. Its natural presence in the river water was overridden a hundredfold by anthropogenic enrichment. This is problematic as Mn is easily bioaccumulated, which can lead to unwanted ecotoxicological effects, and—in the case of prolonged exposure to high doses of Mn and its compounds—to detrimental human health impacts. We believe that the changing climate may raise the water flow and thus expand the area of the hydrochemical anomaly. On the other hand, the activation of self-purification and dilution processes could lead to decreasing environmental Mn concentrations.

Evaluating the Impact of Ecological Property Rights to Trigger Farmers’ Investment Behavior—An Example of Confluence Area of Heihe Reservoir, Shaanxi, China

Property rights of natural resources have been acting as a critical legislative tool for promoting sustainable resource utilization and conservation in various regions of the globe. However, incorporating ecological property rights into the natural resources property rights structure may significantly influence farmers’ behavior in forestry investment. It may also trigger forest protection, water conservation, and urban water security. The main aim of the research is to evaluate the impact of ecological property rights and farmers’ investment behavior in the economic forest. We have constructed an analytical framework of collective forest rights from two indicators of integrity and stability, by adopting the theory of property rights and ecological capital to fulfill the study’s aims. The empirical data has been comprised of the microdata of 708 farmers, collected from the confluence area of the Heihe Reservoir, Shaanxi, China. The study also conducted pilot ecological property rights transactions in the surveyed area. The study utilized the double-hurdle model to test the proposed framework empirically. The results show that forest land use rights, economic products, and eco-product income rights positively affect farmers’ forestry investment intensity, and disposal rights (forest land transfer rights) negatively affect farmers’ investment intensity. However, in terms of the integrity of property rights, only the right to profit from ecological products affects farmers’ forestry investment willingness, and other property rights are insignificant. The study also found that the lower the farmers’ forest land expropriation risk is expected, the greater the possibility of investment and the higher the input level. However, we traced that the farmers’ forest land adjustment has no significant impact on farmers’ willingness to invest. Obtaining the benefits of ecological products has been found as the primary motivation for forestry investment within the surveyed area. The completeness of ownership rights positively impacted farmers’ investment intensity. Farmers should realize the ecological value of water conservation forests through the market orientation of the benefit of ecological products. Therefore, the government should encourage farmers and arrange proper training to facilitate a smooth investment. A well-established afforestation program should also be carried out.

Effects of forest cover pattern on water quality of low-order streams in an agricultural landscape in the Pirapora river basin, Brazil

Low-order streams are important places for river formation and are highly vulnerable to changes in terrestrial ecosystems. Thus, the land-use/land-cover plays an important role in the maintenance of water quality. However, only land-use/land-cover composition may not explain the spatial variation in water quality, because it does not consider land-use/land-cover configuration and forest cover pattern. In this context, the study aimed to evaluate the forest cover pattern effects on water quality on low-order streams located in an agricultural landscape. Applying a paired watershed method, we selected two watersheds classified according to their morphometry and average slope to discard other physical factors that could influence the water quality. Land-use/land-cover pattern was analyzed for composition and forest cover configuration using landscape metrics, including the riparian zone composition. Water quality variables were obtained every two weeks during the hydrological year. This way, watersheds had similar morphometry, slope, and land-use/land-cover composition but differed in forest cover pattern. Watershed with more aggregated forest cover had a better water quality than the other one. The results show that forest cover contributes to water quality maintenance, while forest fragmentation influences the water quality negatively, especially in sediment retention. Agricultural practices are sources of sediment and nutrients to the river, especially in steep relief. Thus, in addition to land-use/land-cover composition, forest cover pattern must be considered in management of low-order streams in tropical agricultural watersheds.

High concentrations of metals in the waters from Araguari River lower section (Amazon biome): Relationship with land use and cover, ecotoxicological effects and risks to aquatic biota

The Araguari River is one of the most important water body in the Brazilian state of Amapá. However, the quality of its waters has been deteriorating and, recently, high concentrations of metals were found in water samples collected from its lower section. Overall, we aimed to evaluate land use and cover around three sampling sites located in the Araguari River lower section and its contribution to water pollution by metals; correlate land use pattern with detected metal concentrations; assess acute toxicity using the Daphnia similis test and genotoxicity using the Danio rerio bioassay of water samples from the three sampling sites; and investigate the risks arising from metals present in waters to aquatic biota. Riparian forest around all sampling sites is fragmented owing to the expansion of pasture areas, which showed a significant positive correlation (p < 0.05) with the concentrations of Hg and Cu in water samples. Water samples from sampling sites 2 and 3 presented acute toxicity for D. similis, and the D. rerio bioassay confirmed the presence of genotoxic pollutants in the waters from all sampling sites. Our preliminary risk assessment showed that individual concentrations and the mixture of metals posed a high risk to aquatic biota. Taken together, our results demonstrate that the conversion of native forest to pastureland contributes to water contamination by metals, which contributes to the risks to aquatic biota.

The impact of land resource mismatch and land marketization on pollution emissions of industrial enterprises in China

Local governments' strategy of increasing the land supply by selling industrial land at low prices causes industrial land in China to be priced substantially below the market value. Whether under planned or market allocation, urban land is an important part of China's market-oriented economic reform. However, direct empirical research on the impact of industrial land transfer on environmental pollution is still lacking. Based on matched data, this study investigates the impact of land resource mismatch and land marketization on the pollution emissions of Chinese enterprises. Pollution emissions refer to the emission intensity of industrial enterprises' major pollutants, such as industrial water, industrial waste gas and sulfur dioxide, and it is calculated by the comprehensive index method. The impact of land resource mismatch and land marketization on the pollution emissions of Chinese enterprises is investigated using a panel fixed effect model, subsample regression, the instrumental variable method and a mediating effect model. The benchmark analysis shows that land resource mismatch increases pollution emissions. The influence mechanism analysis shows that land resource mismatch may increase the pollution emissions of enterprises by causing overinvestment and low productivity. In addition, the expanded analysis shows that China's land marketization can reduce the intensity of and have a long-term impact on the pollution emissions of enterprises. This paper provides a theoretical and scientific basis for correcting the mismatch of land resources and promoting the reform of land marketization in China.

Understanding the spatiotemporal pollution dynamics of highly fragile montane watersheds of Kashmir Himalaya, India

Pollution of riverine ecosystems through the multidimensional impact of human footprints around the world poses a serious challenge. Research studies that communicate potential repercussions of landscape structure metrics on snowmelt riverine water quality particularly, in climatically fragile Himalayan watersheds are very scarce. Though, worldwide, grasping the influence of land-use practices on water quality (WQ) has received renewed attention yet, the relevance of spatial scale linked to landscape pattern is still elusive due to its heterogenic nature across diverse geomorphic regions. In this work, therefore, we tried to capture the insights on landscape-aquascape interface by juxtapositioning the impacts of landscape structure pattern on snowmelt stream WQ of the whole Jhelum River Basin (JRB) under three varying spatial scales viz., watershed scale, riparian corridor (1000 m wide) and reach buffer (500 m wide). The percentage of landscape pattern composition and configuration metrics in the JRB were computed in GIS utilizing Landsat-8 OLI/TIRS satellite image having 30 m resolution. To better explicate the influence of land-use metrics on riverine WQ with space and time, we used Redundancy analysis (RDA) and multilinear regression (MLR) modeling. MLR selected land-use structure metrics revealed the varied response of WQ parameters to multi-scale factors except for total faecal coliform bacteria (TC) which showed perpetual presence. The reach-scale explained slightly better (76%) variations in WQ than riparian (75%) and watershed (70%) scales. Likewise, across seasonal scale, autumn (75%), winter (83%), and summer (77%) captured the most WQ variation at catchment, riparian, and reach scales respectively. We observed impairing WQ linkages with agriculture, built-up and barren rocky areas across watersheds, besides, pastures in riparian buffer areas, and fragmentation of landscape patches at the reach scale. Due to little appearance of spatial scale differences, a multi scale perspective landscape planning is emphasized to ensure future sustainability of Kashmir Himalayan water resources.

Native forest cover safeguards stream water quality under a changing climate

Ensuring a sufficient and adequate supply of water for humans and ecosystems is a pressing environmental challenge. The expansion of agricultural and urban lands has jeopardized watershed ecosystem services and a changing climate poses additional risks for regional water supply. We used stream water quality data collected between 2000 and 2014, coupled with detailed precipitation and land cover information, to investigate the effects of landscape composition and short-term precipitation variability on the quality of water resources in the state of São Paulo, Brazil. The state is home to over 45 million people and has a long history of human landscape modification. A severe drought in 2014-2015 led to a major water crisis and highlighted the fragility of the regional water supply system. We found that human-dominated watersheds had lower overall water quality when compared to forested watersheds, with urban cover showing the most detrimental impacts on water quality. Forest cover was associated with a better overall water quality across the studied watersheds, with forested watersheds having low turbidity and high dissolved oxygen. High precipitation led to increased turbidity and fecal coliforms levels and lower dissolved oxygen in streams but these effects depended on watershed land cover. High precipitation diluted concentrations of nitrogen and dissolved solids in highly urbanized watersheds but exacerbated turbidity in pasture-dominated watersheds. Given the high costs of water treatment in densely populated regions, there is a pressing need to plan and manage landscapes in order to ensure adequate water resources. In tropical regions, maintaining or restoring native vegetation cover is a promising intervention to sustain adequate water quality.

Using a grey multivariate model to predict impacts on the water quality of the Zhanghe River in China

In order to assess the social factors affecting the water quality of the Zhanghe River and predict the potential impact of growth in primary, secondary, tertiary industries and population on water quality of the Zhanghe River in the next few years, a deformation derivative cumulative grey multiple convolution model (DGMC(1,N)) was applied. In order to improve the accuracy of the model, the accumulation of deformation derivatives is introduced, and the particle swarm optimization algorithm is used to solve the optimal order. The DGMC(1,N) model was compared with GM(1,2) and GM(1,1) models. The results show that the DGMC(1,N) model has the highest prediction accuracy. Finally, DGMC(1,N) model is used to predict the potential impact of growth in primary, secondary, tertiary industries and population on water quality in the Zhanghe River (using chemical oxygen demand (COD) as the water quality indicator).

How fish traits and functional diversity respond to environmental changes and species invasion in the largest river in Southeastern China

Background

Freshwater fish populations are facing multiple stressors, including climate change, species invasion, and anthropogenic interference. Temporal studies of fish functional diversity and community assembly rules based on trait-environment relationships provide insights into fish community structure in riverine ecosystems.

Methods

Fish samples were collected in 2015 in the Min River, the largest freshwater riverine system in Southeastern China. Fish functional diversity was compared with the background investigation in 1979. Changes in functional richness, functional evenness, functional divergence, and functional beta diversity were analyzed. Relationships between functional diversity and environmental factors were modeled by random forest regression. Correlations between fish functional traits and environmental factors were detected by fourth-corner combined with RLQ analysis.

Results

Functional richness was significantly reduced in 2015 compared with 1979. Functional beta diversity in 2015 was significantly higher than that in 1979, with functional nestedness being the driving component. Reduction of functional richness and domination of functional nestedness is associated with species loss. Trait convergence was the dominant mechanism driving the temporal changes of functional diversity. Precipitation, temperature, species invasion, and human population were the most significant factors driving fish functional diversity. Higher precipitation, higher temperature, and presence of invasive species were significantly associated with higher swimming factor and higher relative eye diameter, while the opposite environmental conditions were significantly associated with higher pectoral fin length and eurytopic water flow preference.

Conclusions

Environmental filtering is the dominant temporal assembly mechanism shaping fish community structure. This work contributes to the understanding of temporal freshwater fish community assembly and the associations between fish functional structure and local environmental conditions, which will be informative for future freshwater fish conservation.

Nitrogen Fertilization. A Review of the Risks Associated with the Inefficiency of Its Use and Policy Responses

Nitrogen (N) is a key input to food production. Nearly half of N fertilizer input is not used by crops and is lost into the environment via emission of gases or by polluting water bodies. It is essential to achieve production levels, which enable global food security, without compromising environmental security. The N pollution level expected by 2050 is projected to be 150% higher than in 2010, with the agricultural sector accounting for 60% of this increase. In this paper, we review the status of the pollution from N fertilizers worldwide and make recommendations to address the situation. The analysis reviews the relationship between N fertilizer use, N use efficiency, no-point pollution, the role of farmer management practices, and policy approaches to address diffuse pollution caused by N fertilization. Several studies show a lack of information as one of the main hurdles to achieve changes in habits. The objective of this study is to highlight the gravity of the current global non-point pollution as well as the need for a communication effort to make farmers aware of the relationship between their activity and N pollution and, therefore, the importance of their fertilizer management practices.

A multicriteria evaluation approach to set forest restoration priorities based on water ecosystem services

Forest plays an important role in keeping water ecosystem services, such as drinking water provision. Thus, payment for ecosystem services is an essential instrument to promote forest restoration in agricultural watersheds. However, funds are limited and must be well planned to ensure water resources conservation and water ecosystem services improvement. In this context, our study aimed to identify priority areas for forest restoration, based on water ecosystem services in agricultural landscapes. For this, we have developed a decision-making support model for agricultural watersheds (in the Atlantic Forest region), based on mixed approaches, that were multicriteria evaluation (MCE) and Participatory Technique. The model will help decision-makers and stakeholders to set priorities for payment for ecosystem services programs implementation. So, we evaluate its application in watersheds with different forest cover patterns to check if it can be applied to different landscape patterns. The base of the model was the following criteria, that were produced with high-resolution data and ranking in the Participatory Technique context, considering their importance for the study: proximity to spring, slope, soil erodibility, topographic index, and land-use/land-cover (LULC). The criteria were aggregated by the Weighted Linear Combination (WLC) method (an MCE method). The priorities maps showed areas classified as high priority near the rivers (at most 200 m far from rivers), on the greatest slopes (>40%), on soils associated with high potential of erosion, and predominantly in agriculture lands. However, this class presented more percentage of the area associated with native forest in the forested watershed (native forest covers 55% of its area) than in the watershed non-forested (native forest covers 25%). Another important point of the final maps was a high percentage of areas associated with the medium class, which is a characteristic of the WLC method. Thus, areas classified as high and medium priority was defined as targets for forest restoration in the watersheds. We can conclude that for small watersheds, the MCE method, with high-resolution data, supports an appropriate prioritization of areas for forest restoration, aiming at the improvement of water ecosystem services. This way, our model can be applied to various payments for ecosystem services schemes in agricultural landscapes worldwide.

Damming affects riverine macroinvertebrate metacommunity dynamics: Insights from taxonomic and functional beta diversity

Understanding ecological processes that drive metacommunity dynamics is essential for elucidating the mechanisms of community assembly and for guiding biodiversity conservation. This is especially important in dammed rivers. Here, we examined the taxonomic and functional beta diversity of macroinvertebrates and their underlying drivers in a dammed tropical river and compared the patterns with those in an adjacent undammed river. We found that both taxonomic and functional beta diversities were higher in the dammed river than in the undammed river across wet and dry seasons. The replacement component contributed most to the overall beta diversity for both taxonomic and functional facets, and this component was higher in the dammed river than in the undammed river. In addition, the taxonomic richness difference component was significantly higher in the dammed river in the dry season, but the functional richness difference component showed no difference between the two rivers and between the two seasons. Environmental filtering was the primary driver of total beta diversity and its replacement component, whereas the richness difference component was mainly explained by spatial factors, but these drivers varied in the dammed river in different seasons. Overall, our results indicated that damming induced changes in physiochemical variables (e.g., temperature, conductivity, and nutrients), accompanied by alterations in flow regime and longitudinal connectivity, increased replacement and loss of taxa or traits. These changes have consequently led to alteration of macroinvertebrate taxonomic and functional community dissimilarity and affected the relative effects of environmental and spatial factors on beta diversity and its components. Our study helps understand the ecological processes associated with dam impacts on macroinvertebrate biodiversity and the conservation potential of undammed rivers. In addition, our results showed that taxonomic and functional beta diversities can provide complementary information about dam impacts on riverine biodiversity.

From Monitoring and Modeling to Management: How to Improve Water Quality in Brazilian Rivers? A Case Study: Piabanha River Watershed

Water quality has been a global concern, as evidenced by UN Sustainable Development Goals. The current paper has focused on the Piabanha River rehabilitation as a case study which can be generalized to other similar watersheds. A monitoring program during a hydrological year was carried out, and different databases were used to calibrate and validate the QUAL-UFMG water quality model. Sanitation is the major problem in the watershed, notably in its headwater catchments, which concentrate the most urbanized regions where water quality is worse in the dry season due to low river flows. Thus, simulations of the river water quality have been performed through computational modeling suggesting organic load reductions in some sub-basins. In conclusion, some strategies to improve water quality have been discussed: (i) The water quality rehabilitation must consider progressive goals of pollution reduction starting with an initial implementation in a reduced area. The monitoring should be based on a few parameters relevant and simple to monitor. (ii) Pollution reduction ought to be carried out strategically with deadlines and intermediate goals that must be agreed upon between the stakeholders in the watershed. (iii) Watershed committees should supervise projects to improve water quality in partnership with the State Prosecutor’s Office.