A partial least squares - Path modeling analysis for the understanding of biodiversity loss in rural and urban watersheds in Portugal

Microbial community structure and causal analysis in sediments of shallow eutrophic freshwater lakes under heavy metal compound pollution

Heavy metals, due to their toxicity, persistence, and non-biodegradability, have become some of the most severe environmental pollutants globally. Their accumulation in lake sediments can significantly impact aquatic ecosystems' biogeochemical cycles by altering the ecological dynamics of microbial communities. To further elucidate the mechanisms underlying microbial responses to complex heavy metal pollution in lake sediments, sediment samples were collected from Nan Yi Lake, and their physicochemical properties and microbial composition were systematically analyzed. The results demonstrated that the sediments of Nan Yi Lake were significantly contaminated with heavy metals, which were identified as the predominant factors shaping microbial community structure. Heavy metals influenced microbial richness and distribution patterns along sediment depth gradients, driving the establishment of optimal ecological niches. Meanwhile, other physicochemical factors indirectly affected microbial communities by modulating the concentration of heavy metals. Furthermore, the microbial co-occurrence network was closely associated with the concentrations of Fe and As, with sediment particle size also playing a contributing role. This study highlights the intricate interactions between physicochemical factors and microorganisms, offering critical insights into the multifaceted impacts of heavy metal compound pollution on lake ecosystems. It provides a scientific foundation for effective management of lake environmental pollution and ecological restoration efforts.

Ecological health and security of the Jazmurian Wetland Endorheic Watershed, Iran

Wetlands represent a crucial category of aquatic ecosystems that face numerous threats, such as increasing population density, alterations in land-use, climate change, excessive extraction of water resources, and inadequate construction of reservoirs. As a result of these challenges, wetlands cannot perform their essential functions, which include meeting human demands, supporting tourism, mitigating dust storms, and maintaining the biodiversity of flora and fauna. Accordingly, assessing their health and service performance is essential. However, studies on the health and security assessment of the wetland are scant. Therefore, an attempt has been made to evaluate the Jazmurian Wetland Watershed health using the cause-effect pressure (P), state (S), and response (R) conceptual approach. To this end, the problem-oriented variables were obtained through field surveying and data augmentation. Some 12 independent input variables were finalized using principal component analysis (PCA) to assess the watershed health and security at the sub-watershed scale. The study's results elucidated that P = 0.564, S = 0.368, and R = 0.643 were classified in moderate class with negative orientation, relatively desirable with negative inclination, and high with negative tendency, respectively. The overall weighted health and security indices for the Jazmurian Wetland Watershed were 0.504 and 0.446, classifying in moderate conditions with a slight positive tendency. Accordingly, an insight focused on controlling the most influential variables in the P and S indices and pertaining existing conditions on the R index-related factors in priority sub-watersheds is a vital task to take toward ecosystem sustainability. Considering the fragile health and security of the Jazmurian Wetland Watershed, management actions need to be incorporated to prevent further decline and perpetuation of situations in the region.

Estimation of the ecological integrity of the Guadiana River using Partial Least Squares Path Modelling and simulation scenarios

Ecological integrity is fundamental to human life and ecosystems, so its assessment and management are crucial. This concept assesses ecosystem health by examining physico-chemical and biological characteristics, riparian vegetation and macroinvertebrate communities. In recent decades, water resources have undergone significant changes due to various factors that have contributed to the physical, chemical and biological pollution of water. To address this problem, a specific model has been developed using the Partial Least Squares Path Modelling methodology to analyse and quantify the main factors affecting the ecological integrity of the Spanish part of the Guadiana River (Spain). The variables analysed at the different sampling points in the catchment include forest cover, anthropogenic pressure, water quality and biological integrity. Water quality and biological integrity, in turn, constitute the concept of ecological integrity. The model predicts 60.3 % of the physico-chemical water quality and 56.6 % of the biological integrity, showing that ¨Forest cover¨ negatively impacts water quality (W = -0.476) by reducing pollution, while ¨Anthropogenic Pressure¨ positively impacts it (W = 0.680) by increasing pollution. Based on the modelling, three future scenarios were designed, from the lowest to the highest pressure considering changes in riparian forest quality based on QBR and changes in the number of reservoirs: a favourable scenario with high riparian forest quality and no reservoirs; an intermediate scenario with good riparian forest quality and no change in the number of reservoirs; and an unfavourable scenario, characterised by very poor riparian forest quality and an increase in the number of reservoirs. In this context, the importance of the conservation and enhancement of riparian vegetation as a nature-based solution is highlighted, as well as the pressure generated by industrial activity and agricultural practices on the ecological integrity of the study area. The favourable scenario, with very good quality riparian vegetation, improves water quality by up to 85 %, positively impacting the ecological integrity of the river. In contrast, the unfavourable scenario, with extremely degraded riparian forest, would decrease water quality by up to 62 %, negatively affecting ecological integrity. Modelling and future scenarios is an essential tool in the decision-making process to improve environmental governance and water security. In addition, the PLS-PM methodology allows the identification and quantification of relationships between complex variables, providing a solid basis for the design of effective environmental management strategies.

Cadaverine and putrescine exposure influence carbon and nitrogen cycling genes in water and sediment of the Yellow River

The response patterns of microbial functional genes involved in biogeochemical cycles to cadaver decay is a central topic of recent environmental sciences. However, the response mechanisms and pathways of the functional genes associated with the carbon (C) and nitrogen (N) cycling to cadaveric substances such as cadaverine and putrescine remain unclear. This study explored the variation of functional genes associated with C fixation, C degradation and N cycling and their influencing factors under cadaverine, putrescine and mixed treatments. Our results showed only putrescine significantly increased the alpha diversity of C fixation genes, while reducing the alpha diversity of N cycling genes in sediment. For the C cycling, the mixed treatment significantly decreased the total abundance of reductive acetyl-CoA pathway genes (i.e., acsB and acsE) and lig gene linked to lignin degradation in water, while only significantly increasing the hydroxypropionate-hydroxybutylate cycle (i.e., accA) gene abundance in sediment. For the N cycling, mixed treatment significantly decreased the abundance of the nitrification (i.e., amoB), denitrification (i.e., nirS3) genes in water and the assimilation pathway gene (i.e., gdhA) in sediment. Environmental factors (i.e., total carbon and total nitrogen) were all negatively associated with the genes of C and N cycling. Therefore, cadaverine and putrescine exposure may inhibit the pathway in C fixation and N cycling, while promoting C degradation. These findings can offer some new insight for the management of amine pollution caused by animal cadavers.

The main threats facing the eel (Anguilla anguilla) and the sea lamprey (Petromyzon marinus) in Galicia (NW Spain) through Partial Least Squares Path Modelling

Migratory fish are very important species from an ecological and socioeconomic point of view, but they suffer the effects of many threats such as climate change, pollution, or overfishing, thus contributing to the decline of these species. To study the main factors influencing these species, Partial Least Squares Path Modelling (PLS-PM) methodology has been used to analyse and quantify the main threats facing two highly relevant migratory species: the eel (Anguilla anguilla) and the sea lamprey (Petromyzon marinus). Based on this statistical approach, two models have been developed for a total of 14 rivers located in the Autonomous Community of Galicia (NW Spain), one for the eel and the other for the lamprey. For the construction of the models, the influence of environmental factors, surface water quality and anthropogenic impacts on the population of these species has been studied. Two scenarios have also been simulated to assess how the application of corrective measures to reduce the anthropogenic impact implies important improvements to the eel and lamprey populations. The results of the models developed indicate that the variables analysed predict 69% of the eel "Population", with the weight of the measured variables (MV) 'Water treatment plants' having the most substantial weight (W=0.939) followed by the significant negative influence of 'Surface area of reservoirs and rivers' (W=-0.746). Similarly, in the lamprey model, an R2 of 0.58 has been obtained, where the negative influence of the MV "Agricultural nitrate discharge points" (-0.938) stands out substantially. In relation to the scenarios developed for both species, we highlight that the application of measures aimed at reducing anthropogenic pressure manages to mitigate the impact by 4.82% in the case of eel and by 1.37% in the case of lamprey. The set of models and scenarios proposed will make it possible to design preventive and corrective measures to mitigate the impacts affecting these populations, guaranteeing the integrated management of these species, and improving future decision-making, thus strengthening environmental governance.

Ecological structure of aquatic macroinvertebrate communities in the Hauts Plateaux of Northeast Algeria

Aquatic macroinvertebrates are integral parts of functioning wetlands, inhabiting a diversity of aquatic ecosystems where communities are spatially structured. Macroinvertebrates of some Mediterranean regions such as North Africa are still not well studied. Here, we study the community structure of benthic macroinvertebrates in four different types of lotic and lentic wetlands in the semiarid Haut Plateaux of Northeast Algeria. Macroinvertebrates and 06 physicochemical parameters were sampled in 12 sites belonging to four types of habitats (lotic river, lentic river, dams, and sebkha [saline lentic water body]) during January-December 2021. Eventually, the character lentic-lotic was the most important variable affecting the affecting invertebrate communities in the Mediterranean region. The results revealed that sebkha and dams had a lower Shannon index than lentic and lotic rivers. Non-metric multidimensional scaling analysis showed a strong overlap between the community composition in lotic and lentic sites . Howeverin the three types of aquatic groups lentic river, dam and lotic habitats showed a strong overlap between the community whereas sebkha was markedly separated. Redundancy analysis showed that water velocity and pH, were the main drivers of community structure of macroinvertebrates, revealed a strong effect with pH (F1,8=4.15, P = 0.001) and water velocity (F1,8= 3.22, P = 0.002) , separating lotic communities from those that inhabited dams, lentic rivers, and sebkhas. As conclusion, this study contributes to the better understanding of the community structure of macroinvertebrates in semiarid North Africa where wetlands have been experiencing high anthropogenic disturbance.

Hydrogeochemical characteristics and health risk assessment of potentially toxic elements in groundwater and their relationship with the ecosystem: case study in Tunisia

Sidi Bouzid basin knows for several decades a fast-growing anthropogenic activity and, consequently, an increase in groundwater pollution which attracted researcher attention. For this task, we performed an exhaustive study to evaluate groundwater geochemical evolution. Our research begins with analyzing the geochemical process, then determining the water quality indices and their impact on the ecosystem, and after that correlating between different compartments, and ends with the assessment of the human health risk toward NO₃^-, Fe, Mn, Zn, Cd, and Pb. The dominant facies of the groundwater in the study area are Ca-Mg-SO₄ and Ca-Mg-HCO₃ and are mainly influenced by evaporite deposits (CaSO₄, CaSO₄·2H₂O, and NaCl). The pollution index of groundwater (PIG) displays values ranging between 0.5 and 4.5 indicating four classes of pollution (insignificant, low, moderate, and high). More than half of the samples (55%) belong to the low and moderate PIG classes. However, the results show elevated values of NO₃^- concentration; 76% of samples exceed 30 mg/L. Among the studied contaminants, the highest carcinogenic and non-carcinogenic risks in study areas were related to NO₃^-. For all water samples, the risk levels for children were greater than those for adults. Lastly, the partial least square-structural equation modelling (PLS-SEM) shows that the chemical elements do not have a short-term potential impact of pollutants on ecosystems.

Multi-omics methods reveal that putrescine and cadaverine cause different degrees of enrichment of high-risk resistomes and opportunistic pathogens in the water and sediment of the Yellow River

Contamination of antibiotic resistomes due to animal carcass decay has become a serious environmental concern. However, the relationship between main metabolite compounds of corpse decomposition (i.e., putrescine and cadaverine) and antibiotic resistomes remains unclear. To tackle this issue, the response of antibiotic resistance genes (ARGs) and microbiome in aquatic environment to excess putrescine, cadaverine and a mixture of both based on laboratory simulation experiment was investigated by high-throughput quantitative PCR and amplicon sequencing methods. Our results showed putrescine and cadaverine led to the increasing of TC (total carbon) and TN (total nitrogen) both in water and sediment. Under the exposure of putrescine and cadaverine, the total abundance of mobile genetic elements (MGEs) and most ARGs in water was higher than in sediment. In particular, putrescine and cadaverine caused significantly different decreases in alpha diversity of microbial community in water and sediment compared with the control group. Microbial community structures both in water and sediment were also significantly affected by cadaverine and putrescine. Furthermore, putrescine and cadaverine led to different degrees of increases of high-risk ARGs (like mecA) and opportunistic pathogens (like Delftia) in sediment, promoting the prevalence of antibiotic resistant bacteria. In conclusion, our findings revealed the influences of main metabolites of carcass decay on microbiome and resistomes, providing references for risk assessment and pollution management.

A partial least squares-path model of environmental degradation in the Paraopeba River, for rainy seasons after the rupture of B1 tailings dam, Brumadinho, Brazil

The present study aimed to investigate the rupture of B1 tailings dam of Córrego do Feijão mine, which drastically affected the region of Brumadinho (Minas Gerais, Brazil). The contamination of water resources reached 155.3 km from the dam site. In the river channel, high concentrations of Mn, Al, As and Fe were detected and correlated to the spillage of the tailings in the river. The presence of the tailings also affected the chlorophyll-a content in the water, as well as the reflectance of riparian forests. With the increase of metal(oid) concentrations above permitted levels, water management authorities suspended the use of Paraopeba River as resource in the impacted areas, namely the drinking water supply to the Metropolitan region of Belo Horizonte. This study aimed to evaluate possible links between tailings distribution, river water quality, and environmental degradation, which worked as latent variables in partial least squares regression models. The latent variables were represented by numerous physical and chemical parameters of water and sediment, measured four times in 22 locations during the rainy season of 2019, in addition to stream flow and to NDVI evaluated in satellite images processed daily. The modeling results suggested a relationship between river flow turbulence and increased arsenic release from sand fractions, as well as desorption of Mn from metal oxides, both representing causes of water quality reduction. They also revealed increasing iron concentrations affecting the forest NDVI (greening), which was interpreted as environmental degradation. The increase of chlorophyll-a concentrations (related with turbidity decreases), as well as the increase of river flows (responsible for dilution effects), seemed to work out as attenuators of degradation. Although applied to a specific site, our modeling approach can be transposed to equivalent dam failures and climate contexts, helping water resource management authorities to decide upon appropriate recovery solutions.

A partial least squares-path model of causality among environmental deterioration indicators in the dry period of Paraopeba River after the rupture of B1 tailings dam in Brumadinho (Minas Gerais, Brazil)

This study investigated the collapse of B1 mine-tailings dam that occurred in 25 January 2019 and severely affected the Brumadinho region (Minas Gerais state, Brazil) socially, economically and environmentally. As regards water resources, the event impacted the Paraopeba River in the first 155.3 km counted from the dam site, meaning nearly half the main water course downstream of B1. In the impacted sector, high concentrations of tailings-related Al, Fe, Mn, P in river sediment-tailings mixtures and water were detected, as well as changes to the reflectance of riparian forests. In the river water, the metal concentrations raised significantly above safe levels. For caution, the water management authorities declared immediate suspension of Paraopeba River as drinking water source to the Metropolitan Region of Belo Horizonte (6 million people), irrespective of representing nearly 30% of all supply. In this study, the main purpose was to assess potential links between tailings distribution, river water composition and reflectance of forest vegetation, which worked out as latent variables in regression models. The latent variables were represented by numerous physical and chemical parameters, measured 4 times in 22 sites during the dry period of 2019. The modeling results suggested the release of aluminum and phosphorus from sand fractions in the mine tailings as major cause of water contamination. The NDVI changes were interpreted as environmental deterioration. Changes in redox potential may have raised manganese concentrations in surface water further affecting the forest NDVI. Distance from the B1 dam and dissolved calcium appear to attenuate deterioration. Overall, the regressions allowed robust prognoses of environmental deterioration in the Paraopeba River under low flow conditions. More importantly, they can be transposed to similar dam ruptures helping environmental authorities to decide upon measures that can bring the affected rivers to pre-rupture conditions.

Integrated assessment of the impact of land use types on soil pollution by potentially toxic elements and the associated ecological and human health risk

The impact of land use type on the content of potentially toxic elements (PTEs) in the soils of the Qinghai-Tibet Plateau (QTP) and the associated ecological and human health risks has drawn great attention. Consequently, in this study, top- and subsurface soil samples were collected from areas with four different land uses (i.e., cropland, forest, grassland, and developed area) and the total contents of Cr, Cd, Cu, Pb and Zn were determined. Geostatistical analysis, self-organizing map (SOM), and positive matrix factorization (PMF), ecological risk assessment (ERA) and human health risk assessment (HRA) were applied and used to classify and identify the contamination sources and assess the potential risk. Partial least squares path modeling (PLS-PM) was applied to clarify the relationship of land use with PTE contents and risk. The PTE contents in all topsoil samples surpassed the respective background concentrations of China and corresponding subsurface concentrations. However, the ecological risk of all soil samples remained at a moderate or considerable level across the four land use types. Developed area and cropland showed a higher ecological risk than the other two land use types. Industrial discharges (32.8%), agricultural inputs (22.6%), natural sources (23.7%), and traffic emissions (20.9%) were the primary PTE sources in the tested soils, which indicate that anthropogenic activities have significantly affected soil PTE contents to a greater extent than other sources. Industrial discharge was the most prominent source of non-carcinogenic health risk, contributing 37.7% for adults and 35.2% for children of the total risk. The results of PLS-PM revealed that land use change associated with intensive human activities such as industrial activities and agricultural practices distinctly affected the PTE contents in soils of the Qinghai-Tibet Plateau.

Experimental investigations on the vertical distribution and properties of oil-mineral aggregates (OMAs) formed by different clay minerals

After oil spills, the floating oil may interact with suspended minerals to form the oil-mineral aggregates (OMAs) in turbulent environments. In this work, a flume was used in conjunction with a settling device to investigate the vertical distribution and properties of OMAs formed by different clay minerals. The density and size of OMAs depend on the density and surface properties of the constituent particles, which also affect the vertical distribution of dispersed oil. Density of oil-montmorillonite aggregates increased from 1165 to 1897 kg/m3 within 6 h test. Among the four minerals, montmorillonite displayed the highest affinity with dispersed oil and the most significant modification of oil-water interfacial tension. Oil dispersion efficiency was significantly greater and reached 39.3% in the presence of montmorillonite at 300 mg/L compared with the control group (17.6%). Particle concentration is the most important factor for the capture of oil and participation of particles during the OMA formation, while the zeta potential and hydrophobicity have nonsignificant effect on the two processes. Cation exchange capacity has a moderate effect on the sunken oil formation, which is also the second main factor governing the particle participation. Particle size plays a second leading role in governing the sunken oil formation but with a minor contribution of the particle participation.

Modelling of threats that affect Cyano-HABs in an eutrophicated reservoir: First phase towards water security and environmental governance in watersheds

Cyano-HABs are proliferating around the world due to anthropogenic nutrient enrichment of freshwater bodies. This study seeks to obtain a holistic vision over the various threats that affect the Cyano-HABs of Umia basin and especially of A Baxe reservoir (Galicia, NW Spain), through the method of Partial least squares path modelling (PLS-PM). The A Baxe reservoirs is a fundamental source of drinking water supply to surrounding dwellings. This study identifies and quantify the variables that increase contaminant concentration and decrease ecological integrity, as well as how this scenario evolved over various hydrologic years. In this regard, the PLS-PM equations will be robust and powerful tools to predict changes in eutrophication and ecological integrity, as response to measures implemented in the basin that can improve water quality. The dependent latent variables are "Eutrophication" (chlorophyl-a, Microcystis sp.) and "Ecological Integrity" (METI Bioindicator). The independent latent variables are "SWP", which represents surface water parameters (phosphorus, nitrogen and pH) and "Climatic Conditions" (temperature, precipitation). The PLS-PM results revealed that 51.0% of "Eutrophication" is predicted by the independent variables. The connections between latent variables are quantified through path coefficients (β). The "SWP" contributes by increasing "Eutrophication" (β = 0.235), the same occurring with the "Climatic Conditions" (β = -0.672). The variables "Eutrophication" (β = -0.217) and "SWP" (β = -0.483) lower the "Ecological Integrity". On the other hand, different trophic scenarios, adapted to the temperature increase predicted for the study area, were tested, and it was found that ecological integrity would improve by 46% if the oligotrophic state were reached. Therefore, it is recommended to prevent pollution by means of water control and governance plans, as well as corrective and preventive measures, which guarantee the water security of the river basins. Despite the complex mathematics behind the PLS-PM models, their user-friendly development and application through interactive graphical interfaces make them easily transposable to other eutrophic reservoirs, widening the readership of these studies focused on multiple-geosphere assessment of environmental impacts.

Coupling Coordination Analysis and Prediction of Landscape Ecological Risks and Ecosystem Services in the Min River Basin

Watershed landscape ecological security and ecosystem service functions are the material basis and environmental guarantee for promoting socioeconomic development. Analyzing the spatiotemporal characteristics of landscape ecological risks (LERs) and ecosystem services (ESs) and exploring the coupling coordination relationship between the two are of great significance for promoting the construction of ecological civilization and achieving sustainable development in the watershed. With the Min River Basin as the study area, the landscape ecological risk assessment, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), and Carnegie Ames–Stanford Approach (CASA) models were used to evaluate the LERs and ESs based on the shared socioeconomic pathways (SSPs), and the patch-generating land use simulation (PLUS) model was used to predict the land use distribution of the Min River Basin in 2030. On this basis, the coupling coordination degree model was used to explore the coupling coordination relationship between the LERs and ESs. The results show that, from 2000 to 2020, the LER of the Min River Basin gradually decreased, and the overall spatial distribution pattern was “high in the north and low in the south”. The ES of the Min River Basin initially decreased and then increased, showing a spatial distribution pattern of “low in the south and high in the north”. Among the SSPs in 2030, the LER is the largest under the SSP3 scenario and the smallest under the SSP4 scenario. The ES improvement is the most significant under the SSP1 scenario and the lowest under the SSP3 scenario. From 2000 to 2030, the coupling coordination degree of the Min River Basin first decreased and then increased, showing a spatial distribution pattern of “high in the south and low in the north”. Among the five SSPs, the coupling coordination degree was the highest under SSP1. The spatial distribution of urban area is the main driving factor affecting the coupling coordination relationship between the LER and ES, and the development of social and economy is the beginning of landscape pattern optimization.

A combined GIS-MCDA approach to prioritize stream water quality interventions, based on the contamination risk and intervention complexity

Water management decisions are complex ever since they are dependent on adopted politics, social objectives, environmental impacts, and economic determinants. To adequately address hydric resources issues, it is crucial to rely on scientific data and models guiding decision-makers. The present study brings a new methodology, consisting of a combined GIS-MCDA, to prioritize catchments that require environmental interventions to improve surface water quality. A Portuguese catchment, Ave River Basin, was selected to test this methodology due to the low water quality. First, it was calculated the contamination risk of each catchment, based on a GIS-MCDA using point source pressures, landscape metrics, and diffuse emissions as criteria. This analysis was compared to local data of ecological and chemical status through ANOVA and the Tukey test. The results showed the efficiency of the method since the contamination risk was lower for catchments under a good status and higher in catchments with a lower classification. In a second task, it was calculated the intervention complexity using a different GIS-MCDA. For this approach, it was chosen five criteria that condition environmental interventions, population density, slope, percentage of burned areas, Strahler order, and the number of effluent discharge sites. Both multicriteria methods were combined in a graphical analysis to rank the catchments intervention priority, subdividing the prioritization into four categories from 1st to 4th^, giving a higher preference for catchments with high contamination risk and low intervention complexity. As a result, catchments with a good status were dominantly placed under low intervention priority, and catchments with a lower ecological status were classified as a high priority, 1st and 2nd. In total, 248 catchments were spatially ranked, which is an essential finding for decision-makers, that are willing to safeguard the catchment water quality.

Impacts of riparian width and stream channel width on ecological networks in main waterways and tributaries

Riparian buffer width and stream channel width have different impacts on ecological networks (e.g., plant cover, regeneration, exotics, erosion, habitat, and stressors) and provide various ecosystem services. The protection of riparian zones of increasing widths for higher-order streams and connected tributaries alongside mega-reservoirs and around dams is of great global significance. However, it remains unclear which protection strategies are most effective for such zones. By applying a rapid field-based approach with 326 transects on an inundated area of 58,000 km² within the Three Gorges Dam Reservoir (TGDR) in China, we found that riparian buffer areas were influenced differently by broad-ranging widths. The riparian buffer width of 101.84 ± 72.64 m (mean ± standard deviation) had the greatest impact on the main waterway, whereas the stream channel width of 99.87 ± 97.10 m was most influential in tributaries. The correlation coefficient strengths among ecological and stress parameters (independently) were relatively greater in the main waterway riparian zones; the highest value was r = 0.930 using Pearson correlation (p < 0.05). In contrast, stress parameters revealed substantial and strong relationships with ecological parameters in tributaries, with the highest value being r = 0.551. Riparian width had the strongest influence on buffer vegetation scales, high-impact exotics, and bank stability. In comparison, channel width had the greatest effect on tree roots, dominant tree regeneration, and agricultural farming. These parameters showed distinctive responses in the shapes of indexing in higher-order streams and connected tributaries. These observations confirm the urgent need for research on regional-based extended riparian areas managed by the same administration strategies. Revised guidelines are needed to protect massive dam and reservoir ecosystems from further deterioration.

Spatio-seasonal variation of water quality influenced by land use and land cover in Lake Muhazi

Understanding the influence of land use/land cover (LULC) on water quality is pertinent to sustainable water management. This study aimed at assessing the spatio-seasonal variation of water quality in relation to land use types in Lake Muhazi, Rwanda. The National Sanitation Foundation Water Quality Index (NSF-WQI) was used to evaluate the anthropogenically-induced water quality changes. In addition to Principal Components Analysis (PCA), a Cluster Analysis (CA) was applied on 12-clustered sampling sites and the obtained NSF-WQI. Lastly, the Partial Least Squares Path Modelling (PLS-PM) was used to estimate the nexus between LULC, water quality parameters, and the obtained NSF-WQI. The results revealed a poor water quality status at the Mugorore and Butimba sites in the rainy season, then at Mugorore and Bwimiyange sites in the dry season. Furthermore, PCA displayed a sample dispersion based on seasonality while NSF-WQI's CA hierarchy grouped the samples corresponding to LULC types. Finally, the PLS-PM returned a strong positive correlation (+ 0.831) between LULCs and water quality parameters in the rainy season but a negative correlation coefficient (- 0.542) in the dry season, with great influences of cropland on the water quality parameters. Overall, this study concludes that the lake is seasonally influenced by anthropogenic activities, suggesting sustainable land-use management decisions, such as the establishment and safeguarding protection belts in the lake vicinity.

Estimating water erosion from the brightness index of orbital images: A framework for the prognosis of degraded pastures

The inadequate management of soils and the absence of conservation practices favor the degradation of pastures and can trigger adverse environmental alterations and damage under the terms of Brazilian Federal Law no. 6.938/1981. Based on this premise, this study aimed to estimate soil losses caused by water erosion in pasture areas using the brightness index (BI) from the annual series of Landsat 8 images in different geological formations. A specifically prepared Google Earth Engine (GEE) script automatically extracted the BI from the images. The study occurred in the Environmental Protection Area (EPA) of Uberaba River basin (Minas Gerais, Brazil). To accomplish the goal, 180 digital 500-wide random buffers were selected from 3 geologic types (60 points per type), and then analyzed for zonal statistics of USLE (Universal Soil Loss Equation) soil loss and BI in a Geographic Information System. The regression models BI versus USLE soil loss allowed estimating BI soil losses over the pastures of EPA. The model fittings were remarkable. The validation of soil loss maps in the EPA occurred in pasture phytophysiognomies through the probing of penetration resistance in 37 randomly selected locations. The results were satisfactory, mostly those based on the BI. The BI losses increased for greater resistances. Amplified losses also occurred in regions exposed to environmental land use conflicts (actual uses that deviate from land capability or natural use). Overall, the BI approach proved efficient to accurately track soil losses and pasture degradation over large areas, with the advantage of standing on a single parameter easily accessed through remote sensed data. From an environmental standpoint, this is an important result, because the accurate diagnosis and prognosis of degraded pastures is paramount to implement mitigation measures following the "polluter pays principle", even more in Brazil where the areas occupied by degraded pastures are enormous.

Effects of both climate change and human water demand on a highly threatened damselfly

While climate change severely affects some aquatic ecosystems, it may also interact with anthropogenic factors and exacerbate their impact. In dry climates, dams can cause hydrological drought during dry periods following a great reduction in dam water discharge. However, impact of these severe hydrological droughts on lotic fauna is poorly documented, despite climate change expected to increase drought duration and intensity. We document here how dam water discharge was affected by climate variability during 2011-2018 in a highly modified watershed in northeastern Algeria, and how an endemic endangered lotic damselfly, Calopteryx exul Selys, 1853 (Odonata: Calopterygidae), responded to hydrological drought episodes. Analysis was based on a compilation of data on climate (temperature, precipitation, and drought index), water dam management (water depth and discharge volume and frequency), survey data on C. exul occurrence, and capture-mark-recapture (CMR) of adults. The study period was characterized by a severe drought between 2014 and 2017, which led to a lowering of dam water depth and reduction of discharge into the river, with associated changes in water chemistry, particularly during 2017 and 2018. These events could have led to the extirpation of several populations of C. exul in the Seybouse River (Algeria). CMR surveys showed that the species was sensitive to water depth fluctuations, avoiding low and high water levels (drought and flooding). The study shows that climate change interacts with human water requirements and affects river flow regimes, water chemistry and aquatic fauna. As drought events are likely to increase in the future, the current study highlights the need for urgent new management plans for lotic habitats to maintain this species and possible others.

A case study of factors controlling water quality in two warm monomictic tropical reservoirs located in contrasting agricultural watersheds

The integration of internal (e.g., stratification) and external (e.g., pollution) factors on a comprehensive assessment of reservoir water quality determines the success of ecosystem restoration initiatives and aids watershed management. However, integrated analyses are scarcer than studies addressing factors separately. Integration is likely more efficient in studies of small well-characterized (experimental) reservoir watersheds, because the isolation of factor contributions is presumably clearer. But those studies are uncommon. This work describes the water quality of two small 5.5 m-deep reservoirs (MD-Main and VD-Voçoroca dams) located in Pindorama Experimental Center, state of São Paulo, Brazil, considering the interplay between reservoir dimension, seasonal thermal stratification, chemical gradients, erosive rainfall events, presence of natural biofilters, and land uses and landscape patterns around the reservoirs and within the contributing watersheds. The monitoring of agricultural activities and water quality parameters occurred in October 2018-July 2019. A 4 °C thermal stratification occurred in October (difference between surface and bottom water temperature), which decreased until disappearance in January (VD) or April (MD). The longer stratification period of MD was justified by its larger area relative to VD (≈10×). Thermal stratification triggered hypoxia at the bottom of both reservoirs (DO ≈ 1 mg/L), more prolonged and severe in MD. Hypoxia activated Ec and TDS peaks in January likely explained by bottom-sediment nutrient releases, presumably phosphorus. The Ec peak reached 560 μS/cm in MD and 290 μS/cm in VD. The smaller VD peak was probably explained by the action of macrophytes. In March, a 240 NTU turbidity peak occurred in MD, caused by precedent erosive rainfall and the lack of vegetation protection alongside the south border. As expected, the study accomplished clear isolation of factor contributions, verified by Factor and Cluster analyses. Our results can subsidize studies on larger reservoir watersheds requiring restoration, where the isolation of factors is more challenging.

Water security and watershed management assessed through the modelling of hydrology and ecological integrity: A study in the Galicia-Costa (NW Spain)

Water management is a crucial tool for addressing the increasing uncertainties caused by climate change, biodiversity loss and the conditions of socioeconomic limits. The multiple factors affecting water resources need to be successfully managed to achieve optimal governance and thus move towards water security. This study seeks to obtain a holistic vision of the various threats that affect the ecological integrity of the basins that form the hydrological district of Galicia-Costa, through the method of partial least squares path modelling (PLS-PM). The data is analysed overall for the hydrological years from 2009 to 2015. The independent latent variables are "Anthropogenic" (comprising the percentage of water bodies with edges alongside artificial surfaces, the percentage connected to artificial land use patches, the edge density of artificial surfaces and population density) and "Nature" (edge density of forestry land uses, edge length of land water bodies alongside forested areas and the percentage of land occupied by the largest patch of forest). The dependent latent variables are "SWP", which represents surface water parameters (biological oxygen demand, chlorides, conductivity and dissolved iron) and "Ecological Integrity" (METI Bioindicator). The connections between latent variables are uantified through path coefficients (β). From an overall perspective, the PLS-PM results reveal that 69.0% of "SWP" is predicted by the independent variables (R² = 0.690), "Anthropogenic" contributes by increasing SWP (β = 0.471), while "Nature" decreases the concentration of SWP (β = -0.523), which indicates the polluting parameters in the water. The variables "Anthropogenic" (β = -0.351) and "SWP" (β = -0.265) lower the quality of "Ecological Integrity". This variable must be managed through soil conservation measures for the benefit of water security. This study has been able to identify and quantify the variables that increase contaminant concentration and decrease ecological integrity, providing a promising methodology that facilitates protection and correction measures to guarantee water safety.

Impact of anthropogenic pressures on wild mammals of Northern Portugal

Background and Aim:

Wild mammals are among the most threatened species of the world in large part due to human activity. In this work, we used the method of partial least squares-path modeling associated with a geographic information system to analyze the impact of anthropogenic pressures on the mortality of wild mammals.

Materials and Methods:

We collected the data related to the cause of death of native wild mammals admitted to the Wildlife Rehabilitation Centre of Parque Biológico de Gaia in Northern Portugal, during 10 years (2008-2017).

Results:

A total of 359 animals from 42 municipalities (rural and urban areas) were included in the study. The main cause of death was of traumatic origin. From the anthropogenic pressures included in the study, water reservoirs, small companies, and residential buildings were the ones that contributed the most to increase the mortality of traumatic and non-traumatic origin. This relation of cause-effect (mortality-anthropogenic pressures) was supported by the high coefficients of determination obtained (R² > 0.8).

Conclusion:

The present results allow a general view on the reality of mammal’s mortality in Northern Portugal. Furthermore, it could also constitute a valuable tool for the conservation of wild mammals in those areas.

Integrating Remote Sensing and Landscape Characteristics to Estimate Soil Salinity Using Machine Learning Methods: A Case Study from Southern Xinjiang, China

Soil salinization, one of the most severe global land degradation problems, leads to the loss of arable land and declines in crop yields. Monitoring the distribution of salinized soil and degree of salinization is critical for management, remediation, and utilization of salinized soil; however, there is a lack of thorough assessment of various data sources including remote sensing and landscape characteristics for estimating soil salinity in arid and semi-arid areas. The overall goal of this study was to develop a framework for estimating soil salinity in diverse landscapes by fusing information from satellite images, landscape characteristics, and appropriate machine learning models. To explore the spatial distribution of soil salinity in southern Xinjiang, China, as a case study, we obtained 151 soil samples in a field campaign, which were analyzed in laboratory for soil electrical conductivity. A total of 35 indices including remote sensing classifiers (11), terrain attributes (3), vegetation spectral indices (8), and salinity spectral indices (13) were calculated or derived and correlated with soil salinity. Nine were used to model and estimate soil salinity using four predictive modelling approaches: partial least squares regression (PLSR), convolutional neural network (CNN), support vector machine (SVM) learning, and random forest (RF). Testing datasets were divided into vegetation-covered and bare soil samples and were used for accuracy assessment. The RF model was the best regression model in this study, with R2 = 0.75, and was most effective in revealing the spatial characteristics of salt distribution. Importance analysis and path modeling of independent variables indicated that environmental factors and soil salinity indices including digital elevation model (DEM), B10, and green atmospherically resistant vegetation index (GARI) showed the strongest contribution in soil salinity estimation. This showed a great promise in the measurement and monitoring of soil salinity in arid and semi-arid areas from the integration of remote sensing, landscape characteristics, and using machine learning model.

Watersheds, Anthropogenic Activities and the Role of Adaptation to Environmental Impacts

Runoff has shaped the Earth into watersheds, and humans have appropriated many of them [...]

A new radon prediction approach for an assessment of radiological potential in drinking water

Inhaled radon from groundwater used for domestic purposes is one of the sources of natural radioactivity into indoor air. Due to uranium-bearing minerals occurrences, hydrogeochemical conditions, tectonic structures, and hydraulic circuits, the radon pathway from rocks to groundwater is quite unpredictable. High radon potential from bedrocks is not always associated with high radon levels in groundwater. Besides, inhaled radon from domestic use may also increase the exposure toindoor radon levels. This innovative methodology using hydrogeochemical conditions and groundwater flow transport was used for radon predictions in the underground to ensure safe drinking water ingestion and inhalation. This innovative radon prediction methodology is based on classic hydrogeochemical analyses (Eh-pH, Piper, Schöeller and Gibb's diagrams) and multivariate statistical analyses (Principal Component Analysis and Pearson's correlation). High dissolution of major ions does not imply high radon mobilization from rocks to groundwater. The travel time was estimated to developed a flow transport of contaminated groundwater. Radiological results show that of the 25 sampled springs, five of them contained radon concentrations above the Portuguese imposed limit (²²²Rn = 500 Bq·L^-1), and 16 of them with values above the WHO recommended limit (²²²Rn = 100 Bq·L^-1). Overall, this new approach of radon prediction showed that uranium enrichment in rocks at ideal hydrochemical conditions and emanation coefficient, and shallow circuits, are responsible for radon increasing in drinking water. The proposed approach allow to predict the areas with high radon potential groundwaters, being a tool to be used by water planners and policy makers for corrective and preventive measures in shallow groundwater flows. To safeguard clean water within the predefined deadline of Sustainable Development Goals (2030) and to ensure human health in compliance with WHO guidelines for safe drinking water, should be established priority water protection policies to reduced radon in this contaminated springs (n = 16).

Grey water footprint as an indicator for diffuse nitrogen pollution: The case of Navarra, Spain

Nitrogen is an essential element for plant growth, while its application and associated pollution is a worldwide concern. Generally, diffuse source pollution and its impacts on ecosystem health are difficult to monitor and regulate. Here we used the grey water footprint (GWF) and water pollution level (WPL) indicators, based on a soil nitrogen balance approach to differentiate between surface and groundwater, in order to better understand and quantify the pressure that nitrogen fertilisation generates on freshwater. For the first time, we compared the results of these indicators with actual nitrogen concentration data in surface and groundwater bodies, showing in both cases a positive significant correlation according to Spearman correlation coefficient. This means that the theoretical WPL results might be valuable to anticipate and identify nitrate pollution in surface and groundwater bodies. However, several factors influence the N-related processes that should be considered, such as natural attenuation. We estimated the agricultural and livestock nitrogen loads delivered to freshwater and the associated GWFs and WPLs at the municipality level in Navarra. Large GWFs are observed in southern Navarra, particularly in intensive agricultural regions such as Ribera Alta-Aragón and Ribera Baja. We estimated that 64% of the GWF related to nitrogen loads came from artificial fertilisers, 16% from manure, 11% from atmospheric deposition and the remaining 9% from biological fixation, seeds and other organic fertilisers. Among the crops, cereals had the largest contribution to the nitrogen-related GWF (54%) followed by vegetables (17%) and fodder (11%).

The modeling of pasture conservation and of its impact on stream water quality using Partial Least Squares-Path Modeling

Cattle grazing is a major source of income across the globe, and therefore conservation of pastures is vital to society. Pasture conservation requires the full understanding of factors contributing to their degradation, which is facilitated through panoramic analyses capable to handle all factors and capture their relationships at once. In this study, Partial Least Squares - Path Modeling (PLS-PM) was used to accomplish that task. The study area was the Environmental Protection Area of Uberaba River Basin (525 km²), located in the state of Minas Gerais, Brazil, and extensively used for livestock pasturing (51%). The selected (15) contributing factors comprised soil characteristics (e.g., organic matter, phosphorus content), runoff indicators (e.g., percentage of sand and clay in the soil), environmental land use conflicts (deviations of actual from natural uses), stream water quality parameters (e.g., oxidation-reduction potential-ORP, turbidity), and pasture conservation indicators (extent of degraded pasture within a pre-defined buffer). These measured variables were assembled into 5 conceptual (latent) variables to form the PLS-PM model, namely Groundcover, Pasture Conservation, Surface Runoff, Environmental Land Use Conflicts and Water Quality. The results elected Groundcover as prominent contributor to Pasture Conservation, because of its largest regression (path) coefficient (β = 0.984). The most influent measured variable was organic matter. Surface Runoff (β = -0.108) and Environmental Land Use Conflicts (β = -0.135) contribute to pasture degradation. The role of conflicts is, however, limited to predefined areas where the deviations of actual from natural uses are more expressive. Pasture Conservation contributes unequivocally to improved Water Quality (β = 0.800), expressed as high ORP. The PLS-PM model was free from multi-collinearity problems and model fits (R²) were high. This gives us confidence to implement conservation measures and improved management techniques based on the PLS-PM results, and to transpose the model to other areas requiring pasture quality improvements.

Macroinvertebrate functional feeding group alterations in response to habitat degradation of headwater Austral streams

Protecting the structural and functional integrity of lotic ecosystems is becoming increasingly important as many ecological systems face escalating pressures from human population growth and environmental impacts. Knowledge on the functional composition of macroinvertebrates in austral temperate streams is generally lacking hindering the design and implementation of water management and restoration goals. Therefore, this study examined the effects of urban land-use activities on the benthic macroinvertebrate functional feeding guild structure among different stream orders in an austral river system (Bloukrans River) in the Eastern Cape Province of South Africa. Water quality and macroinvertebrate community data were collected across two seasons from 18 sites in two different stream order categories (i.e. 1, 2 + 3), following standard methods. We separated macroinvertebrates into functional feeding groups (FFGs), which we then used to assess the effects of riparian condition on FFG organization. Linear mixed effects model (LMM) results demonstrated that total dissolved solids (TDS), canopy cover, phosphate and channel width were the key variables that described the major sources of variation in macroinvertebrate FFGs. Based on FFG proportions, collector-gatherers were the most abundant in the Bloukrans River and represented 71.3% of the macroinvertebrate assemblages. The FFG ratios indicated that all the eighteen sites were strongly heterotrophic (i.e. streams received additional sources of energy from leaf litter and other organic matter), showed below expected linkage with riparian input and stable substrates were limited. The FFG ratios offered some insights into the overall functioning of Bloukrans River system. Our results highlight the importance of including macroinvertebrate functional diversity as a complementary approach to assess the ecological integrity in management and restoration plans of river systems.

The assessment of water erosion using Partial Least Squares-Path Modeling: A study in a legally protected area with environmental land use conflicts

Water erosion has historically been assessed by various methods, with the purpose to help reducing this phenomenon. However, application of models capable to handle complex relationships between large numbers of variables is still relatively scarce. The method of Partial Least Squares-Path Modeling (PLS-PM), used in this study, was able to expose complex causal paths between soil erosion and potentially related factors, namely "Surface Runoff", "Environmental Land Use Conflicts", "Soil Fertility" and "Relief Factors", within the Environmental Protection Area of Uberaba River Basin (EPA) located in Minas Gerais state, Brazil. In the context of PLS-PM, soil erosion (dependent) and the related factors (independent) are called latent variables and described by measured or estimated parameters. For example, the "Relief Factors" were described by measured drainage density and topographic slope. These were linked to the corresponding latent variables through weights and the later joined to each other through paths. During the PLS-PM runs, weights and paths were quantified and latent variables interpreted in regard to their importance for soil erosion and spatial incidence. The spatial incidence was used to prioritize areas for soil conservation. To test the model, data were obtained from soil samples (texture and fertility parameters) or digitally extracted from cartographic products (e.g., maps of soil loss, land use, brightness index, topographic slope, drainage density), at 37 sites within the EPA. The PLS-PM results revealed that 70.2% of soil erosion is predicted by the independent variables (R² = 0.702), and that "Soil Fertility" and "Environmental Land Use Conflicts" were the most influencing ones (β = -0.758 and β = 0.346, respectively). These variables can be managed by man, through implementation of effective soil conservation measures and respect for suitable land use. It is therefore urgent to act in these regard, considering the socioeconomic and environmental importance of the EPA.

Estimation of Climatologies of Average Monthly Air Temperature over Mongolia Using MODIS Land Surface Temperature (LST) Time Series and Machine Learning Techniques

The objective of this research was to develop a robust statistical model to estimate climatologies (2002–2017) of monthly average near-surface air temperature (Ta) over Mongolia using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) time series products and terrain parameters. Two regression models were analyzed in this study linking automatic weather station data (Ta) with Earth observation (EO) images: partial least squares (PLS) and random forest (RF). Both models were trained to predict Ta climatologies for each of the twelve months, using up to 17 variables as predictors. The models were applied to the entire land surface of Mongolia, the eighteenth largest but most sparsely populated country in the world. Twelve of the predictor variables were derived from the LST time series products of the Terra MODIS satellite. The LST MOD11A2 (collection 6) products provided thermal information at a spatial resolution of 1 km and with 8-day temporal resolution from 2002 to 2017. Three terrain variables, namely, elevation, slope, and aspect, were extracted using a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), and two variables describing the geographical location of weather stations were extracted from vector data. For training, a total of 8544 meteorological data points from 63 automatic weather stations were used covering the same period as MODIS LST products. The PLS regression resulted in a coefficient of determination (R2) between 0.74 and 0.87 and a root-mean-square error (RMSE) from 1.20 °C to 2.19 °C between measured and estimated monthly Ta. The non-linear RF regression yielded even more accurate results with R2 in the range from 0.82 to 0.95 and RMSE from 0.84 °C to 1.93 °C. Using RF, the two best modeled months were July and August and the two worst months were January and February. The four most predictive variables were day/nighttime LST, elevation, and latitude. Using the developed RF models, spatial maps of the monthly average Ta at a spatial resolution of 1 km were generated for Mongolia (~1566 × 106 km2). This spatial dataset might be useful for various environmental applications. The method is transparent and relatively easy to implement.

The Role of Landscape Configuration, Season, and Distance from Contaminant Sources on the Degradation of Stream Water Quality in Urban Catchments

Water resources are threatened by many pollution sources. The harmful effects of pollution can be evaluated through biological indicators capable of tracing problems in life forms caused by the contaminants discharged into the streams. In the present study, the effects on stream water quality of landscape configuration, season, and distance from contaminant emissions of diffuse and point sources were accessed through the evaluation of a Portuguese macroinvertebrate index (IPtIN) in 12 observation points distributed within the studied area (Ave River Basin, Portugal). Partial least-squares path models (PLS-PMs) were used to set up cause–effect relationships between this index, various metrics adapted to forest, agriculture, and artificial areas, and the aforementioned emissions, considering 13 distances from the contaminant sources ranging from 100 m to 56 km. The PLS-PM models were applied to summer and winter data to explore seasonality effects. The results of PLS-PM exposed significant scale and seasonal effects. The harmful effects of artificial areas were visible for distances larger than 10 km. The impact of agriculture was also distance related, but in summer this influence was more evident. The forested areas could hold onto contamination mainly in the winter periods. The impact of diffuse contaminant emissions was stronger during summer, when accessed on a short distance. The impact of effluent discharges was small, compared to the influence of landscape metrics, and had a limited statistical significance. Overall, the PLS-PM results evidenced significant cause–effect relationships between land use metrics and stream water quality at 10 km or larger scales, regardless of the season. This result is valid for the studied catchment, but transposition to other similar catchments needs to be carefully verified given the limited, though available, number of observation points.

River nutrient water and sediment measurements inform on nutrient retention, with implications for eutrophication

The consideration of nutrients in pollution dynamics is important for environmental management and conservation. Developing countries are yet to appreciate the aquatic ecosystem pollution impacts on their economies and as such, information on water pollution dynamics is limited. This study assessed the spatio-temporal dynamics of nutrient loading and retention in stream water and sediments in the Bloukrans River system, Eastern Cape province, South Africa over the course of the wet and dry season. Sediment and water samples were analysed for total phosphorus (TP) and nitrogen (TN) concentrations, and were used in combination with river flow discharge, to determine nutrient loads. The study results highlight that river discharge plays a significant role in temporal differences in sediment and water column nutrient concentrations. The mean sediment nutrient concentration was high for the dry season, with high values being observed for the urban river system. Nutrient loads were high above the sewage treatment works outflow (i.e. urban sites), as such, a decreasing trend was observed with increasing distance from the urban environment. Nutrient loads were generally high for the dry season in comparison to the wet season indicating organic matter retention (i.e. accumulation from burst sewage pipes) most likely due to low flows. While it was evident that the ageing wastewater infrastructure contributed to the observed state of the Bloukrans River, the high natural nutrient retention capacity seemed to mitigate eutrophication of downstream aquatic ecosystems. As such, the nutrient retention capacity and management of the system is central to the entire Bloukrans River catchment management practices. Therefore, the study contributes to our understanding of water and sediment nutrient pollution dynamics in an arid temperate river landscape where vast spatio-temporal differences in base flow characterise the riverscape.

Seasonal and Scale Effects of Anthropogenic Pressures on Water Quality and Ecological Integrity: A Study in the Sabor River Basin (NE Portugal) Using Partial Least Squares-Path Modeling

Interactions between pollution sources, water contamination, and ecological integrity are complex phenomena and hard to access. To comprehend this subject of study, it is crucial to use advanced statistical tools, which can unveil cause-effect relationships between pressure from surface waters, released contaminants, and damage to the ecological status. In this study, two partial least squares-path models (PLS-PM) were created and analyzed in order to understand how the cause-effect relationships can change over two seasons (summer and winter) and how the used scale (short or long) can affect the results. During the summer of 2016 and winter of 2017 surface water parameters and the North Invertebrate Portuguese Index were measured in strategic sampling sites. For each site, it two sections were delineated: the total upstream drainage area (long scale) and 250 m (short scale). For each section, data of pressures in surface waters including point source, diffuse emissions and landscape metrics were gathered. The methodology was applied to the Sabor River Basin, located in the northeast of Portugal. In this study, it was possible to determine in which season pressures affect ecological integrity and also which scale should be addressed. The models showed the influences of manganese and of potassium concentrations in stream water on the decrease in summer water quality, while arsenic’s harmful effect occurs during winter. Pastures and environmental land use conflicts were considered threats to water quality when analyzed on a long scale, whereas agricultural areas played a role when the short scale was used. The effect of landscape edge density revealed to be independent of scale or season. Effluent discharges in surface water affected the water quality during the summer season, while the effect of discharges in groundwater affected the water quality in winter. It has also been found that, to find the harmful effect of pressures, it is necessary to approach different scales and that the role of landscape metrics can also overlap contaminant sources.

A structural equation model to predict macroinvertebrate-based ecological status in catchments influenced by anthropogenic pressures

A Partial Least Squares-Path Model (PLS-PM) was developed for the Ave River Basin (North of Portugal), and the results used in a scenario analysis. The data for PLS-PM comprised a set of anthropogenic pressures, water quality parameters, and a macroinvertebrate-based biodiversity index (IPtI_N) used to assess the ecological status of streams. These groups of measured parameters (called latent variables) were given the names "Pressures", "Contamination" and "Ecological Integrity". Besides, latent variables were connected through path coefficients representing potential causal effects among them. In a large portion of Ave the ecological status of streams is currently bad or poor. Nitrate and coliforms were the most weighted measured variables of latent variable "Contamination", with w ≈ 0.7 and w ≈ 0.2, respectively. The highest "Pressures" weights were ascribed to livestock farming (0.7) and population density (0.4). The connections "Pressures"-"Contamination" and "Contamination" - "Ecological Integrity" exposed a sequence of direct negative effects between the three variables, expressed in the corresponding path coefficients (pc = 0.87 and pc = -1.11). Paradoxically, a direct negative effect of "Pressures" over "Ecological Integrity" was absent (pc = 0.29). Therefore, the poor ecological status of local stream waters might not be directly related to the presence of potentially threatening contaminant sources (the "Pressures"), but to ineffective monitoring of livestock farming and wastewater treatment activities that potentiate (accidental) releases of contaminants into the streams. The lack of a direct link "Pressures" - "Ecological Integrity" supported the results of pressure change versus IPtI_N change scenarios. Regardless of some significant reductions of anthropogenic activity and population density until 2027, announced by the Portuguese Environmental Agency, the scenarios could not predict improvement of ecological status beyond the "moderate" category. The study recommendations were therefore to prevent contamination through proper implementation and monitoring of existing watershed management plans. The adequate treatment of domestic effluents and the control of livestock farming residues are urgent.

A Regression Model of Stream Water Quality Based on Interactions between Landscape Composition and Riparian Buffer Width in Small Catchments

Riparian vegetation represents a protective barrier between human activities installed in catchments and capable of generating and exporting large amounts of contaminants, and stream water that is expected to keep quality overtime. This study explored the combined effect of landscape composition and buffer strip width (L) on stream water quality. The landscape composition was assessed by the forest (F) to agriculture (A) ratio (F/A), and the water quality by an index (IWQ) expressed as a function of physico-chemical parameters. The combined effect (F/A × L) was quantified by a multiple regression model with an interaction term. The study was carried out in eight catchments of Uberaba River Basin Environmental Protection Area, located in the state of Minas Gerais, Brazil, and characterized by very different F/A and L values. The results related to improved water quality (larger IWQ values) with increasing values of F/A and L, which were not surprising given the abundant similar reports widespread in the scientific literature. But the effect of F/A × L on IWQ was enlightening. The interaction between F/A and L reduced the range of L values required to sustain IWQ at a fair level by some 40%, which is remarkable. The interaction was related to the spatial distribution of infiltration capacity within the studied catchments. The high F/A catchments should comprise a larger number of infiltration patches, allowing a dominance of subsurface flow widespread within the soil layer, a condition that improves the probability of soil water to cross and interact with a buffer strip before reaching the stream. Conversely, the low F/A catchments are prone to the generation of an overland flow network, because the absence of permanent vegetation substantially reduces the number of infiltration patches. The overland flow network channelizes runoff and conveys the surface water into specific confluence points within the stream, reducing or even hampering an interaction with a buffer strip. Notwithstanding the interaction, the calculated L ranges (45–175 m) are much larger than the maximum width imposed by the Brazilian Forest Code (30 m), a result that deserves reflection.

Conjunctive Water Resources Management in Densely Urbanized Karst Areas: A Study in the Sete Lagoas Region, State of Minas Gerais, Brazil

Headwater catchments store valuable resources of quality water, but their hydraulic response is difficult to assess (model) because they are usually deprived of monitoring stations, namely hydrometric stations. This issue becomes even more pertinent because headwater catchments are ideal for the practice of conjunctive water resources management involving the supply of towns with groundwater and surface water, a solution that can be used to mitigate overexploitation of groundwater resources in densely urbanized and populated areas. In this study, a stepwise approach is presented whereby, in a first stage, a gauged basin was modeled for stream flow using the JAMS J2000 framework, with the purpose to obtain calibrated hydraulic parameters and ecological simulated stream flow records. Having validated the model through a comparison of simulated and measured flows, the simulated record was adjusted to the scale of an ungauged sub-basin, based on a new run of JAMS J2000 using the same hydraulic parameters. At this stage, a second validation of modeled data was accomplished through comparison of the downscaled flow rates with discharge rates assessed by field measurements of flow velocity and water column height. The modeled basin was a portion of Jequitiba River basin, while the enclosed sub-basin was the Marinheiro catchment (state of Minas Gerais, Brazil). The latter is a peri-urban watershed located in the vicinity of Sete Lagoas town, a densely urbanized and populated area. This town uses 15.5 hm3 year−1 of karst groundwater for public water supply, but the renewable resources were estimated to be 6.3 hm3 year−1. The impairment between abstraction and renewable resources lasts for decades, and for that reason the town experiences systemic water table declines and sinkhole development. The present study claims that the storage of quality water in the Marinheiro catchment, in a dam reservoir, would help alleviate the depletion of groundwater resources in the karst aquifer because this catchment could deliver 4.73 hm3 year−1 of quality surface water to the municipality without endangering ecologic flows. The construction of a small dam at the outlet of Marinheiro catchment could also improve aquifer recharge. Presently, the annual recharge in this catchment approaches 1.47 hm3 but could be much larger if the small dam was installed in the water course and the captured stream water managed properly.

Hydrologic Impacts of Land Use Changes in the Sabor River Basin: A Historical View and Future Perspectives

The study area used for this study was the Sabor river basin (located in the Northeast of Portugal), which is composed mostly for agroforestry. The objectives were to analyze the spatiotemporal dynamics of hydrological services that occurred due to land use changes between 1990 and 2008 and to consider two scenarios for the year 2045. The scenarios were, firstly, afforestation projection, proposed by the Regional Plan for Forest Management, and secondly, wildfires that will affect 32% of the basin area. In this work, SWAT (Soil and Water Assessment Tool) was used to simulate the provision of hydrological services, namely water quantity, being calibrated for daily discharge. The calibration and validation showed a good agreement for discharge with coefficients of determination of 0.63 and 0.8 respectively. The land use changes and the afforestation scenario showed decreases in water yield, surface flow, and groundwater flow and increases in evapotranspiration and lateral flow. The wildfire scenario, contrary to the afforestation scenario, showed an increase in surface flow and a decrease in lateral flow. The Land Use and Land Cover (LULC) changes in 2000 and 2006 showed average decreases in the water yield of 91 and 52 mm·year−1, respectively. The decrease in water yield was greater in the afforestation scenario than in the wildfires scenario mainly in winter months. In the afforestation scenario, the large decrease varied between 28 hm3·year−1 in October and 62 hm3·year−1 in January, while in the wildfires scenario, the decrease was somewhat smaller, varying between 15 hm3·year−1 in October and 49 hm3·year−1 in January.

The Potential of Small Dams for Conjunctive Water Management in Rural Municipalities

The drinking water supply to Vila Pouca de Aguiar municipality in North Portugal is based on high quality groundwater, namely on nearly one hundred artesian springs and fifty boreholes. The groundwater resources are plentiful on a municipal level, but evidence some deficits at the sub-municipal (village) level, especially during the dry period (July- August) that coincides with the return of many emigrants for holiday time. The deficits affect mostly the municipal capital (Vila Pouca de Aguiar) and a neighboring village (Pedras Salgadas), which populations nearly double or even triple during that period. The estimated annual deficits approach 55,000 m³/yr in those villages. If the anticipated increase in consumption/habitant and decrease in annual rainfall become reality in the next two decades, then the deficits may raise to approximately 90,000 m³/yr. To balance the water supply system, this study proposes its transition towards a conjunctive water management based on surface water stored in small dams and groundwater. A hydrologic modeling involving small forested catchments (< 15 km²) elected the Cabouço watershed as most suited basin to store stream water, because surface water availability is large (2.4 Mm³/yr) and forest cover is dominant (84.8%). Estimated nutrient loads are also compatible with drinking water supply.

Undamming the Douro River Catchment: A Stepwise Approach for Prioritizing Dam Removal

Dams provide water supply, flood protection, and hydropower generation benefits, but also harm native species by altering the natural flow regime, and degrading the aquatic and riparian habitats. In the present study, which comprised the Douro River basin located in the North of Portugal, the cost-benefit assessment of dams was based upon a balance between the touristic benefits of a dammed Douro, and the ecological benefits of less fragmented Douro sub-catchments. Focused on four sub-catchments (Sabor, Tâmega, Côa and Corgo), a probabilistic stream connectivity model was developed and implemented to recommend priorities for dam removal, where this action could significantly improve the movement of potadromous fish species along the local streams. The proposed model accounts for fish movement across the dam or weir (permeability), which is a novel issue in connectivity models. However, before any final recommendation on the fate of a dam or weir, the connectivity results will be balanced with other important socio-economic interests. While implementing the connectivity model, an inventory of barriers (dams and weirs) was accomplished through an observation of satellite images. Besides identification and location of any obstacles, the inventory comprised the compilation of data on surrounding land use, reservoir water use, characteristics of the riparian gallery, and permeability conditions for fish, among others. All this information was stored in a geospatial dataset that also included geographical information on the sub-catchment drainage network. The linear (drainage network) and point (barriers) source data were processed in a computer program that provided or returned numbers for inter-barrier stream lengths (habitat), and the barrier permeability. These numbers were finally used in the same computer program to calculate a habitat connector index, and a link improvement index, used to prioritize dam removal based upon structural connectivity criteria. The results showed that habitat patch connectivity in the Sabor, Tâmega and Côa sub-catchments is not dramatically affected by the installed obstacles, because most link improvement values were generally low. For the opposite reason, in the Corgo sub-catchment, obstacles may constitute a relatively higher limitation to connectivity, and in this case the removal of eight obstacles could significantly improve this connectivity. Using the probabilistic model of structural connectivity, it was possible to elaborate a preliminary selection of dams/weirs that critically limit stream connectivity, and that will be the focus of field hydraulic characterization to precisely determine fish movement along the associated river stretches. Future work will also include the implementation of a multi-criteria decision support system for dam removal or mitigation of the critical structures, as well to define exclusion areas for additional obstacles.

Can Land Cover Changes Mitigate Large Floods? A Reflection Based on Partial Least Squares-Path Modeling

Common approaches to large flood management are Natural Water Retention Measures and detention basins. In this study, a Partial Least Squares-Path Model (PLS-PM) was defined to set up a relationship between dam wall heights and biophysical parameters, in critical flood risk zones of continental Portugal. The purpose was to verify if the heights responded to changes in the biophysical variables, and in those cases to forecast landscape changes capable to reduce the heights towards sustainable values (e.g., <8 m). The biophysical parameters comprised a diversity of watershed characteristics, such as land use and geology, surface runoff, climate indicators and the dam heights. The results have shown that terrain slope (w > 0.5), rainfall (w > 0.4) and sedimentary rocks (w > 0.5) are among the most important variables in the model. Changes in these parameters would trigger visible changes in the dam wall height, but they are not easily or rapidly modified by human activity. On the other hand, the parameters forest occupation and runoff coefficient seem to play a less prominent role in the model (w < 0.1), even though they can be significantly modified by human intervention. Consequently, in a scenario of land cover change where forest occupation is increased by 30% and impermeable surfaces are decreased by 30%, interferences in the dam heights were small. These results open a discussion about the feasibility to mitigate large floods using non-structural measures such as reforestation.

The Buffer Capacity of Riparian Vegetation to Control Water Quality in Anthropogenic Catchments from a Legally Protected Area: A Critical View over the Brazilian New Forest Code

The riparian buffer width on watersheds has been modified over the last decades. The human settlements heavily used and have significantly altered those areas, for farming, urbanization, recreation and other functions. In order to protect freshwater ecosystems, riparian areas have recently assumed world recognition and considered valuable areas for the conservation of nature and biodiversity, protected by forest laws and policies as permanent preservation areas. The objective of this work was to compare parameters from riparian areas related to a natural watercourse less than 10 m wide, for specific purposes in Law No. 4761/65, now revoked and replaced by Law No. 12651/12, known as the New Forest Code. The effects of 15, 30 and 50 m wide riparian forest in water and soil of three headwater catchments used for sugar cane production were analyzed. The catchments are located in the Environmental Protection Area of Uberaba River Basin (state of Minas Gerais, Brazil), legally protected for conservation of water resources and native vegetation. A field survey was carried out in the catchments for verification of land uses, while periodical campaigns were conducted for monthly water sampling and seasonal soil sampling within the studied riparian buffers. The physico-chemical parameters of water were handled by ANOVA (Tukey’s mean test) for recognition of differences among catchments, while thematic maps were elaborated in a geographic information system for illustration purposes. The results suggested that the 10, 30 or even 50 m wide riparian buffers are not able to fulfill the environmental function of preserving water resources, and therefore are incapable to ensure the well-being of human populations. Therefore, the limits imposed by the actual Brazilian Forest Code should be enlarged substantially.

Evaluation of watershed health using Fuzzy-ANP approach considering geo-environmental and topo-hydrological criteria

Assessment of watershed health and prioritization of sub-watersheds are needed to allocate natural resources and efficiently manage watersheds. Characterization of health and spatial prioritization of sub-watersheds in data scarce regions helps better comprehend real watershed conditions and design and implement management strategies. Previous studies on the assessment of health and prioritization of sub-watersheds in ungauged regions have not considered environmental factors and their inter-relationship. In this regard, fuzzy logic theory can be employed to improve the assessment of watershed health. The present study considered a combination of climate vulnerability (Climate Water Balance), relative erosion rate of surficial rocks, slope weighted K-factor, topographic indices, thirteen morphometric characteristics (linear, areal, and relief aspects), and potential non-point source pollution to assess watershed health, using a new framework which considers the complex linkage between human activities and natural resources. The new framework, focusing on watershed health score (WHS), was employed for the spatial prioritization of 31 sub-watersheds in the Khoy watershed, West Azerbaijan Province, Iran. In this framework, an analytical network process (ANP) and fuzzy theory were used to investigate the inter-relationships between the above mentioned geo-environmental factors and to classify and rank the health of each sub-watershed in four classes. Results demonstrated that only one sub-watershed (C15) fell into the class that was defined as 'a potentially critical zone'. This article provides a new framework and practical recommendations for watershed management agencies with a high level of assurance when there is a lack of reliable hydrometric gauge data.

Preservation of wild bird species in northern Portugal - Effects of anthropogenic pressures in wild bird populations (2008-2017)

In this study we aim to obtain a holistic view over the consequences of human-induced threats to the wild bird populations in the study area, based on data collected from a Wildlife Rehabilitation Centre (WRC) through the method of Partial Least Squares-Path Modelling (PLS-PM). The study area comprised 76 rural and urban municipalities located in northern Portugal. Within PLS-PM the threats ("anthropogenic pressures") are termed exogenous latent variables, while the final environmental consequence (wild bird mortality) is termed endogenous latent variable. Latent variables are concepts assessed by numerical parameters. The PLS-PM results identified as most significant pressures, the number of small and medium companies in the municipalities, both in traumatic and non-traumatic deaths. Although the pattern of weights is similar regardless of the general cause of death, traumatic causes seem to play a more prominent role given the larger weights in the relevant specific causes (number of companies). The high coefficients of determination (R² > 0,8) reveal that the variance of wild bird mortality is largely explained by the variance of the pressures, which indicates a cause-effect relationship between the independent (pressures) and dependent (mortality) variables. The ample coverage of northern Portugal with a huge dataset suggests that this cause-effect relationship is typical from this region. The use of a sophisticated statistical method PLS-PM and its incorporation into a Geographic Information System (GIS) revealed to be an important tool for analysing wildlife impacts of environmental and human factors. The results obtained with this model indicate that there is a substantial negative impact of human activity on wild bird mortality.