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

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.

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.

Modeling the effect of improved sewage disposal rates on ecological status for aquatic organisms in Japan

Improving sewage disposal rates is an important policy for maintaining the health of aquatic organisms in river environments. In Japan, the rate is not yet 100 %. Two measures are necessary to eliminate the discharge of untreated greywater: (1) increase the number of households connected to sewage lines in areas with sewage systems, and (2) replace single-type household onsite wastewater treatment systems (OWTSs) with combined-type systems. To estimate the effect of improving the disposal rate on river water quality, we developed a hydrology-based organic pollution assessment model with a gridded spatial resolution of 250 m to estimate the biochemical oxygen demand (BOD) in rivers in Gunma Prefecture, Japan. We considered three scenarios based on the sewage disposal rate of 70.5 % in 2015. In Scenario A, the disposal rate is increased to 75.2 % in 2030 by increasing the connection rate to sewage lines. In Scenario B, the rate is increased to 88.2 % in 2030 through additional progress in converting from single-to combined-type OWTSs. In Scenario C, the rate reaches 100 % by 2040. The ecological status of rivers was evaluated using taxon richness of Ephemeroptera, Plecoptera, and Trichoptera estimated from its reported relationship to BOD. The number of sites in Gunma Prefecture polluted by organic waste classified as III (poor) and IV (very poor) was estimated to be 1610 under the present state (2015) and decreased to 1212 (25 % reduction) in Scenario A, 619 (62 % reduction) in Scenario B, and 50 (97 % reduction) in Scenario C, with the improvements mainly in small branch rivers. The effects of improved disposal rates were mainly evident in areas with relative high population densities using single-type OWTSs outside of areas with a sewage system, and measures taken in these areas were shown to be effective.

Hydrogeochemical and multivariate statistical approaches to investigate the characteristics of groundwater quality in fluoride-enriched hard rock region in Tirupathur district of Tamil Nadu, India

Fluoride pollution is a major issue worldwide, posing health risks such as dental and skeletal fluorosis. This study was conducted in fluoride enrichment hard rock regions of Vaniyambadi and Ambur talks in Tirupathur district, Tamil Nadu. Four hundred eighty groundwater samples were collected from May 2021 to April 2022 and grouped as summer, southwest monsoon (SWM), northeast monsoon (NEM), and winter. Maximum concentration of fluoride was found to be 4 mg/L in the summer season in Vellakuttai region of Vaniyambadi taluk. The study aims to investigate the hydrogeochemical process and mechanism influencing groundwater chemistry and it also provides the confirmation of exploratory data analysis in groundwater quality using structural equation modeling. The Piper and Gibbs diagrams illustrate the rock-water interaction and anthropogenic sources that contribute to the NaHCO3 and NaCl-type waters, respectively. Multivariate statistical analysis such as hierarchical cluster analysis (HCA), principal component analysis (PCA), multiple linear regression (MLR), and structural equation modeling (SEM) has been carried out to determine the groundwater quality. HCA manifests the nature and sources of groundwater, whereas PCA divides all the physicochemical parameters into two PC loadings, accounting for 97.46%, 99.46%, 99.18%, and 98.93% of cumulative % of variance during the summer, SWM, NEM, and winter seasons, respectively. PC1 has a higher loading factor to Cl, Ca, and Mg, whereas PC2 has a higher loading factor to Na, HCO3, SO4, and NO3. The results of the MLR model provide higher accuracy in detecting the contamination factors associated with the environment and natural rocks. SEM revealed the goodness-of-fit indices 0.993, 0.999, 1.000, and 0.999 in summer, SWM, NEM, and winter, respectively. Hence, this study provides insight view of variation of fluoride concentration in groundwater in different seasons and also mentions the factors that influence fluoride concentration in Vaniyambadi and Ambur taluk.

Identification and restoration of hydrological processes alteration during the fish spawning period

The hydrological processes play an important role in stimulating fish spawning behavior. Changes in the natural hydrological processes will alter the populations and distribution of fish, which may have a negative impact on the native aquatic organisms. The aim of this study is to identify the alteration of the water rising process during the fish spawning period and to construct an ecological flow optimization model to restore the water rising conditions for fish reproduction. The Mann-Kendall test and the sliding t-test were used to detect the mutation year of the mean daily flow data sets in the fish spawning period in each monitoring year. Then the data sets can be divided into pre-altered and post-altered periods. The water rising process was characterized by the water rising processes count, the duration, the daily flow increase rate, the date of the water rising process, and the initial water rising flow. The changes in hydrological processes in the middle reaches of the Yangtze River were investigated by comparing the post-altered and pre-altered characteristic parameters. Furthermore, we integrated the statistical values of the five characteristic parameters in pre-altered into an ecological flow optimization model to simulate the natural water rising processes for the spawning of the Four Major Chinese Carps (FMCC) and Chinese Sturgeon (CS). The analysis showed that after the hydrological mutation year, the duration and the initial water rising flow in the FMCC spawning season were increased, with hydrological alteration degrees of 63.10% and 70.16%, respectively; however, the daily flow increase rate was significantly decreased, with hydrological alteration of 86.50%. During the CS spawning season, the water rising processes count and the initial water rising flow were dramatically altered parameters, with hydrological alteration degrees of 50.86% and 83.27%, respectively. The former parameter increased, but the latter decreased significantly in the post-altered period. To induce the spawning activity of FMCC and CS, appropriate ecological flows and hydrological parameters were proposed. These results showed that during the spawning seasons of FMCC and CS, the hydrological processes of the middle reaches of the Yangtze River changed significantly. Therefore, ecological flow must be ensured through ecological operation of upstream reservoirs to provide suitable spawning conditions in target fish spawning grounds.

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.

Water Quality Predictions Through Linear Regression - A Brute Force Algorithm Approach

Linear regression is one of the oldest statistical modeling approaches. Still, it is a valuable tool, particularly when it is necessary to create forecast models with low sample sizes. When researchers use this method and have numerous potential regressors, choosing the group of regressors for a model that fulfills all the required assumptions can be challenging. In this sense, the authors developed an open-source Python script that automatically tests all the combinations of regressors under a brute-force approach. The output displays the best linear regression models, regarding the thresholds set by users for the required assumptions: statistical significance of the estimations, multicollinearity, error normality, and homoscedasticity. Further, the script allows the selection of linear regressions with regression coefficients according to the user's expectations. This script was tested with an environmental dataset to predict surface water quality parameters based on landscape metrics and contaminant loads. Among millions of possible combinations, less than 0.1 % of the regressor combinations fulfilled the requirements. The resulting combinations were also tested in geographically weighted regression, with similar results to linear regression. The model's performance was higher for pH and total nitrate and lower for total alkalinity and electrical conductivity.•A Python script was developed to find the best linear regressions within a dataset.•Output regressions are automatically selected based on regression coefficient expectations set by the user and the linear regression assumptions.•The algorithm was successfully validated through an environmental dataset.

Co-driving factors of tidal effect on the abundance and distribution of antibiotic resistance genes in the Yongjiang Estuary, China

The unreasonable use of antibiotics and the transmission of antibiotic resistance genes (ARGs) induced by antibiotics have led to a large number of ARGs entered the water environment, which seriously threatened human health and environmental safety. The estuarine aquatic environment connects with inland rivers and sea and is frequently influenced by human activities. This study aims to reveal the occurrences and abundances of ARGs and bacterial community composition by high-throughput quantitative PCR including 296 primers and high-throughput sequencing in the tide rising and ebbing of surface water in the Yongjiang Estuary, China. The results showed that there were a large number of ARGs and mobile genetic elements (MGEs) detected in the rising tide and ebb tide water bodies. The numbers of detected ARGs in each sample at rising and ebb tide ranged from 16 to 77 and 61 to 88, respectively, and the absolute abundance ranges were 1.69 × 10⁴-1.69 × 10⁹ copies/L and 3.18 × 10³-2.57 × 10⁹ copies/L, respectively. Obvious tidal distribution characteristics of ARGs were showed. Most of ARGs conferred resistance to multidrug, aminoglycosides and sulfanilamides. Proteobacteria, Actinobacteria and Bacteroidetes were the dominantly bacterial phylum in the Yongjiang Estuary. Network analysis results indicated that multi-genera were identified as possible ARGs hosts, and they carried more than two types of ARGs genes. Partial least squares path modeling further revealed that MGEs and bacterial community composition were the most important driving factors. The results of the study can provide the corresponding scientific basis for the diffusion and control of ARGs in estuaries.

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.

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.

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.

Effects of different types of land-use on taxonomic and functional diversity of benthic macroinvertebrates in a subtropical river network

Expansion of agricultural and urban areas and intensification of catchment land-use increasingly affect different facets of biodiversity in aquatic communities. However, understanding the responses of taxonomic and functional diversity to specific conversion from natural forest to agriculture and urban land-use remains limited, especially in subtropical streams where biomonitoring programs and using functional traits are still under development. Here, we conducted research in a subtropical stream network to examine the responses of macroinvertebrate taxonomic and functional diversity to different types of land-use in central China. Our results showed that medium body size, univoltine, gill respiration, and slow seasonal development were much higher in natural forest sites, while certain traits related to strong resilience and resistance (e.g., small body size, fast seasonal development, bi-or multivoltine, abundant occurrence in drift, sprawler) dominated in high-intensity agriculture and urbanization sites. We further found that land-use compromised water quality (e.g., increases in total phosphate, conductivity and water temperature) and habitat conditions (e.g., high proportion of sand and silt, gravel, and channel width) accounted for the changes in trait composition based on a combination of RLQ and fourth-corner analysis. Moreover, natural forest sites presented relatively high values of functional richness than other land-use, demonstrating the importance of natural forest maintenance to promote high levels of functional diversity. However, taxonomic diversity indexes showed higher sensitivity to distinguish different types of land-use compared to functional diversity measures. Even so, given that certain trait categories showed significant relationships with specific local environmental stressors, trait-based approaches can provide reliable evidence to diagnose the cause of impairment and complement the results of the taxonomic-based approaches. Our findings support the idea that taxonomic and functional approaches should be integrated in river restoration and land-use management.

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.

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 [...]

Mixing data for multivariate statistical study of groundwater quality

In the present paper, a multivariate statistical modeling study of water quality data from different places of Kozhikode Gity, Kerala, India, has been conducted applying multiple linear regression (MLR), structural equation modeling (SEM), and adaptive neuro-fuzzy inference system (ANFIS) modeling. First, we combined water quality data from different places in the study area over different time periods to obtain a unified multiple linear regression (MLR) model. By mixing three data sets from different places and time periods in four different ways, different regression models were formed with total dissolved solids (TDS) as the dependent variable and calcium, magnesium, nitrate, sodium, chloride, potassium, total hardness, and sulfate as independent variables. The effectiveness of each model was then tested against a data set, which corresponded to a different period and location. One unmixed model and three mixed models showed similar performance. An SEM was developed for the data set, which is obtained by mixing all the three data sets. The same regression coefficients are found for the SEM and the corresponding MLR. An improvement in the sample size as a result of mixing of data sets could be thought of as the reason for this phenomenon. We thus selected the MLR obtained by mixing all three data sets as our unified model. For the mixed data set, we then developed an ANFIS model with calcium, magnesium, nitrate, sodium, chloride, potassium, total hardness, and sulfate as input variables and TDS as the output variable. On the external data set, the ANFIS model showed a better performance than the MLR model.

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).

Population dynamics of small endotherms under global change: Greater white-toothed shrews Crocidura russula in Mediterranean habitats

Small endotherms would be especially exposed to main global change drivers (habitat and climate changes) but would also be able to withstand them by adjusting population dynamics locally to changing climate- and habitat-driven food and predation conditions. We analyse the relative importance of changes in climate (mean and variability, including relevant time-lags) and habitat conditions on the abundance, age structure and growth rate of Mediterranean populations of a small endotherm, the greater white-toothed shrew Crocidura russula, along a 10-year period (2008-2017). Habitat type and season were the key factors shaping shrew population dynamics, which showed consistent peak numbers in open habitats in autumn, after the spring-summer reproductive period. Significant increases in aridity (increasing temperature and decreasing rainfall) along the study period did not explain variation in shrew numbers, although short-term variations in abundance were negatively related to relative air humidity and temperature over three last months prior to the surveys. Overall, ongoing climate change have not yet affected shrew population dynamics in its core areas of the Mediterranean region, in spite of expectations based on climate change rate in this region and small endotherm sensitivity to these changes. Reliance on open habitats with lower predation pressure would explain the resilience of shrew populations to climate change. However, current trends of land use change (land abandonment and afforestation) threaten Mediterranean open habitats, so that resilience would not last for long if these trends are not counteracted.

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.

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.