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The study of land subsidence has recently been expanded due to its increased occurrence and magnitude worldwide. This paper develops and applies an optimal control model of groundwater extractions under conditions of land subsidence. We include, in a traditional groundwater management model, two types of negative externalities associated with land subsidence: damage to infrastructure and to economic activities, and the loss of aquifer storage capacity. Using a two-stage optimal control method, characterized by two sub-problems corresponding to the phase before and after the occurrence of subsidence, we find the economically sustainable paths of groundwater extractions and water table levels under the existence of land subsidence impacts. The theoretical results indicate that the presence of land subsidence dictates the optimal paths of groundwater withdrawals and water table levels. The model has been applied to the Alto Guadalentín over-exploited aquifer system in the Segura River Basin of Spain. The empirical outcomes indicate that by following the optimal paths, groundwater extractions should be curtailing to avoid reaching the critical water level at which subsidence takes place. Results suggest that regional net present value of welfare over the planning period, under the two land subsidence scenarios, is reduced by nearly 1–5%, compared to the no land subsidence scenario. Furthermore, under subsidence, even with relatively small impacts of both types of externalities, groundwater optimal extractions are kept at levels that avoid these externalities. These outcomes clearly call for government intervention in order to reduce groundwater withdrawals in aquifers with propensity to face undesirable subsidence effects. • LS due to aquifers overused causes major social costs with irreversible impacts. • LS has not received proper attention by regulators and the economic damages are not accurately assessed. • This paper develops a groundwater optimization model including negative externalities of LS. • In presence of subsidence, even with small impacts, groundwater management is necessary. • The results call for government intervention to curtail groundwater withdrawals to face LS. [ABSTRACT FROM AUTHOR]

The presence of trace elements in water for domestic supply or irrigation could pose a significant toxic risk for health, due to direct consumption or bioaccumulation through the ingestion of vegetables irrigated with this water. This paper studies the presence of 41 trace elements plus nitrate and bromate in groundwater, using a multivariate statistical tool based on Principal Component Analysis and a geostatistical Kriging method to map the results. Principal Component Analysis revealed 11 significant principal components, which account for 82% and 81% of the total variance (information) respectively for the two dates analysed. Ordinary Kriging was applied to draw maps of the trace elements and PC scores. This research breaks new ground in terms of the large number of parameters used and in terms of the analysis of spatiotemporal variations in these parameters. The results obtained indicate that PC1 represents the natural quality of the aquifer (geogenic) and that there is little change in the average PC1 value between the two dates studied (June near the peak recharge point and November at the end of summer). Agriculture is the human activity that causes the greatest variations in the quality of the groundwater due to the use of fertilizers and due to watering crops with wastewater (PC7_J and PC5_N, June and November, respectively). Other elements of industrial origin, which are dangerous for human health, such as Pb, Cu and Cd, are grouped together in other principal components. The results show that the decline, or even complete absence, of natural recharge during the summer months leads to an increase in the TEs produced by human activity. This indicates that a temporary reduction in the natural recharge could worsen the quality of water resources. Based on the interpretation of the estimated maps, a synthetic map was created to show the spatial distribution of the areas affected by geogenic and anthropogenic factors. Studies with a global approach like this one are necessary in that the possible sources of pollution that could alter the quality of the groundwater and the amount of trace elements and other potentially harmful substances could increase as time goes by. The main advantage of the methodology proposed here is that it reduces the number of parameters, so simplifying the results. This makes it easier to interpret the results and manage the quality of the water. • PCA and geostatistical methods were used to establish the spatiotemporal variations in 41 trace elements. • A complex spatial relationship between anthropogenic and geogenic activities was reduced to just six categories. • The anthropogenic activity with the greatest impact on groundwater quality is agriculture. • Evaporitic rocks were the main cause of geogenic contamination of the groundwater. [ABSTRACT FROM AUTHOR]

In wastewater treatment plants (WWTPs), the stochastic nature of influent wastewater and operational and weather conditions cause fluctuations in effluent quality. Data-driven models can forecast effluent quality a few hours ahead as a response to the influent characteristics, providing enough time to adjust system operations and avoid undesired consequences. However, existing data for training models are often incomplete and contain missing values. On the other hand, collecting additional data by installing new sensors is costly. The trade-off between using existing incomplete data and collecting costly new data results in three data challenges faced when developing data-driven WWTP effluent forecasters. These challenges are to determine important variables to be measured, the minimum number of required data instances, and the maximum percentage of tolerable missing values that do not impede the development of an accurate model. As these issues are not discussed in previous studies, in this research, for the first time, a comprehensive analysis is done to provide answers to these challenges. Another issue that arises in all data-driven modeling is how to select an appropriate forecasting model. This paper addresses these issues by first testing nine machine learning models on data collected from three wastewater treatment plants located in Iran, Australia, and Spain. The most accurate forecaster, Bayesian network, was then used to address the articulated challenges. Key variables in forecasting effluent characteristics were flow rate, total suspended solids, electrical conductivity, phosphorus compounds, wastewater temperature, and air temperature. A minimum of 250 samples was needed during the model training to achieve a great reduction in the forecasting error. Moreover, a steep increase in the error was observed should the portion of missing values exceed 10%. The results assist plant managers in estimating the necessary data collection effort to obtain an accurate forecaster, contributing to the quality of the effluent. [Display omitted] • Bayesian network is benchmarked against eight AI models to predict wastewater quality. • Bayesian networks can handle missing value in input data due to probabilistic nature. • Key variables in WWTP quality and quantity were specified. • Input data quality has a huge role in successful development of data-driven models. • The prediction error sharply increases when the portion of missing data exceeds 10%. [ABSTRACT FROM AUTHOR]

Climate change has intensified the effects of habitat fragmentation in many ecosystems, particularly exacerbated in riparian habitats. Therefore, there is an urgent need to identify keystone connectivity spots to ensure long-term conservation and sustainable management of riparian systems as they play a crucial role for landscape connectivity. This paper aims to identify critical areas for connectivity under two contrasting climate change scenarios (RCP 4.5 and RCP 8.5 models) for the years 2030, 2050 and 2100 and to group these critical areas by similar connectivity in keystone spots for sustainable management. A set of analyses comprising climate analysis, drainage network analysis, configuration of potential riparian habitats, riparian habitat connectivity, data clustering, and statistical analysis within a Spanish river basin (NW Spain) were applied. The node and link connectivity would be reduced under the two climate change scenarios (≈2.5 % and 4.4 % reduction, respectively), intensifying riparian habitat fragmentation. Furthermore, 51 different clusters (critical areas) were obtained and classified in five classes (keystone spots) with similar connectivity across the different scenarios of climate change. Each keystone spot obtained by hierarchical classification was associated with one or more climate scenarios. One of these keystone spots was especially susceptible to the worst climate change scenario. Key riparian connectivity spots will be crucial for the management and restoration of highly threatened riparian systems and to ensure long-term biodiversity conservation. • Connectivity importance was reduced under different climate change scenarios. • Critical area detection for connectivity conservation is threatened by climate change. • Critical areas were classified with similar connectivity keystone spots against climate change. • Keystone spots with high PC index will be priority for conservation management. [ABSTRACT FROM AUTHOR]

Nitrate pollution in aquifers is a global concern. Spain has developed a national strategy to recover nitrate polluted aquifers aligned with the European Union (EU) policies, specifically through the water planning under the EU Water Framework Directive. River basin management plans use PATRICAL model results to define the maximum nitrogen surplus in each polluted aquifer for the first time. The maximum nitrogen surplus allows to reach the good status in each aquifer and the model provides the number of years required. Around 30% of the aquifers in Spain is currently heavily polluted by nitrates. Model results show that 90% of these aquifers can be recovered in next 6-12 years by increasing nitrogen use efficiency and reducing nitrogen losses around 50%, which is in line with the EU Farm to Fork Strategy. The remaining aquifers require additional reductions to achieve the good status. In Spain this increase in nitrogen efficiency can be obtained with different measures including 30% reduction of current fertilization., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Miguel Angel Perez Martin reports financial support was provided by Government of Spain Ecological Transition Ministry. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The latest report on the state of nature in Europe (2013-2018) shows that biodiversity is declining at an alarming rate, with most protected species and habitats in poor condition. Despite an increasing volume of collected biodiversity information, urgent action is needed to integrate biodiversity data and knowledge to improve conservation efforts. We conducted a study in Catalonia (NE Spain), where we collected management measures implemented between 2013 and 2018, including allocation, budget, pressures aimed, and habitats/species potentially benefiting. We integrated information on pressures and habitats/species with the measures to identify non-spatial management gaps. Then, we integrated the spatially explicit information to determine the spatial management gap, identifying geographical areas where species/habitats are under pressure without registered measures. We demonstrated the importance of integrating existing information. Our findings revealed that resources were often not distributed adequately across species/habitats, with biases towards certain taxa being a common issue. The non-spatial management gap analysis identified taxonomic groups, especially plants and mollusks with the wider management gaps. We also identified threatened areas, especially in the northeast of the region with the larger spatial management gaps. These results could guide priority objectives to optimize conservation efforts. Integrating different information sources provided a broader view of the challenges that conservation science is facing nowadays. Our study offers a path toward bending the curve of biodiversity loss by providing an integrative framework that could optimize the use of the available information and help narrow the knowing-doing gap. In the context of the EU, this example demonstrates how information can be used to promote some environmental policy instruments, such as the Prioritized Action Frameworks (PAFs). Additionally, our findings highlight the importance of supporting decision-making with systematic assessments to identify deficiencies in the conservation process, reduce the loss of critical ecosystems and species, and avoid biases among taxa., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Traditional management practices, such as grazing, can have adverse impact on soils. Despite an extensive body of literature exploring the effects of grazing on soil and plants worldwide, there is a notable lack of research on its impacts in Mediterranean forests within the Iberian Peninsula Furthermore, there is a knowledge gap on the enzymatic activities and basal respiration of soil in forest after grazing. To address these gaps, this study aimed to investigate the impact of grazing on various important physicochemical and biological soil properties along with vegetation richness in a Mediterranean forest located in Castilla-La Mancha (Central Eastern Spain). Relative to undisturbed sites, grazing significantly reduced soil water content (-53%) and available water (-59%). However, soil hydraulic conductivity remained unaffected by animal trampling and the soil water repellency observed in ungrazed sites disappeared. Grazed soils experienced a slight increase in pH (+18%). Among the biochemical properties studied, only dehydrogenase showed a significant increase (+100%) while basal respiration exhibited a notable decrease (-24%). Grazing resulted in a reduction of plant species richness (-34%) indicating a loss of biodiversity in grazed areas. The observed significant alterations in key soil and plant properties due to livestock activity suggest that grazing has the potential to modify the overall soil quality of these sites. Certain variables that exhibited noteworthy differences between grazed and ungrazed sites could serve as indicators of grazing impacts in Mediterranean forests. These indicators may be considered proxies for establishing effective land management strategies to mitigate degradation in the Mediterranean forest ecosystem., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Annually, the Mediterranean region attracts around one-third of the global coastal tourism, which is acknowledged as a substantial contributor to plastic pollution. Coastal municipalities mitigate this through periodic sand and shore cleaning. However, the efficacy of these measures remains uncertain. In this study, the occurrence of MPs (10 μm-5 mm) in sand from seven different, regularly cleaned, touristic beaches of the coastline of Valencia province (E Spain) was assessed. Two different sampling campaigns were performed in winter and in summer (2022) to compare the results and understand the influence of the high touristic activity, as well as, the efficiency of the measures taken against MPs pollution. The methodology used was designed specifically for the matrix and employed density separation using a Sediment Microplastic Isolation (SMI) Unit. In addition to conventional visual inspection and ATR-FTIR, automatic quantification and identification of the polymers of lower size was performed by μFTIR. The average MPs concentration in the summer (339 ± 92 MP kg -1 by stereomicroscopy and 339 ± 189 MP kg -1 by μFTIR) was significantly higher than in the winter (71 ± 92 MP kg -1 and 143 ± 85 MP kg -1 ) (p < 0.05). The combination of these analytical tools provides comprehensive information about the MPs present in beach sand. Fibers were the most abundant form of MPs, while most of the polymers analyzed were polyethylene (PE) and halogenated polystyrene (Cl-PS and Br-PS) with food packaging, swimming equipment and fishing nets being their most probable sources. Ecological risk assessment was performed through the Pollution Load Index (PLI), the Hazardous Index (HI) and the Risk Quotient (RQ), with the results indicating potential risk that ranges from moderate to high depending on the applied approach., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Rivers are ecosystems highly threatened by human activities and fish are an invaluable tool to measure and communicate environmental degradation and restoration. Fish bioassessment is crucial but notoriously difficult in Mediterranean-climate streams for a number of reasons, including low local species richness, faunas with high spatial turnover and generalist species, and scarcity of reference sites. In this study, we conducted the most comprehensive test of the pan-European fish index (EFI+) in the Iberian Peninsula, analysing its response to multiple anthropogenic pressures. We compiled a database, which we provide online, with 2970 electrofishing samples across Spain, involving 100,732 fish of 69 species. Principal component analyses of many quantitative variables were used to create new synthetic anthropogenic pressure indices. Correlation and multiple linear regression analyses were used to test the relationship between these pressures and the fish index (EFI+) and its four individual metrics scores (i.e., density of species intolerant to oxygen depletion, density of fish ≤150 mm of species intolerant to habitat degradation, richness of species of rheophilic reproduction habitat, and density of species of lithophilic reproduction habitat). We also obtained the same models but including the river basin district to test for spatial or methodological differences. Our results indicate that both the EFI+ index and its individual metrics respond to various anthropogenic pressures. These pressures explained about 36% of the variance of EFI+ values. Notably, downstream and mainstream reaches with higher agricultural or urban land uses, increased hydrologic alteration, and water and habitat quality impairment exhibited lower EFI+ values. Although less variance was explained for the individual metrics than for the fish index, they responded as expected to the different pressures. For instance, the richness of rheophilic species and the number of lithophilic fish decreased with hydrologic alteration, while the number of fish intolerant to oxygen depletion decreased with water quality impairment. Similar correlations were observed when river basin district was included in the model, but with higher explained variation and greater significance of the pressures. While it is possible to develop regional indices with more metrics and a stronger correlation with anthropogenic pressures, EFI+ is the only fish index that has been validated throughout the Spanish peninsular territory. Our results support the use of EFI+ in intercalibration exercises across Spain until better regional indices are developed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Geospatial fire behaviour and fire hazard simulators, fire effects models and smoke emission software commonly use standard fuel models in order to simplify data collection and the inclusion of complex fuel scenarios. These fuel models are often mapped using remotely sensed data. However, given the great complexity of fuelbeds, with properties that vary widely in both time and space, the use of these standard fuel models can greatly limit accurate fuel mapping. This affects fuel hazard assessment, fuel reduction treatment plans, fire management decision-making and evaluation of the environmental impact of wildfire. In this study, we developed unique customized fire behaviour fuel models for shrub and bracken communities, by using k-medoids clustering analysis based on both fuel structural characteristics and potential fire behaviour. We used an original database of 722 destructive sample plots in nine different shrub and bracken communities covering the entire distribution area in Galicia (NW Spain), one of the regions in Europe most affected by forest fires. Measurements of cover, height and fuel fractions loads differentiated by size and vegetative state (live or dead) were used to estimate the potential rate of fire spread with five different models including fireline intensity, heat per unit area and the flame length for each sampling site and considering extreme environmental conditions. The optimal number of clusters was established by combining practical knowledge about the shrubland communities under study and their associated fire behaviour, with maximization of the mean value of the silhouette variable and minimization of the within-cluster sum of squares. The structural characteristics of the medoids derived from the analysis were associated with each of the proposed customized fuel models. Finally, a simple dichotomous classification based only on shrub height was developed to enable construction of spatially explicit fuel model maps based on remotely sensed data. Thus, the methodology applied allows generation of a more realistic representation of fuel distribution in the landscape, based on fuel structure measurements of natural regional ecosystems rather than on the use of standard models. We believe that the proposed methodology is generally applicable to communities composed of other shrub and fern species in different biogeographical regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Cave heritage is often threatened by tourism or even scientific activities, which can lead to irreversible deterioration. We present a preventive conservation monitoring protocol to protect caves with rock art, focusing on La Garma Cave (Spain), a World Heritage Site with valuable archaeological materials and Palaeolithic paintings. This study assessed the suitability of the cave for tourist use through continuous microclimate and airborne particles monitoring, biofilm analysis, aerobiological monitoring and experimental visits. Our findings indicate several factors that make it inadvisable to adapt the cave for tourist use. Human presence and transit within the cave cause cumulative effects on the temperature of environmentally very stable and fragile sectors and significant resuspension of particles from the cave sediments. These environmental perturbations represent severe impacts as they affect the natural aerodynamic control of airborne particles and determine bacterial dispersal throughout the cave. This monitoring protocol provides part of the evidence to design strategies for sustainable cave management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

This study evaluate the effects of four organic soil amendments on soil. Physical, chemical and biochemical properties were compared to untreated and natural (not cultivated) soils in a semiarid region (Andalusia, Spain). A large set of physical, chemical biochemical properties and, the composition of bacterial communities; and overall soil quality index (SQI) were evaluated on soils treated with organic soil amendments of animal origin (compost from sheep and cow manure [CS] or chicken manure, [CK], vegetal origin (greenhouse crop residues [CC]), and vermicompost (CV). Immediately after application, the animal origin compost significantly increased pH, electrical conductivity (EC), and total nitrogen (TN) as well as the enzymatic activities associated with the carbon (C) cycle but decreased the richness and evenness of bacterial communities. After 3 months of treatment, all measured properties recovered except for EC, TN and dehydrogenase activity (whose increase was stable over time), as did bacterial richness, which remained lower. The vegetal-originating compost increased EC and pH whereas the other effects were not significant throughout the monitoring period. CV application did not affect soil properties. The SQI was the highest for soils treated with CK compost, both immediately after application and over time. The soil treatments with the other organic amendments did not result in a significantly different SQI over time compared to both untreated and natural sites., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)