Search Results (3,874)

Sustainable fertilization techniques are essential in Mediterranean farming systems, where the depletion of organic matter, influencing soil water and nutrient availability, is becoming an increasing concern. In this context, organic fertilizers offer an effective strategy to restore soil fertility while reducing environmental impacts. This research aimed to evaluate the effects of different organic fertilizers on soil quality and tree performance in a sweet cherry (Prunus avium L.) orchard. This study was conducted in two growing seasons (2021–2022) in an organic orchard in Southern Italy, comparing four treatments: (i) compost, (ii) compost combined with compost tea, (iii) mixed manure, and (iv) an unfertilized control. The results indicated that compost tea, applied both to the soil and as a foliar spray, significantly improved tree water status, particularly under water stress conditions, as reflected by more negative stem water potential values. Moreover, this treatment enhanced photosynthetic performance, yield, and fruit quality, achieving the highest ratio of soluble solids content/total acidity. The findings suggest that compost tea, in combination with compost, could be a sustainable and valuable fertilization option for Mediterranean organic tree orchards. However, further studies are necessary to understand the benefits of other fruit orchards as well as the long-term effects on soils. Full article

Abstract: The Australian lungfish, Neoceratodus forsteri, is one of the world’s oldest vertebrate lineages, with a slow life-history and threatened status, requiring immediate conservation efforts. The main threats to lungfish populations are degradation and availability of key macrophyte habitats, water regulation and flow modification. As this long-lived species (at least 77 years) has delayed maturity (mature at 10 years), field monitoring alone will not be enough to inform the challenge of ensuring sustainable populations. A stochastic metapopulation model was developed for the Burnett River (Southeast Queensland, Australia), an important habitat for the lungfish that is a highly regulated system with extensive water infrastructure. The model consists of three interacting populations, where the ecology and biology of the species were translated into an 80-year-class population projection matrix for each population, each with post-development streamflow, habitat and movement rules. The model highlights the longer-term interaction between dams and stream flows on habitat availability and subsequent recruitment. Through a pre-development streamflow, we quantify the impact of high regulation and development on the lungfish population in the Burnett River: a minor decline in the upstream population (e.g., 9.8% decline), a large decline in the middle population (64.2% decline), virtually no change in the downstream population (e.g., 1.2% decline) and a moderate decline in the overall metapopulation (e.g., 22.3% decline). The loss of spawning and feeding habitat remains the main reason for population decline, with implications that the loss will lead to greater pressure on remaining downstream habitat due to combined flow and dam effects and, in turn, to extended periods of recovery of spawning habitat. Our modeling approach substantially advances conservation management of this species, as it can be adapted to suit other populations in other river systems and used to test sensitivity to recovery actions. Full article

Grapevines are subjected to many physiological and environmental stresses that influence their vegetative and reproductive growth. Water stress, cold damage, and pathogen attacks are highly relevant stresses in many grape-growing regions. Precision viticulture can be used to determine and manage the spatial variation in grapevine health within a single vineyard block. Newer technologies such as remotely piloted aircraft systems (RPASs) with remote sensing capabilities can enhance the application of precision viticulture. The use of remote sensing for vineyard variation detection has been extensively investigated; however, there is still a dearth of literature regarding its potential for detecting key stresses such as winter hardiness, water status, and virus infection. The main objective of this research is to examine the performance of modern remote sensing technologies to determine if their application can enhance vineyard management by providing evidence-based stress detection. To accomplish the objective, remotely sensed data such as the normalized difference vegetation index (NDVI) and thermal imaging from RPAS flights were measured from six commercial vineyards in Niagara, ON, along with the manual measurement of key viticultural data including vine water stress, cold stress, vine size, and virus titre. This study verified that the NDVI could be a useful metric to detect variation across vineyards for agriculturally important variables including vine size and soil moisture. The red-edge and near-infrared regions of the electromagnetic reflectance spectra could also have a potential application in detecting virus infection in vineyards. Full article

(1) Background: To date, data concerning the population of Alosa immaculata and Alosa tanaica from the marine waters of Bulgaria are rather scarce. In the range of a project for mapping the Bulgarian marine protected sites from the network NATURA 2000, we provide an intense investigation of the biology and distribution of both Alosa species. (2) Methods: A trawling survey was carried out within 102 predefined sampling plots of 10 × 10 km grid cells (93 cells on the continental shelf, up to 100 m depth, and 9 offshore cells). In some coastal regions, sampling was conducted with gill nets of different mesh sizes (28 mm to 36 mm). Analysis of the suitability of the occupied habitat of both species was carried out using the MAXENT v 3.4.0 software application. The status of the populations was studied based on the parameters abundance (ind./km⁻²), biomass (kg/km⁻²), size, sex structure, maturity, and food spectrum. (3) Results: Out of 102 transects studied, A. immaculata was found in 12 transects and A. tanaica in 13. A total of 408 fish specimens were captured, out of which 313 were A. immaculata and 95 were A. tanaica. Both species were distributed along Bulgaria’s entire Black Sea coast, with a numerical prevalence of the catches in the southern part. The population size of A. immaculata for the number of individuals on a biographical level in the Marine Black Sea Biographic Region (MBLS) was a minimum of 100,255 individuals and a maximum of 526,408 individuals (the average was 313,286). The population size for A. tanaica was a minimum of 28,183 individuals and a maximum of 449,549 individuals (an average of 238,866). The current population density of A. immaculata in the MBLS was 25.98 ind./km⁻², and for A. tanaica, it was 19.00 ind./km⁻². The current biomass of the population of A. immaculata in the MBLS was 3.44 kg/km⁻², and the population of A. tanaica was 0.53 kg/km⁻². The sex ratio for A. immaculata was 1 male:2.6 females, and for A. tanaica, 1 male:3.8 females. Both shad species were feeding with less intensity or not feeding during the winter. The diversity in the food spectrum of A. tanaica was more limited compared to that of A. immaculata. (4) Conclusions: Key parameters for the Bulgarian Black Sea Exclusive Economic Zone indicate current stability in the resources of A. immaculata and A. tanaica and more favorable conditions for the populations in the Natura 2000 sites compared to that outside the Natura 2000. The results of this study should be used to develop management plans for marine protected areas, and future monitoring projects should follow the sampling protocol. Full article

The water-level-fluctuation zone of a reservoir is an important connection between land and water; due to counter-seasonal rhythmic water level changes, this area is more sensitive and vulnerable, whereas the assessment and management of heavy metal pollution are still elusive. This study selected the water-level-fluctuation zone in the hinterland of the Three Gorges Reservoir. Through a quadrats investigation, the soil pollution status of seven heavy metals and the composition of herbaceous plants were identified, and the potential of the dominant species for phytoremediation was assessed. The results showed that the overall pollution was at the alert level (P_N = 0.97) and a low ecological risk level (RI = 123.12). And the study area was primarily contaminated by a mixed source of traffic, agriculture, and industry. A total of 17 dominant species were calculated using importance values. Most dominant species had better phytoremediation potential for Cd and Cu. None of the 17 dominant species were hyperaccumulators, but they could still play an important role in phytoremediation due to their high adaptability to specific environments. The results have guiding significance for the management and remediation of soil heavy metal pollution in global reservoir areas, further promoting global ecological security and sustainable development. Full article

Preserving healthy river habitats is essential for maintaining fish diversity. Over time, anthropogenic activities have severely damaged river habitats, leading to notable changes in fish diversity patterns. Conducting thorough and reliable investigations into fish diversity is crucial for assessing anthropogenic impacts on diversity. In August 2023, a water ecology survey was conducted across 20 terraced river sections in the mainstem of the Jialing River, resulting in the collection of 60 environmental DNA water samples. The survey identified 99 fish species, representing 74 genera across 7 orders and 20 families, with the Cyprinidae exhibiting the highest number of species. The fish communities are predominantly composed of species inhabiting slow flowing water, demersal fish, omnivores, and fish spawning adhesive eggs. Overall, small-bodied fish dominate the mainstem of the Jialing River, and the species preferring flowing habitats are relatively scarce. In addition, geographic division analyses revealed minimal variations in fish species composition and diversity among the terraced reservoirs and across the upper, middle, and lower reaches. Notably, the fish compositions in the middle and lower reaches were found to be similar, indicating a certain degree of convergence in these sections of the Jialing River. In conclusion, this study unveils the current status and distribution pattern of fish diversity in the Jialing River and highlights the extent of anthropogenic activities’ impact on fish diversity. Full article

This study addresses the challenges of and opportunities for achieving the ambitious greenhouse gas emissions reduction target of the fishery sector of the Republic of Korea, set at 96% by 2030. We also focus on the current status of land-based aquaculture and underground seawater resource development, quantitatively compare energy inputs for land-based fish cultivation, and evaluate the potential of underground seawater to reduce CO₂ emissions. Since 2010, 762 underground seawater boreholes have been developed, yielding a cumulative daily pumpage of 125,780 m³. Jeollanam-do was found to have the highest daily pumpage, with an annual energy requirement of 131,205,613 Mcal. Despite the fact that the energy demands for underground seawater are higher in some months, it provides a 22.6% reduction in total annual energy consumption compared to surface water. The use of underground seawater for heating or cooling resulted in a 24.1% reduction in the required input energy. However, energy requirements increase due to the relatively high surface water temperature in some regions and seasons. This study also highlights the utilization of underground seawater in heating or cooling surface water via indirect applications using geothermal heat pumps. This innovative research broadens the methods of greenhouse gas mitigation, particularly in the agriculture, livestock, and fisheries industries. Full article

Climate-driven water challenges in the Pacific Northwest necessitate precise irrigation for sustainable vineyard management. In such scenarios, conservation of water using different approaches, including subsurface irrigation, becomes critical. Detecting crop water status becomes key to evaluating and managing such approaches. This study examines how multispectral, thermal, and hyperspectral proximal sensing data depict irrigation-induced variations in stomatal conductance in Cabernet Sauvignon vineyards during 2016 and 2017. The roles of individual and combined sensing modalities were analyzed, with key contributions including the identification of indices that characterize stomatal conductance. Data were collected at the following growth stages: 80 and 44 days before harvest (DBH) in 2016; and 64, 44, and 8 DBH in 2017. The vegetation indices analyzed included the green normalized difference vegetation index (GNDVI) and leaf area index (LAI) from multispectral data, crop water stress index (CWSI) from thermal data, and normalized difference spectral indices (NDSI) from hyperspectral data. Pearson’s correlations at 80 and 44 DBH (2016) showed significant relationships between normalized stomatal conductance and multispectral indices (LAI: r = 0.59 to 0.66, GNDVI: r = 0.41 to 0.50, both p < 0.01). NDSI pairs (1380 nm with 1570 nm, 1570 nm with 1810 nm) at 80 DBH showed significant correlations (r = −0.27, 0.31, both p < 0.05). In 2017, the thermal data showed the strongest correlation with normalized stomatal conductance (r = −0.83) at 44 DBH. In the same year, NDSI pairs exhibited stronger correlations than multispectral indices as the DBH decreased (1380 nm with 1570 nm: r = −0.58 to −0.69, 1570 nm with 1810 nm: r = 0.64 to 0.48, both p < 0.05). Combining LAI with these NDSI pairs improved stomatal conductance predictions (2016: R² = 0.37–0.50; 2017: R² = 0.51–0.63, both p < 0.01). These results demonstrate the precision of a multimodal sensing approach, particularly integrating multispectral and hyperspectral data, to improve irrigation strategies and promote sustainable viticulture. Full article

Mulching practices have demonstrated the potential to increase crop yields and resource utilization efficiency. However, the response of different crops with various growth stages to different mulching practices remains unclear, particularly in the rainfed agroecosystem. Therefore, a two-year field experiment (2013–2015) of different crops (wheat, maize, and potato) was conducted to evaluate the effects of three different mulching treatments: straw strip mulching (SM), plastic film mulching (PM), and conventional planting without mulching as the control (CK), on soil moisture and temperature, evapotranspiration (ET), water use efficiency (WUE), crop yield and economic benefits on the Loess Plateau. The results indicated that both mulching practices significantly increased the soil water content (SM: 4.3% and PM: 3.6%) compared to CK. However, the effects on soil temperature varied between mulching practices, PM increased soil temperature by 4.9% compared to CK, while SM decreased it by 6.3%. The improved soil hydrothermal conditions, characterized by favorable temperatures and higher soil water status would lead to a higher crop daily growth rate (5.3–49.8%), as well as greater dry matter accumulation (4.7–36.7%). Furthermore, mulching practice (SM and PM) has a significant influence on crop yield and its components of various crops, as well as WUE. The mean grain yield of SM and PM was, respectively, increased by 11.4% and 27.1% for winter wheat, compared to CK, 1.8% and 24.3% for spring maize, and 23.0% and 13.9% for potato, respectively. Compared to CK, PM yielded a higher net economic benefit and WUE for winter wheat and spring maize, while SM presented the best economic benefit and WUE for potato. In conclusion, a comprehensive analysis of crop yield, economic benefits, and resource utilization efficiency suggests that straw strip mulching for potato is a more sustainable environmentally friendly mulching practice, recommended for rainfed farming systems on the Loess Plateau and areas with similar climatic conditions. Full article

Leaf water potential (ψ_leaf) is a key indicator of plant water status, but its measurement is labor-intensive and limited in spatial coverage. While remote sensing has emerged as a useful tool for estimating vegetation water status, ψ_leaf remains unexplored, particularly in mixed forests. Here, we use spectral indices derived from unmanned aerial vehicle-based hyperspectral imaging and machine learning algorithms to assess ψ_leaf in a mixed, multi-species Mediterranean forest comprised of five key woody species: Pinus halepensis, Quercus calliprinos, Cupressus sempervirens, Ceratonia siliqua, and Pistacia lentiscus. Hyperspectral images (400–1000 nm) were acquired monthly over one year, concurrent with ψ_leaf measurements in each species. Twelve spectral indices and thousands of normalized difference spectral index (NDSI) combinations were evaluated. Three machine learning algorithms—random forest (RF), extreme gradient boosting (XGBoost), and support vector machine (SVM)—were used to model ψ_leaf. We compared the machine learning model results with linear models based on spectral indices and the NDSI. SVM, using species information as a feature, performed the best with a relatively good ψ_leaf assessment (R² = 0.53; RMSE = 0.67 MPa; rRMSE = 28%), especially considering the small seasonal variance in ψ_leaf (±σ = 0.8 MPa). Predictions were best for Cupressus sempervirens (R² = 0.80) and Pistacia lentiscus (R² = 0.49), which had the largest ψ_leaf variances (±σ > 1 MPa). Aggregating data at the plot scale in a ‘general’ model markedly improved the ψ_leaf model (R² = 0.79, RMSE = 0.31 MPa; rRMSE = 13%), providing a promising tool for monitoring mixed forest ψ_leaf. The fact that a non-species-specific, ‘general’ model could predict ψ_leaf implies that such a model can also be used with coarser resolution satellite data. Our study demonstrates the potential of combining hyperspectral imagery with machine learning for non-invasive ψ_leaf estimation in mixed forests while highlighting challenges in capturing interspecies variability. Full article

The increasing consumption of pharmaceuticals, including antibiotics, and their improper disposal have resulted in both pharmaceuticals and their metabolites being released into the environment, where they pose a risk to both ecosystems and human health. One of the most serious threats to public health associated with the presence of antibiotics in the environment is antimicrobial resistance (AMR). In order to combat AMR, the legal aspect of water protection becomes a critical area of action. This article analyzes the current challenges and legislative developments in the European Union (EU) aimed at mitigating pharmaceutical contamination in aquatic environments, particularly with regard to AMR. It traces the evolution of EU water protection policies from the initial surface and groundwater directives to the recent updates of the Water Framework Directive, Groundwater Directive and Environmental Quality Standards Directive, focusing on the integration of pharmaceutical contaminants into the regulatory framework. In addition, these changes include the update of the Watch List system for monitoring emerging contaminants, the adoption of effects-based methods (EBMs) in the assessment of water status and the streamlining of the legislative process to respond more quickly to emerging threats in the aquatic environment. The EU’s strategic approach to pharmaceuticals in the environment is emphasized as a key framework for harmonizing the environmental standards and addressing the problem of AMR through more sustainable pharmaceutical practices. This study advocates for a proactive, integrated approach to water policy that aligns regulatory actions with scientific advancements to protect public health and ecosystem integrity. Full article

This study examined the ecological status of the Streževo Reservoir in North Macedonia, focusing on zooplankton as an indicator of water quality. Built in 1982, the Streževo Reservoir serves several purposes, including irrigation, water supply, and hydropower generation. The research project investigated the seasonal and vertical variation in zooplankton abundance and biomass as well as the influence of environmental factors. Sampling was conducted seasonally (spring, summer, and autumn) in 2010 and 2011 across the longitudinal profile (epilimnion, metalimnion, and hypolimnion) of the reservoir at three sampling stations: the inflow of the Šemnica River, a central station in open water, and a site near the dam. The Streževo Reservoir is characterized by significantly pronounced seasonal and vertical temperature stratifications. The species diversity of the zooplankton was low, with only 21 taxa identified. Seasonal oscillations in abundance were statistically significant, with maximum values in the summer period and minimum values in spring. The Shannon diversity index displayed the lowest diversity values in the autumn, in the hypolimnion, and the highest values in the summer, in the metalimnion. The RDA analysis showed that temperature was the most important predictor of zooplankton abundance distribution, followed by Chl a concentration and TN. According to the Zooplankton Index of Quality Assessment (Zoo-IQ), during the investigated period the reservoir had good water quality in all three studied seasons, as well as through the whole profile. Overall, the study highlights the importance of zooplankton as an indicator of water quality and provides valuable insights into the ecological status of the Streževo Reservoir. The novelty of this study lies in its comprehensive examination of the interconnected dynamics affecting reservoir ecology, particularly as the present study is the first to perform such an analysis for the Streževo Reservoir. It highlights the impacts of thermal stratification on biochemical processes, the seasonal variations in dissolved oxygen and phosphorus levels due to phytoplankton activity, and the influences of temperature on zooplankton diversity and abundance. Furthermore, it introduces the Zoo-IQ index as an innovative tool for assessing water quality through zooplankton analysis, emphasizing its relevance as an early indicator of ecological changes in freshwater systems. Moreover, this multi-faceted approach underscores the complexity of reservoir ecosystems and the importance of proactive management strategies to the mitigation of water quality fluctuations. This study underlines the need for continuous monitoring and proactive management strategies to address the aging of reservoirs. Full article

The objective of this study is to better identify the state of eutrophication of coastal waters along the southern coast of the city of Jeddah in the Red Sea. Thirty-six samples from surface seawater were collected during the spring and autumn of 2021. Water temperature, pH, salinity, dissolved oxygen (DO), nutrients, and chlorophyll-a (Chl-a) content were examined as a guide of water quality indicators. The present data revealed low levels of Chl-a content (in the range of 0.11–0.24 µg L⁻¹). The average concentrations of DIN (dissolved inorganic nitrogen) forms follow the order NO₃-N > NH₄-N ~ NO₂-N (representing about 11.4–29.4% of the total nitrogen). To investigate the trophic status and water quality, numerical indicators were applied to the results of the analysis of chemical variables (NH₄-N, NO₃-N, and PO₄-P) and the biological analysis (Chl-a) in the aqueous environment within the study area. These indicators are simplified based on the specialist, the non-specialist, the decision-maker, and the one responsible for managing the coastal areas. We also obtain through this method a single numerical value that expresses the state of the coastal waters. According to the analysis of phosphorus and nitrogen data and a trophic index (TRIX), the study area’s trophic status was determined as oligotrophic, due to low nutrient concentrations in the seawater. The current study identified a total of 58 species of phytoplankton comprised four classes in the investigated areas; Bacillariophyceae was the dominant algal class (Diatoms 30 species), followed by Chlorophyceae (9 species), Dinophyceae (11 species), and Cyanophyceae (8 species). Seasonally, spring recorded the highest value of total phytoplankton, recording a value of 251 × 10³ cells/L with a percentage of 61%, while autumn recorded the lowest value of 186 × 10³ cells/L with a percentage of 39%. Phytoplankton classes can be arranged in order of prevalence as follows: Bacillariophyceae >> Dinophyceae > Chlorophyceae > Cyanophyceae. Full article

Water distribution networks (WDNs) are critical infrastructures that directly impact urban development and citizens’ quality of life. Due to digitalization technologies, modern networks have evolved towards cyber-physical systems, allowing real-time management and monitoring of network components. However, the increasing volume of data from monitoring poses significant challenges to accurately estimate the hydraulic status of the system, mainly when anomalous events or unreliable readings occur. This paper presents a novel methodology for state estimation (SE) in WDNs by integrating convolutional graph networks (GCNs) with long short-term memory (LSTM) networks. The methodology is validated on two WDNs of different scales and complexities, evaluating the SE of the sensors. The capability of the GCN-LSTM model was assessed during the last two months of the time series by simulating failures to analyze its impact on sensor readings and estimation accuracy. The smaller network showed higher sensitivity of the sensors to detect failures, while the larger one evidenced more challenges in SE due to the sensor dispersion. Overall, the model achieved low prediction errors and high coefficient of determination values between the actual and simulated values, showing good performance. Likewise, the simulated failures showed that replacing the missing data with the hourly mean of the last week significantly improved the accuracy of the predictions, guaranteeing a robust SE in the event of sensor failures. This methodology provides a reliable tool for addressing various network configurations’ operational challenges. Full article

Effective control of the health operating condition of multi-support, ultra-long shaft system water-lubricated stern bearings is crucial for supporting the intelligent maintenance and health management of ships. This study investigates the failure modes of water-lubricated stern bearings and focuses on the critical failure modes of abnormal wear and high-temperature meltdown to analyze the mechanisms and influencing factors of these failures. It discusses the conditions for healthy operation of water-lubricated stern bearings, as well as methods for controlling lubrication and temperature rise. Based on this, controllable parameters for the healthy operation of water-lubricated stern bearings were selected, an experimental rig was constructed, and experiments were conducted using SF-2A material water-lubricated bearings. The experimental results indicate that by controlling parameters such as shaft rotational speed, inlet lubrication water temperature, clear-water lubrication, sediment-laden-water lubrication, bearing specific pressure, and the surface morphology of the bearing liner, the velocity characteristics, lubrication characteristics, and temperature rise characteristics of the bearings can be effectively altered. The sensitivity of the lubrication and temperature rise characteristics of SF-2A material water-lubricated stern bearings to controllable parameters varies under different environmental conditions. The study finds that precise control of these parameters can improve the operating condition and reliability of water-lubricated bearings. Full article