Search Results (4,590)

Native soils host diverse symbiotic microflora that contribute to sustainable agricultural practices and plant establishment. This study aims to investigate the benefits of rhizosphere soil microbiota associated with four Mediterranean native plants, Rhus pentaphylla (NS1), Drimia maritima (NS2), Pistacia lentiscus (NS3), and Withania frutescens (NS4), growing in proximity to the local Moroccan almond variety Prunus dulcis (Mill.) (NS5). Native soils were applied directly as living substrates to evaluate their effects on the germination and early development of almond, with particular emphasis on the potential of arbuscular mycorrhizal fungi (AMFs). Root analysis revealed high mycorrhizal colonization intensity (M% = 87.5–95%) and infectivity (F% = 100%). Under the tested soil conditions, three native soils (NS1, NS3, and NS5) achieved germination rates exceeding 70% after 28 days. Moreover, NS5 and NS1 soils showed the strongest effects on almond germination and seedling growth, respectively. Overall, the use of native soils enhanced almond germination and early development, highlighting the role of AMFs as natural biofertilizers. The associated native plant species may also function as nurse plants that facilitate almond establishment. These findings support the use of the rhizosphere microbiome as a bio-based strategy to promote sustainable almond cultivation in local and Mediterranean agroecosystems. Full article

Hydropower stations, as critical infrastructure for basic energy supply, play a pivotal role in ensuring the reliability of power systems through their safe and stable operation. Grounding grids operating long-term in complex soil environments are prone to corrosion and degradation, disrupting current distribution balance and causing spatial asymmetry in the voltage field, thereby compromising system safety. Corrosion branch resistance increment identification based on the electrical network method is typically modeled as a parameter inversion optimization problem. However, this problem exhibits underdetermination and other characteristics, making it difficult for traditional analytical methods to obtain stable solutions. To address this, this paper proposes a quantum perturbation scheduling candidate pool-guided sine–cosine algorithm (QSPSCA). Building upon the classical sine–cosine algorithm framework, it incorporates a dynamic candidate pool with multi-source attractor points and a quantum-inspired long-tail scheduling local refinement operator. This achieves an enhanced and smooth transition between global exploration and local refinement. Comparative experiments based on the CEC2017 benchmark and a hydropower station grounding grid corrosion diagnosis case demonstrate that QSPSCA outperforms multiple comparison algorithms in terms of average optimality and result stability. Furthermore, QSPSCA is applied to three typical engineering-constrained optimization problems. Results demonstrate that, whilst satisfying engineering constraints, this method consistently yields higher-quality feasible solutions with superior convergence accuracy and stability compared to alternative algorithms. Therefore, QSPSCA is not only applicable to underdetermined inversion diagnostics but also provides a solution framework with broad applicability for complex engineering optimization problems under structural symmetry perturbations. Full article

Surface water quality, serving as a key link between domestic water use and agricultural production, impacts both the drinking water safety of local residents and the sustainable use of irrigated soil. To better protect water resources and enhance their sustainable value, this study collected 50 water samples from the areas surrounding Nansi Lake. Using the Piper trilinear diagram, Gibbs model, and ion ratio analysis, the main hydrochemical types were identified. Based on this, the entropy-weighted water quality index (EWQI) was used to evaluate the water’s suitability for drinking, while irrigation water quality indicators were applied to assess its suitability for irrigation. The results indicate that during both dry and rainy seasons, Na⁺ and SO₄²⁻ dominate the water, with average total dissolved solids (TDS) of 1279 mg/L and 1163 mg/L, respectively, indicating moderately elevated salinity. The ion concentrations follow the order: SO₄²⁻ > HCO₃⁻ > Cl⁻ > NO₃⁻ > F⁻ and Na⁺ > Ca²⁺ > Mg²⁺ > K⁺. From a hydrochemical perspective, mixed-type and Cl-Na-type waters prevailed in both seasons. The chemical composition of surface water in the study area is largely governed by rock weathering, with ions primarily originating from the dissolution of silicate and evaporite minerals. Furthermore, cation exchange processes play a significant role in shaping the evolution of the water chemistry. The water quality evaluation indicates that surface water in the study area is generally Class II, representing good water quality. However, Class IV and Class V water exist in some areas, where the primary exceedance parameter is SO₄²⁻, which is a key factor influencing water quality. Irrigation suitability is generally good. Systematic investigation of surface water hydrochemistry and quality is of great practical significance for ensuring safe drinking and irrigation water and promoting sustainable socio-economic development. Full article

This study assessed photovoltaic (PV) soiling losses at Alamogordo, New Mexico, USA, located within the Chihuahuan Desert and near the White Sands gypsum dune field, a region with frequent dust events. Soiling material collected from PV module surfaces showed seasonal variations in mineral composition, with quartz being the main component during the fall season and calcite predominating during the spring. All samples collected during the following spring season contained large amounts of gypsum, indicating transport from White Sands, supported by HYSPLIT back-trajectories and surface wind data. Soiling materials collected from PV module surfaces generally had a mineral composition similar to that of the surrounding local soils. The mean particle size of collected soiling material samples ranged from 8 to 21 µm, with ~90% of particles being dust (<50 µm) and ~10% of the soiling particles being sand (>50 µm). Despite Alamogordo experiencing 22 dust events during this study, soiling-related power losses were relatively low, about 2% to 3%, much lower than reported for Global Dust Belt locations. The prevailing south-to-southwest winds and their gusts acted as a passive cleaning mechanism, as they were aligned with the front of the PV modules and likely resuspended particles off panel surfaces. Additionally, relatively low rainfall (about 2.2 mm per hour) was effective in restoring PV performance. These findings suggest that, due to the relatively low soiling losses observed, frequent cleaning may not be necessary at this location, resulting in potential savings in maintenance costs over the long-term operation of the PV system. Full article

This study presents a fire risk prediction framework applied to two conservation units within the Atlantic Forest biome (AFb): Serra da Gandarela National Park (PNSG), Minas Gerais, and Campos de Palmas Wildlife Refuge (RVSCP), Paraná. Daily climate data (2001–2023), remote sensing vegetation indices Normalized Difference Vegetation Index (NDVI) and Normalized Multi Band Drought Index (NMDI), fire foci, and estimates of soil volumetric moisture were integrated to analyze the climatic and environmental drivers of fire occurrence and to develop predictive models. Sea Surface Temperature (SST) anomalies in the Niño 3.4 region revealed the influence of El Niño–Southern Oscillation (ENSO) variability on local hydrometeorological dynamics. Vegetation indices and soil moisture data reinforced this relationship, with NMDI values below 0.4 and sharp declines in volumetric moisture indicating water stress during the dry season. Kernel density maps identified clusters of fire foci during this period, confirming the strong seasonality of fire occurrence. Based on climatic predictors and environmental indicators, fire risk indices were developed for each conservation unit and validated using independent data. Model performance showed moderate explanatory capacity, with coefficients of determination ranging from 0.53 to 0.68 and high agreement between estimated and observed values. Validation stratified by ENSO phases (Neutral, El Niño, and La Niña) demonstrated stable performance across contrasting climatic regimes, indicating temporal resilience of the modeling framework. Overall, the integration of climate data, spectral indices, and soil moisture information improves the ability to anticipate fire risk in Atlantic Forest conservation units, providing a useful tool to support prevention, monitoring, and decision-making in protected areas. Full article

Alhagi camelorum is a dominant leguminous shrub distributed in the Taklamakan Desert, an area characterized by extreme drought and high soil salinization, which can complete its life cycle normally in salt-affected soils. However, the underlying molecular regulatory mechanism of its salt tolerance remains largely unclear. The AcABI5 gene was successfully cloned and characterized, and it encodes a typical nuclear-localized bZIP transcription factor. Functional characterization demonstrated that overexpression of AcABI5 markedly improved the salt stress tolerance of A. camelorum calli, whereas silencing of AcABI5 via virus-induced gene silencing (VIGS) rendered the plant more sensitive to salt stress. Further mechanistic investigations revealed that AcABI5 enhanced salt tolerance by regulating the expression of superoxide dismutase (SOD)- and peroxidase (POD)-related antioxidant genes. Compared with the wild type, AcABI5-overexpressing calli exhibited significantly increased SOD and POD activities and remarkably reduced malondialdehyde (MDA) content under salt treatment, whereas AcABI5-silenced lines exhibited the opposite physiological phenotypes. Furthermore, heterologous silencing of AcABI5 in Nicotiana benthamiana via virus-induced gene silencing (VIGS) produced comparable salt-sensitive phenotypes, similar to those observed in A. camelorum AcABI5-silenced lines. Collectively, these results provide insights into the molecular mechanism by which AcABI5 enhances salt tolerance in A. camelorum, and lay a solid theoretical foundation for the optimization of the A. camelorum genetic transformation system and the expansion of related salt-tolerant crop research. Full article

Invasive alien species such as Lantana camara L. impact native species and soil properties, but context-specific effects in transfrontier conservation areas remain poorly understood. Understanding these effects is essential for biodiversity conservation and management. We assessed associations between L. camara presence and native woody species composition and structure, as well as soil nutrients, in protected and communal areas within the Kavango–Zambezi Transfrontier Conservation Area (KAZA TFCA), Zimbabwe. The study hypothesised that invasion effects on vegetation are stronger in communal areas due to higher disturbance, and that soil changes are influenced by land-use intensity. We used stratified random sampling to select 60 plots across invaded and uninvaded sites. Woody vegetation was assessed for species composition and richness, stem density, canopy cover %, height, and diameter at breast height. Soil samples were analysed for nitrogen, organic carbon, phosphorus, potassium, and pH. The presence of L. camara was negatively associated with native species richness, density, height, and canopy cover %, with stronger effects in communal plots. Invaded plots had lower pH (e.g., 6.1 in Park areas) and higher levels of some soil nutrients, particularly phosphorus and organic carbon, though patterns varied by land-use type. These results suggest that anthropogenic disturbance amplifies invasion impacts. We conclude that L. camara reduces native vegetation diversity and structure in this species-rich transfrontier area. Management should prioritise control at communal edges to support woody species resilience, ecosystem services, and biodiversity, with strategies adapted to local land-use conditions. Full article

Responding to rapid urbanization, this study examines the trade-offs and synergies of ecosystem services (ESs) at the county scale in the Zhengzhou metropolitan area and constructs an ecological security pattern. Using the InVEST model, we quantified carbon storage (CS), soil conservation (SC), habitat quality (HQ), water yield (WY), and food production (FP). We then analyzed their trade-offs and synergies using the geographically weighted regression model, identified driving factors with an optimal parameter-based geographical detector model, detected ecosystem service bundles via a Self-organizing map model, and constructed an ecological security pattern based on circuit theory. The results showed that: (1) From 2003 to 2023, ES spatial distribution remained stable overall, with weak trade-offs and synergies. Locally, WY and HQ declined, while SC and FP increased. (2) Slope and DEM enhanced SC, whereas urban expansion consistently weakened CS, HQ, and FP. Moreover, slope played an increasingly prominent role in regulating WY. (3) Key synergistic bundles with stable spatiotemporal distribution were identified as ecological sources, leading to the construction of ecological security pattern characterized by “four districts, one corridor, and one belt.” This provides a framework for integrating ecological space protection and restoration into urban development. Full article

Soil erosion is a significant environmental concern in arid regions, particularly in dam-regulated watersheds, where intermittent flows from sprinkler irrigation can exacerbate land degradation. This study assesses soil erosion susceptibility in the Sidi Aich watershed using a combined approach of the Revised Universal Soil Loss Equation (RUSLE) and the Analytic Hierarchy Process (AHP), enabling the integration of both regional characteristics and expert-driven weighting. The RUSLE model accounts for natural and human-induced factors, whereas AHP provides a hierarchical weighting system that highlights rainfall erosivity and the local impacts of dam-regulated discharges. Results show that 26.12% of the area falls into the very high susceptibility category, 25.45% into high, 23.91% into moderate, and 24.51% into low susceptibility. Model validation demonstrates satisfactory predictive performance, with Area Under the Curve (AUC) values of 0.85 for AHP and 0.78 for RUSLE. Overall, the findings emphasize the critical role of dam-controlled releases in increasing soil vulnerability, a factor that may not be fully captured when using RUSLE alone. By combining RUSLE and AHP, this research provides a more realistic and regionally tailored assessment of erosion risk, offering valuable guidance for watershed management and erosion mitigation strategies in arid environments. Full article

Riparian ecosystems are being increasingly threatened by hydrological alteration and biological invasions, yet the role of local environmental heterogeneity in shaping invasion dynamics remains poorly understood. To address this, we tested the hypothesis that invasion patterns are spatially structured and therefore cannot be fully captured by global statistical models. We evaluated this hypothesis by analysing the relationship between soil sand content and the abundance of Gleditsia triacanthos in a riparian forest of the Esteros de Farrapos and Islands of the Uruguay River National Park, Uruguay. Generalized Linear Mixed Model revealed no significant relationship between soil sand content and G. triacanthos abundance (χ² = 1.93, p = 0.17). In contrast, spatially explicit analyses showed that relationships between sand content and abundance were spatially contingent. Positive linear relationships predominated in areas with low sand content (mean 24.5%, n = 12), while negative relationships were restricted to the highest sand levels (mean 87.6%, n = 3). Intermediate sand-content zones (mean 47%, n = 16) showed no consistent patterns. These results suggest that invasion patterns vary across spatial contexts and may reflect the influence of different processes operating locally, indicating that relying solely on global analyses risks misinterpreting drivers and overlooking fine-scale variation. Our findings emphasize that understanding invasive species in heterogeneous systems requires considering whether mechanisms operate at local or broad scales, and that explicitly analyzing spatial structure can guide both hypothesis formulation and field study design. Full article

Urban trees are increasingly deployed as nature-based infrastructure to mitigate heat and manage stormwater, yet quantitative guidance on how species traits and site context shape transpiration remains fragmented. We conducted a systematic metadata analysis of seven field studies that measured daily transpiration rate in urban settings using heat-pulse methods. The units and spatial scales reported were harmonized with the sap flow density across active sapwood (J_s, g H₂O/${\mathrm{cm}}^2$/day) by converting reported stand transpiration and the outer 2 cm of sapwood sap flux using established Gaussian radial distribution functions for angiosperms and gymnosperms, which account for the non-linear decline in sap flux from the vascular cambium to the heartwood boundary. We then summarized distributions and tested group differences with Kruskal–Wallis and Dunn post hoc comparisons across wood anatomy, climate, soil texture, and planting configuration. Conifers exhibited significantly lower median $J_s$ (39.76 g/${\mathrm{cm}}^2$/day) than angiosperms, while the ring-porous group (median $J_s$ = 92.25 g/${\mathrm{cm}}^2$/day) and diffuse-porous groups (median $J_s$ = 96.70 g/${\mathrm{cm}}^2$/day) had similar distributions overall. Climate-modulated responses within wood anatomy groups differed, with diffuse-porous species exhibiting the highest median $J_s$ (152.59 g/${\mathrm{cm}}^2$/day) in semi-arid regions, ring-porous species maintaining comparatively stable median $J_s$ across climates (varying slightly between 80.72 and 99.32 g/${\mathrm{cm}}^2$/day), and conifers reaching their highest median $J_s$ (69.90 g/${\mathrm{cm}}^2$/day) in humid continental sites. Soil texture effects were consistent with moisture availability: sandy loam generally reduced $J_s$ relative to loam or silt loam for conifers and diffuse-porous species. Across anatomies, single trees transpired more than clustered trees or closed canopies. For example, planting as single trees increased median $J_s$ by 86% in conifers (from 33.01 to 61.37 g/${\mathrm{cm}}^2$/day) and by 45% in diffuse-porous species (from 81.31 to 118.25 g/${\mathrm{cm}}^2$/day). These results provide actionable ranges and contrasts to inform species selection and planting design for urban greening and runoff reduction, while highlighting data gaps for future research. Ultimately, by matching specific wood anatomies and planting configurations to local soil and climatic conditions, urban planners and ecohydrologists can strategically optimize urban forests to maximize targeted ecosystem services. Full article

Nitrous oxide (N₂O) is a major agricultural greenhouse gas. Its direct emission factor (EF) is a key parameter for greenhouse gas inventories and developing mitigation strategies. However, the Intergovernmental Panel on Climate Change (IPCC) default EF may not reflect actual emissions from Chinese croplands. This study compiled extensive field observations from key agricultural regions in China. A systematic meta-analysis was conducted to evaluate annual N₂O emissions and nitrogen fertilizer-induced direct emission factors. Subgroup analyses revealed that fertilizer type, land use, soil texture, and climate zone all significantly influence EF. Univariate meta-regression indicated that EF is positively correlated with nitrogen (N) application rate and mean annual temperature but negatively correlated with soil pH, highlighting these factors as key drivers of N₂O emissions. The mean EF in Chinese croplands was about 0.68%, much lower than the 1% global default recommended by the IPCC. The combined effects of optimized agricultural management, cropping systems, and local environmental conditions help explain these lower emission factors. These findings provide a scientific basis for developing region-specific emission factors, improving cropland mitigation strategies, and enhancing the accuracy of greenhouse gas inventories. Full article

Permeability anisotropy, which is widely present in natural soil deposits, plays an important role in controlling groundwater flow patterns and ground deformation during deep excavation dewatering. However, isotropic assumptions are still commonly adopted in engineering practice, making it difficult to accurately capture realistic subsurface hydraulic conditions. In this study, a deep foundation pit of a metro station in Jinan, China, is taken as a case study. A three-dimensional excavation–dewatering model incorporating permeability anisotropy is established using PLAXIS 3D to systematically investigate the influence of the permeability ratio (Kx/Kz) ranging from 0.1 to 10 on the seepage field evolution, dewatering influence radius, ground surface settlement, and consolidation time history. The results indicate that increasing permeability anisotropy promotes a fundamental transition of the seepage regime from vertically concentrated recharge to laterally dominated radial flow. Correspondingly, the dewatering influence radius exhibits a pronounced non-monotonic response to Kx/Kz, decreasing significantly with increasing permeability ratio and reaching a minimum at approximately Kx/Kz ≈ 5, followed by a slight rebound. Meanwhile, surface settlement profiles evolve from a localized concentration pattern to a widely distributed form as permeability anisotropy increases, accompanied by a remarkable outward expansion of the settlement influence zone. Both the magnitude and spatial distribution of settlement show high sensitivity to variations in permeability anisotropy. Based on these findings, a three-stage conceptual seepage structure model accounting for permeability anisotropy is proposed, characterized by vertically dominated flow, a transitional competition regime, and horizontally dominated flow. The staged evolution of seepage structures is shown to govern the non-monotonic variation in the dewatering influence radius and the spatial–temporal response of ground settlement. The results indicate a dual-scale influence mechanism of permeability anisotropy on dewatering-induced hydro-mechanical behavior, providing a theoretical basis for refined dewatering design and environmental impact assessment in deep excavation projects. Full article

Efficient soil fertility monitoring is essential for sustainable agriculture, food security, and environmental management across Africa, yet conventional laboratory methods remain prohibitively costly and slow for continental-scale applications. Soil spectroscopy is considered as a rapid, non-destructive alternative with transformative potential. This review provides a systematic synthesis of spectroscopic applications across Africa, encompassing laboratory, field, airborne, and satellite-based platforms, while examining major data sources including the Africa Soil Information Service (AfSIS) and GEO-CRADLE spectral libraries. We critically evaluate the evolution of modeling approaches, revealing that Partial Least Squares Regression (PLSR) dominates, but a shift toward advanced frameworks like hybrid physically based models, ensemble learning and deep neural networks is essential. Critically, we identify a pronounced imbalance wherein laboratory spectroscopy prevails while imaging and satellite-based approaches remain comparatively underutilized, despite their unparalleled potential for scaling point measurements to continental extents. The review consolidates findings on key soil properties, demonstrating consistent successes for primary constituents with direct spectral responses (i.e., organic carbon), while revealing relative uncertainty for properties inferred indirectly via covariance (e.g., available phosphorus, potassium). Despite significant local and regional progress, the absence of a standardized pan-African spectral library and the intractable transferability problem remain formidable barriers. Future research must pivot decisively toward imaging spectroscopy and satellite platforms, mitigating PLSR dominance through systematic adoption of ensemble methods, transfer learning, and model harmonization frameworks to fully operationalize these technologies in support of Africa’s sustainable development goals. Full article

Fuzzy logic-based mineral potential mapping was applied to the Tisová–Klingenthal Cu–Co VMS deposit (Erzgebirge) in the Czech–German border region. The study area is characterized by heterogeneous geological and geochemical datasets derived from differing national surveys and historical mining. Using the Exploration Information System (EIS) toolkit, a knowledge-driven fuzzy logic approach integrated key spatial datasets, including copper and zinc soil and stream sediment anomalies and metabasalt lithology, relevant to Besshi-type VMS deposits. Three prospective anomalies were identified: the historic Tisová mine and two additional targets aligned along the same stratigraphic horizon. Artificial Neural Network (ANN) modelling was limited by insufficient training data, resulting in overfitting and reduced predictive reliability. Follow-up soil geochemical surveys conducted over the largest anomaly returned locally elevated copper values but did not conclusively confirm mineralisation. The results demonstrate that fuzzy logic provides a flexible and interpretable framework for mineral potential mapping in complex, data-scarce environments and highlight the need for iterative modelling and targeted exploration. Full article