Search Results (7,487)

Sensitive benthic macroflora are widely recognized as valuable indicators of ecological quality in coastal ecosystems. This study investigated their diversity and spatial distribution along the Aegean coast of Türkiye and evaluated their relationships with physicochemical variables, nutrient concentrations, and anthropogenic pressures quantified using the Macroalgae-Land Uses Simplified Index (MA-LUSI). A total of 25 coastal stations were surveyed during spring, summer, and autumn 2022, and 91 sensitive taxa were recorded, including 30 brown algae, 52 coralligenous red algae, four green algae, and five seagrasses. Clustered heatmaps based on Bray–Curtis dissimilarity were used to evaluate spatial patterns in community composition using presence–absence and percentage coverage data, whereas Canonical Correspondence Analysis (CCA) was applied to examine the relationships between sensitive phytobenthic communities and environmental variables. The presence–absence heatmap clearly distinguished İzmir-Bostanlı from the remaining stations because of its markedly lower sensitive taxon richness and distinct taxonomic composition. The percentage coverage heatmap also revealed considerable spatial variation among stations, reflecting differences in the abundance and distribution of sensitive habitat-forming taxa. CCA demonstrated clear relationships between sensitive phytobenthic communities and local environmental gradients, with several southern and central Aegean stations being closely associated with sensitive habitat-forming taxa. MA-LUSI values ranged from 0.94 at Gökçeada to 11.25 at İzmir-Bostanlı, indicating pronounced spatial differences in anthropogenic pressure. Overall, the findings demonstrate that sensitive benthic macroflora provide reliable indicators of environmental quality and highlight their importance for the ecological assessment, long-term monitoring, and conservation of coastal ecosystems along the Aegean coast of Türkiye. By identifying areas of ecological degradation, this study also provides a scientific basis for prioritizing conservation and restoration actions in coastal areas exposed to high anthropogenic pressure. Full article

Water color is an important optical proxy for trophic status and water quality, but its integration into regulatory assessment frameworks is still limited. This study assesses the potential of the Forel–Ule Index (FUI) derived from Sentinel-2 as a proxy indicator to support the assessment of the ecological status of reservoirs under the European Union’s Water Framework Directive (WFD). Seventeen reservoirs located in semi-arid Mediterranean climate agricultural basins in southern Portugal (Sorraia, Sado, and Guadiana) were analyed, combining 4316 FUI observations (2017–2024) with in situ water quality data and official WFD ecological status classifications. The results showed that the values on the FUI scale (which ranges from 1 to 21) fell, for the most part, between 12 and 18 and with marked spatial and seasonal contrasts, particularly between more transparent reservoirs and persistently turbid ones, probably eutrophicated reservoirs. Principal component analysis showed that the first component (PC1, 39.5% of variance) represents a trophic gradient dominated by turbidity, chemical oxygen demand and chlorophyll-a, and is positively, albeit moderately, correlated with FUI (Spearman’s ρ = 0.439, p < 0.001), while the second component, dominated by nitrogen, showed no significant association. To make the Water Framework Directive (WFD) regulations compatible with the structure of the available dataset, ecological status was dichotomized into “Satisfactory” and “Deterioration”. Binary logistic regression showed that increasing FUI values were significantly associated with a lower probability of classification as “Satisfactory” (β = −0.682, p = 0.0137; odds ratio = 0.51, 95% CI: 0.29–0.87). The model performance was moderate (balanced accuracy = 0.682; AUC = 0.754), with better identification of “Deterioration” conditions than “Satisfactory” conditions. The Mann–Whitney U test confirmed that mean FUI values differed significantly between the two ecological status groups (U = 65, p = 0.0166), with lower values associated with reservoirs meeting the “Good” threshold. Overall, FUI proved to be a low-cost and temporally flexible screening and early-warning tool, particularly useful for identifying departures from favorable ecological conditions. However, the index is not a direct substitute for the official ecological classification and is best applied in combination with physicochemical and biological metrics when assessing changes in water quality over a shorter period of time. Full article

The Soil Quality Index (SQI) is a vital tool for evaluating soil quality; however, traditional approaches seldom integrate microbial data from high-throughput sequencing—commonly used to characterize soil microbial communities—into the SQI framework. This study enhances the SQI by incorporating microbial indicators derived from high-throughput sequencing, establishing a more comprehensive evaluation system. We collected soil samples from mining areas and analyzed their fundamental physicochemical properties and microbial indicators. Four SQI models were constructed using different indicator sets: (1) only physicochemical properties (T-SQI); (2) physicochemical properties and bacterial α-diversity (α-SQI); (3) physicochemical properties, α-diversity, and relative abundances of the top five abundant bacteria (αMA-SQI); and (4) physicochemical properties, α-diversity, and relative abundances of the top five bacteria based on LDA scores (αBM-SQI). Results demonstrated that integrating multi-level microbial indicators improved the rationality of soil quality rankings and significantly strengthened correlations with α-diversity. Gemmatimonadota was consistently selected in the Minimum Data Set (MDS) for both αMA-SQI and αBM-SQI, highlighting its ecological importance. Statistically, microbial indicators at the order and family levels were most suitable for inclusion in the MDS, as their results deviated least from the total dataset. In conclusion, incorporating microbial diversity across taxonomic levels refines the SQI, enabling a more accurate and holistic assessment of soil health. Full article

Loess mountainous regions in northern China suffer frequent landslides, collapses and debris flows controlled by complex geological settings, seasonal rainstorms, freeze–thaw cycles and large-scale human engineering activities. Multi-geohazard susceptibility evaluation can provide fundamental data support for regional disaster prevention and territorial planning. Taking Shanxi Province, a typical loess-mountain transition zone, as the study area, this paper establishes an evaluation framework for landslides, collapses and debris flows. Ten conditioning factors are selected, including lithology, terrain parameters, distance to faults, distance to rivers, NDVI and RX1day (annual maximum 1-day precipitation). A 30 m grid unit is adopted as the basic evaluation unit. A total of 2598 verified geohazard points are taken as positive samples. Negative samples with equal quantity are extracted from low and very low susceptibility areas of the preliminary zoning map generated by the Frequency Ratio (FR) method, with an 800 m minimum separation distance between sampling points to reduce spatial autocorrelation. Two models, Logistic Regression (LR) and Support Vector Machine (SVM), are constructed, and five-fold cross-validation is used to test model performance through five statistical indicators and AUC values. The results show that, under the specific model configurations and sampling strategy adopted in this study, the LR model achieved higher predictive performance (average test AUC = 0.995) than the SVM model (average test AUC = 0.752) in the comparative assessment. Statistical analysis of the final susceptibility map derived from the LR model indicates that high and very high susceptibility zones account for 80.94% of the total provincial area and contain 87.45% of all recorded geohazard points, which confirms the consistency and reasonableness of the zoning results. Spatially, high-susceptibility areas are concentrated in the western and northwestern loess tablelands, the Fenhe River fault basin, and fault-developed sections of the Lüliang and Taihang Mountains. Thick loess layers, river undercutting and coal mining activities jointly reduce slope stability in these zones. Compared with conventional susceptibility modeling workflows, this study incorporates the RX1day extreme precipitation index and implements Frequency-Ratio-constrained stratified negative-sample selection to reduce training-sample bias. The produced susceptibility maps can provide technical support for differentiated geological hazard risk management, ecological restoration and territorial spatial planning for loess-mountain transition regions in northern China, thereby directly contributing to regional sustainable development and disaster resilience. Full article

Long-term mining activities can cause complex ecological and environmental problems, including mineral surface exposure, dust-related disturbance, and vegetation degradation, while conventional ecological indices may not fully characterize the distinctive ecological conditions of mining areas. This study developed a mining-area Modified Remote Sensing Ecological Index (MRSEI) by incorporating the Lithological Mineral Index (LMI), Normalized Dust Difference Index (NDDI), and Vegetation Health Index (VHI) into the Remote Sensing Ecological Index (RSEI) framework. Object-based analytical units were constructed using Landsat time-series data from 2000 to 2024 and G-means clustering, followed by the development of an Object-Based XGBoost-SHAP (OB-XGBoost-SHAP) framework to quantify the relative model contributions and nonlinear associations of explanatory factors. The results showed that, in the Daye mining area (DMA), MRSEI provided clearer differentiation of ecological quality among land-use types than RSEI and Mining-Specific Eco-Environment Index (MSEEI), with an overall gradient of forest land > cultivated land > construction land > mining land. Annual Principal Component Analysis (Annual-PCA) and Global Principal Component Analysis (Global-PCA) results showed high consistency (Pearson r = 0.985). Across the seven evaluation years, the mean MRSEI of the DMA increased from 0.5493 in 2000 to 0.6035 in 2024, representing an overall change of 9.87%. The object-based model consistently outperformed the regular-grid model under random splitting, while model performance decreased under spatially separated validation but retained moderate predictive capability. Particulate Matter (PM10), Digital Elevation Model (DEM), Temperature (TEM), and Land Use Intensity (LU) showed relatively high model contributions, with their relative importance varying across different periods. This study integrates mining-specific ecological characterization, object-based spatial analysis, and explanatory-factor contribution analysis, providing a methodological reference for ecological quality assessment and long-term change monitoring in mining areas. Full article

Studying the relationships between understory plant diversity and soil physicochemical properties aids in understanding the sustainable development of plantation forests. Vegetation restoration in latosol gully erosion areas plays a key role in preventing soil erosion. Variations in understory plant diversity and soil physicochemical properties in areas that have undergone vegetation restoration subsequent to gully erosion are not well understood. In this study, we investigated the understory species composition, importance values, plant diversity, and soil physicochemical properties and explored their correlations following vegetation restoration using four forest types (Acacia mangium forest, Eucalyptus robusta forest, A. mangium–E. robusta mixed forest, and A. mangium–E. robusta–Schizostachyum pseudolima mixed forest) in the Mahuangling Watershed, Hainan Province. A total of 49 plant species belonging to 47 genera and 20 families were recorded. The E. robusta forest (31 species) and A. mangium–E. robusta mixed forest (27 species) had higher species richness and more complex community structures. The dominant shrub species were Rhodomyrtus tomentosa, Breynia fruticosa, Aporosa dioica, and Dodonaea viscosa, while the dominant herbaceous species were Ageratum conyzoides, Chromolaena odorata, Spermacoce alata, and Erigeron sumatrensis. In all four vegetation restoration forest types, the richness index in the herbaceous layer was higher than in the shrub layer, while the diversity index showed no significant difference between the shrub and herbaceous layers (p > 0.05). The soil bulk density ranged from 1.57 g·cm⁻³ to 1.63 g·cm⁻³, with the A. mangium forest having better soil total porosity (38.77%) and water-holding capacity (190.37 t·hm⁻²) than the other forests. NH₄⁺-N and NO₃⁻-N were lower in the E. robusta forest, while the A. mangium forest had significantly higher organic matter content (13.71 g·kg⁻¹). Correlation and redundancy analyses showed that soil water content, pH, and soil organic matter were key factors affecting herbaceous-layer and shrub-layer plant diversity. On the whole, we suggest that the planting of pure and mixed forests of A. mangium should be considered in future ecological restoration projects in the gully erosion area of Mahuangling in order to maintain the stability of understory plant diversity and improve latosol soil fertility. Full article

Farm-level ecological organization may influence insect biodiversity, although these relationships can vary among regional settings and may not be captured fully by an aggregated agroecological index. We evaluated associations between the Main Agroecological Structure (MAS), insect biodiversity, community composition, and functional groups associated with potential pollination and biological control across 30 smallholder farms in the Maule Region of Mediterranean Chile. The farms were distributed among Cauquenes, Rauco, and San Clemente, and their immediate surroundings were characterized within 500 m. A total of 3926 individuals representing 144 taxonomic units were collected using standardized yellow pan traps. MAS varied widely among farms (31.8–79.4) but did not differ among municipalities. After accounting for municipality, MAS was not associated with Hill diversity of orders q = 0, q = 1, or q = 2, and no MAS × municipality interaction was detected for these responses. Insect community composition differed among municipalities, although this result was accompanied by heterogeneous multivariate dispersion, whereas the within-municipality association between MAS and community composition was not significant. Pollinator richness and abundance were not associated with MAS. Natural-enemy richness showed a MAS × municipality interaction, with positive associations in Cauquenes and San Clemente but not in Rauco. Natural-enemy abundance increased with MAS, although residual spatial autocorrelation remained after spatial sensitivity analysis. These results indicate that MAS is useful for characterizing farm agroecological organization but was not a general predictor of insect biodiversity. Regional setting, individual MAS components, and the immediate surroundings of each farm should therefore be distinguished when evaluating biodiversity and ecosystem-service potential. Full article

The prefectures and cities along the Yunnan–Vietnam border constitute a key cultural corridor connecting China and ASEAN. Under the dual pressures of globalization and modernization, the regional cultural landscape is undergoing profound structural transformation. This study takes 194 traditional villages and 942 municipal-level and above intangible cultural heritage (ICH) items in Honghe, Wenshan, and Pu’er as the research objects. Kernel density estimation, the standard deviation ellipse, and the gravity center model were employed to identify their spatial distribution patterns, while the spatial mismatch index and GeoDetector were used to examine their spatial coupling relationship and influencing mechanisms. The results indicate the following: (1) traditional villages exhibit a single-core clustered distribution concentrated in the Ailao Mountains-Honghe River Basin of Honghe Prefecture, whereas ICH displays a one-core-two-cluster pattern with relatively weak agglomeration, and the gravity centers of the two heritage systems are separated by 61.21 km; (2) a significant systematic spatial mismatch exists between traditional villages and ICH, with Honghe characterized as a high negative mismatch region, while Pu’er and Wenshan represent positive mismatch regions; (3) their spatial relationship is jointly shaped by nonlinear interactions among natural geographical, socioeconomic, and historical-cultural factors, forming an interaction mechanism dominated by the ecological constraints of hydrothermal conditions and topography together with the spatial organizational effects of border ports and transportation networks. This study reveals the spatial reorganization pattern of cultural heritage elements in the three prefectures and cities along the Yunnan–Vietnam border and provides a scientific basis for the coordinated conservation and spatial optimization of traditional villages and intangible cultural heritage. Full article

Rapid urbanization in the Huaihe River Basin has reshaped land use and intensified the tension between ecological protection and food security. A key gap is that most basin-scale ecosystem service value (ESV) assessments describe changes in land-cover composition but do not identify how landscape configuration–ESV associations vary across space. Using land use remote sensing images from 2000 to 2020, we quantitatively characterized the spatiotemporal evolution of land use via transfer matrices and landscape pattern indices. By integrating the equivalent value factor method, contribution analysis, spatial correlation analysis, and the geographically weighted regression (GWR) model, we examined the spatiotemporal dynamics and driving mechanisms of ecosystem service value (ESV). Key findings are as follows: (1) From 2000 to 2020, cropland area steadily decreased, while construction and forest land expanded markedly, with a synthetic land-use dynamic degree reaching 9.66%. (2) ESV first rose then fell, showing an overall decline. Forest land (18.882 billion CNY) and water areas (20.331 billion CNY) were the primary contributors. The ESV response to land use change manifested as a trade-off between short-term gains and long-term degradation. (3) Landscape patterns exhibited significant spatial heterogeneity, and ESV correlated strongly with patch number (NP) and landscape shape index (LSI). Class area (CA) emerged as the dominant factor, with CA of forest land, cropland, and water areas exerting the most pronounced effects. Based on the differential driving effects of landscape patterns and identified land use change hotspots, we propose enhancing ecosystem service values and mitigating conflicts between ecological conservation and food security through differentiated ecological engineering and ecological compensation strategies. Full article

Aquatic heavy metal pollution poses substantial risks to ecological systems and human health, attributable to the toxic properties and bioaccumulative behaviors of metallic ions, including Hg[II], Zn[II], and ion mixtures. A novel SPR sensing chip based on a Ag-BiFeO₃-MoS₂–graphene hybrid structure is proposed and analyzed for detection of metal ion mixtures. Systematic tuning is implemented for Ag and BiFeO₃ film thicknesses to boost the overall sensing capability, aiming to acquire minimized reflectance together with favorable detection sensitivity. Following this step, we investigate how different quantities of MoS₂ and graphene layers affect the sensing properties of the SPR biosensor. Analytical outcomes demonstrate that configurations adopting monolayer MoS₂ and graphene achieve the maximum phase sensitivity. Moreover, the optimized SPR chip architecture achieves sensing sensitivity two orders of magnitude greater than conventional sensor setups. Numerical investigations are further carried out to evaluate the sensor’s response toward various heavy metal ion species. The maximal sensitivity of 1.599 × 10⁶ deg/RIU is realized when detecting Zn[II]. Under this optimal structural setup, the spatial electric field distributions responding to variations in the refractive index of the sensing medium are also characterized. The remarkable sensitivity of the presented sensor configuration makes it a more competitive choice for deployment in further biological detection scenarios. Full article

Land-use change is a primary driver of changes in ecosystem services, and different development scenarios imply markedly different ecological responses, with consequences for regional economic development and ecological protection. However, existing studies have mostly focused on historical and current conditions, and quantitative assessments of future ecosystem-service changes under multiple land-use scenarios remain limited. In this study, the patch-generating land-use simulation (PLUS) model was used to simulate land-use patterns of Hubei Province under business-as-usual (BAU), economic development (ED), and ecological conservation (EC) scenarios for 2030 and 2040; five ecosystem services—habitat quality (HQ), soil conservation (SC), grain productivity (GP), water yield (WY), and water purification (WP, proxied by nitrogen export)—were then assessed for 2000–2020 and the future scenarios at a 30 m resolution using InVEST-based modules; Spearman correlation analysis was used to identify trade-offs and spatial associations among services, and the geographical detector model (GDM) was applied at 5 km and 10 km grid scales to quantify the explanatory power of driving factors. The results show that from 2000 to 2020, cultivated land, forest land, grassland, and unused land in Hubei Province decreased by 273,146.76 hm², 61,111.08 hm², 8712.99 hm², and 5392.26 hm², respectively, while construction land and water areas expanded. Over the same period, GP, SC, and WY increased, nitrogen export grew (indicating a weakening of water purification), and HQ declined continuously from 0.545 to 0.527; the comprehensive ecosystem-service index (CESI) followed a U-shaped trajectory (0.268 in 2000, 0.243 in 2010, and 0.267 in 2020). Under the future scenarios, GP increases markedly under BAU and ED, while HQ and SC deteriorate and nitrogen export rises; under EC, HQ and SC improve significantly, GP first decreases and then increases, and both WY and nitrogen export decline. Among the driving factors, elevation, slope, and NDVI dominate the spatial heterogeneity of ecosystem services, and their explanatory power varies between the 5 km and 10 km scales. These findings provide a reference for optimizing land-resource allocation and for reconciling economic development, food security, and ecological protection in Hubei Province. Full article

The co-evolution of urban–rural spatial transformation and ecosystem services represents a key scientific issue for high-quality basin development and metropolitan ecological governance. As a core growth pole in the lower Yellow River Basin, the Jinan Metropolitan Area (JMA) faces the overlapping pressures of rapid urbanization and ecological constraints, making it an appropriate case for exploring the interactions between the urban–rural gradient and ecosystem service value (ESV). Based on multisource spatiotemporal datasets for 2000–2024, this study deploys a modified equivalent-factor method, a multidimensional urban–rural gradient model, and a geographic detector to investigate ESV dynamics, the evolution of the urban–rural gradient, and their coupling relationship at a 1 km × 1 km grid scale. The results show that: (1) Total ESV in the JMA increased slightly from 2000 to 2024, with pronounced spatial heterogeneity. High-ESV areas were distributed in the southern mountainous region and along the Yellow River, whereas low-ESV areas were mainly distributed across the northern plains and urban built-up areas. Forestland and water bodies provided the primary foundation for regional ESV stability. (2) Inner-suburban areas expanded rapidly and became the dominant urban–rural transition zone, while rural areas continued to contract. Urban areas exhibited both polarization and sprawl along transportation corridors. (3) The coupling coordination between ESV and the urban–rural gradient exhibited a “high-periphery, low-middle” spatial pattern and declined slightly over time. Land-use change, population density and normalized difference vegetation index (NDVI) serve as core driving factors, with nonlinear threshold effects; pairwise factor interactions exert stronger explanatory power than individual factors. This study advances the analytical framework for examining ESV in basin-metropolitan areas and provides a reference for integrated urban–rural development and ecological protection in similar regions. Full article

Páramo ecosystems are among the most biodiverse and hydrologically critical landscapes on Earth, yet their long-term sustainability is increasingly threatened by climate-driven wildfires. Vegetation Cover Fires (VCFs) in these high-altitude environments degrade carbon stocks, disrupt freshwater regulation, and undermine biodiversity conservation goals central to the UN Sustainable Development Goals (SDGs 13, 15, and 6). Between 2001 and 2023, 128 fire events consumed approximately 815 ha in the Sumapaz locality (the world’s largest continuous páramo), representing 64.9% of all fires recorded across Bogotá’s 20 localities. Despite this disproportionate ecological and social impact, no spatially explicit, operational risk management framework has been available for the region, representing a critical sustainability governance gap. This study addresses that gap by proposing an integrated climate-adaptive risk assessment and management strategy based on (i) the Canadian Forest Fire Danger Rating System Fire Weather Index (FWI), derived from ERA5 reanalysis climate data; (ii) spatial and temporal hotspot analysis of MODIS FIRMS active fire detections; and (iii) IDEAM’s multi-component vulnerability and threat scoring protocol. Spatial data were processed using ArcGIS, and FWI sub-indices were computed for each month of the 2001–2023 period. The FWI averaged 0.78 (low danger) across the study period yet peaked at 13.7 in February 2010 (moderate-to-high danger), consistent with the year of highest recorded fire activity (19 events). High- and very high-risk areas (3.70% combined) coincide with slopes >25%, the presence of the invasive and pyrogenic Ulex europaeus, and proximity to populated and agricultural lands. This study concludes with a three-pillar risk management framework—risk knowledge, risk reduction, and disaster management—providing spatially targeted, operationally viable strategies for local and institutional actors that directly support the sustainable conservation of páramo ecosystem services (water supply, carbon sequestration, biodiversity). The framework is designed to be updatable on a monthly basis using freely available ERA5 data, enabling continuous adaptive governance of wildfire risk as a contribution to long-term territorial sustainability. Limitations regarding MODIS detection uncertainty, ERA5 spatial resolution in complex terrain, and the need for probabilistic modeling are explicitly acknowledged. Full article

The article presents the results of a study on the growth, development, response to mineral nutrition and yield stability of 16 varieties of spring barley on chernozem soils of Northern Kazakhstan, cultivated under three backgrounds of mineral nutrition—without fertilizers, half of the calculated dose (N₃₀P₃₅) and the full calculated dose (N₆₀P₇₀) of fertilizers. The reserves of productive moisture, the content of nitrate nitrogen, mobile phosphorus, exchangeable potassium, pH of the water extract in the soil, phenological development of plants, plant density, elements of crop structure, yield, ecological plasticity to mineral nutrition and stability of yield of barley varieties were studied. It was found that the use of mineral fertilizers increased the average grain yield by 0.29–0.46 t/ha (24.0–38.0%) compared to the unfertilized background. The varieties Kudesnik (+0.77 t/ha; +98.7%), Prairie (+0.80 t/ha; +63.0%) and Arna (+0.64 t/ha; +66.0%) showed the greatest response to fertilizers; the maximum yield was achieved by the varieties KWS Salome (2.30 t/ha) and Vakula (2.28 t/ha) with the full calculated dose of fertilizers. Correlation analysis showed that, against an unfertilized background, yield was most closely related to the 1000-grain weight (r = 0.75), the number of plants before harvesting (r = 0.63), and the number of productive stems (r = 0.53), indicating the leading role of these traits in yield formation. The values of the ecological plasticity coefficient (bi) varied from 0.6 to 1.7, and the yield stability index (Hom) varied from 3.4 to 6.9, which reflects significant differences in the adaptive response of varieties to changes in the level of mineral nutrition. According to the type of adaptability, the following varieties were selected for extensive technology: Velikan, Slavny, Divny, Abalak, Kerzhak, for resource-saving: Astana 2000, Arna, Tselinny-60, Grace, Eifel and intensive technology: KWS Salome, Vakula, Prairie, Paustiana, Ara, Kudesnik, recommended for the corresponding cultivation technologies. Full article

The Berca–Arbănași region of Buzău County (Romania) is of exceptional geochemical interest due to diapiric structures, active mud volcanoes, and historical subsurface hydrocarbon deposits. This study presents the first comprehensive geochemical assessment of surface soils from the Berca–Arbănași Subcarpathian zone, based on the analysis of 27 soil samples collected along three north–south transects and the determination of 12 potentially toxic elements (As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, V, Zn) using aqua regia digestion and ICP-MS. The local geochemical background was calculated using the iterative median ± 2MAD method. Twelve pollution and ecological risk indices were computed: the Pollution Index (PI), Contamination Factor (CF), Geoaccumulation Index (Igeo), Enrichment Factor (EF), Pollution Load Index (PLI), Modified Degree of Contamination (mCd), Nemerow Integrated Pollution Index (PINemerow), Ecological Risk Factor (E_rⁱ), Ecological Risk Index (RI), Mean Effect Range-Median Quotient (MERMQ), Degree of contamination (Cdeg), and the V/Ni petroleum origin indicator. Results show that 66.7% of samples are classified as polluted (PLI ≥ 1; mean = 1.102), with moderate enrichment in Cd, Cu, Hg, Pb, and Zn, attributable to diffuse anthropogenic sources. The ecological risk index (RI) remains low across all samples (mean = 35.96; all < 150), indicating that, despite moderate pollution, ecological risk is currently low. The V/Ni ratio (0.391–0.884, mean = 0.608) is below 1.0 for all samples, indicating a lithogenic (not petroleum) origin of vanadium and nickel and confirming a negligible geochemical impact of mud volcanoes and hydrocarbon extraction activities in the area at the sampled locations. The study establishes baseline geochemical reference values for the Berca–Arbănași area and provides data for sustainable land management, environmental monitoring, and evidence-based policymaking. These results directly support the objectives of the EU Soil Strategy 2030 and align with the United Nations Sustainable Development Goals on food security (SDG 2), good health and well-being (SDG 3), and life on land (SDG 15). Full article