Search Results (9,541)

This study investigates the impact of critical raw material mining and processing on surface water quality within a representative catchment area, using the Luda Yana River Basin in Southern Bulgaria as a case study. Water quality was evaluated using the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI), based on data collected from five monitoring stations. The analysis focused on key heavy metals, including Cu, Zn, Pb, Cd, Fe, Mn, Ni, and As, reflecting the influence of both active and historical mining activities in the region. Index values were calculated for the period 2008–2024 and revealed considerable temporal variability and pronounced spatial differences in water quality along the river course. This study provides one of the first long-term integrated assessments of heavy-metal-related water quality in a mining-impacted river basin in Bulgaria using the CCME WQI framework and offers new evidence on the cumulative effects of historical and ongoing mining activities on surface waters. The calculated CCME WQI values ranged from very low levels indicating poor conditions to moderate values corresponding to marginal and, occasionally, fair conditions. Overall, the predominant water quality categories were “poor” and “marginal.” The results demonstrate that the waters of the studied river basin remain below the thresholds for “fair” physicochemical status as defined by the European Water Framework Directive (2000/60/EC) and the corresponding Bulgarian legislation, including Regulation No. H-4/2012 on surface water characterization and the 2010 Ordinance on environmental quality standards for priority substances and certain pollutants. The findings highlight the persistent anthropogenic pressure exerted on the river system and emphasize the need for improved water management strategies. The study further underlines the importance of integrating environmental protection measures into the exploitation of critical raw materials in order to balance economic development with the sustainable management of water resources. Full article

Forest fires are among the most critical disturbance agents reshaping Mediterranean ecosystems under accelerating climate change. This study employs a multi-scale remote sensing approach to examine the relationship between post-fire vegetation dynamics and climate variability in high-fire-risk areas of southern İzmir, Türkiye. Burned areas were delineated using the Burned Area Index (BAI) and differenced Normalized Burn Ratio (dNBR) applied to Landsat imagery (1990–2024) and Sentinel-2 imagery (2017–2024). Post-fire vegetation recovery was quantified through the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Vegetation Condition Index (VCI), Leaf Area Index (LAI), and Land Surface Temperature (LST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) products. Climate variables, including soil moisture, precipitation, and maximum, minimum, and mean air temperature, were derived from the TerraClimate dataset. Long-term spatiotemporal trends were assessed using the non-parametric Mann–Kendall (MK) test and Sen’s slope estimator for the 2000–2023 period. Results indicate a statistically significant increase in mean temperature (p < 0.05) and a concurrent decline in soil moisture over the past three decades, consistent with progressive atmospheric aridification. Vegetation indices exhibited marked seasonal asymmetry: significant declines in NDVI, SAVI, and LAI were recorded during summer months, whereas partial recovery was confined to the winter–spring wet season. A pronounced warm-dry shift was identified in the post-2015 period, characterized by positive Land Surface Temperature anomalies and compressed vegetation recovery windows. These findings highlight that increasing thermal stress and diminishing soil moisture collectively constrain post-fire ecosystem resilience in the Mediterranean climatic zone (MCZ). The integrated remote sensing framework developed here provides a robust and transferable basis for fire ecosystem monitoring and the formulation of climate adaptation strategies in fire-prone dryland regions. Full article

The 24 solar terms (STs) comprise a traditional Chinese seasonal calendar that has long guided agricultural practices, but their agronomic relevance under observed historical climate change remains uncertain. We assessed 24 STs’ applicability in Shanxi Province using climate records from 23 meteorological stations during 1960–2019. Climate trends were analyzed at the ST scale, and the Decision Support System for Agrotechnology Transfer (DSSAT) CERES-Maize model, calibrated for Denghai 679, was applied to simulate maize phenology and yield for evaluating phenological shifts and sowing-date effects. Results showed that (1) warming was concentrated during Yushui–Qingming and Xiaoxue–Dahan, with sunshine declines across Mangzhong–Xiaoshu and Bailu–Hanlu. Precipitation trends were weak and spatially variable. (2) The calibrated CERES-Maize model reliably reproduced regional yields and phenology. Simulated V3 growth stage, anthesis, and maturity dates advanced by 1.53, 1.88, and 3.11 days per decade, respectively. V3 was associated with early-spring hydrothermal and radiation conditions, while anthesis and maturity were closely associated with summer heat during the STs Xiazhi, Xiaoshu, and Dashu. (3) Model-derived optimal ST/hou sowing windows were Guyu–H2–H3, Xiaoman–H1–H2, and Xiaoman–H2–H3 for Northern, Central, and Southern Shanxi, respectively. Optimized sowing shifted V3 towards Xiaoman–Mangzhong, delayed anthesis from early Xiaoshu to late Dashu–Liqiu, and postponed maturity towards Qiufen, all referring to STs. These findings provide a scientific basis for continued use of the 24 STs in guiding agricultural practices for maize. Full article

Yellow-flowered camellias are a sought-after rarity that has a narrow natural distribution in southern China and northern Vietnam. Belonging to the Camellia sect. Chrysantha Chang, many of the yellow-flowered camellia species are endangered. In this study, whole-genome resequencing (WGR) was applied to a collection of 25 yellow-flowered camellias in the United States of America to generate molecular markers and estimate genetic diversity. A total of 200,385,257 SNPs, 15,632,190 indels, 420,648 structural variations, and 9067 CNVs were identified among the 25 plants. There were 122 SNPs within the chalcone synthase (CHS) gene. Two groups of plants, C. nitidissima and hybrids, were distinctly separated from the other individuals. High within-population diversity and moderate among-population differentiation were found. Compared to the genetic diversity present in the native regions of yellow-flowered camellias, only a limited number of species have been introduced to the United States. The current study is the first report of whole-genome resequencing of yellow camellias and the first investigation of genetic diversity and structure of a collection of individuals from the U.S. This significant genomic resource shall have a meaningful impact on conservation and breeding, as well as on species identification and evolution studies. The genetic diversity information shall guide the efforts in breeding and the introduction of new species. Full article

The unique climate and rivers of the Southern Great Plains of the United States have shaped both ecological and human communities. Historically, the rivers of this region supported a wide variety of endemic species evolutionarily adapted to the particularly harsh environment, characterized by flow variability, periodic flooding and drying, and overall complexity. In this review, we provide an extensive overview of the many perils that the rivers of the Southern Great Plains are now facing due to the anthropogenic changes centered on river dam construction, high agricultural water demand, and groundwater depletion. These factors have fundamentally reshaped the flow regime of the Southern Great Plains rivers, resulting in a decline of native fish assemblages and increases in invasive species as a consequence of modified sediment transport, decrease in microhabitat diversity, changes in channel morphology, and an increase in habitat fragmentation. The case that we describe in the present article represents a prototypical example of the ecological consequences of human-induced alterations of river ecosystems. Here, we present this case as an example of damming-induced alteration of the riverine ecosystem, and we propose possible conservation measures to restore the original riverine environment and protect the currently threatened native fish diversity. Full article

Background: The relationship between diet and body composition in people with HIV (PWH) is still not well defined. Therefore, our primary objective was to assess the association between Mediterranean diet (MD) adherence and body composition measured by whole-body dual-energy X-ray absorptiometry (DXA). Secondly, we aimed to assess differences between people living in the north (Padua, Veneto Region, Italy) vs. those living in the south of Italy (Catanzaro, Calabria Region, Italy) and with respect to ethnicity. Methods: In this cross-sectional study, adults with HIV with a confirmed virological suppression were enrolled at two Italian HIV clinics. MD adherence was assessed using the validated MedDiet Score, with high adherence being defined as a score ≥ 25. All participants underwent whole-body DXA. Anthropometric and DXA-derived measures were compared between people with high vs. low adherence to MD, and multivariable linear regression adjusted for age, sex, and CD4⁺ count at nadir was performed. Results: Among 130 participants (81.5% male; median age 57 years), 105 (80.8%) showed high MD adherence. High adherence to MD was more common among participants from Southern Italy than among those from Northern Italy and was associated with Caucasian ethnicity, higher education, higher CD4⁺ count and CD4/CD8 ratio, and a lower prevalence of obesity and neurological disorders. DXA analyses showed lower total and trunk fat mass and higher lumbar spine bone mineral density in highly adherent individuals. After adjustment, high MD adherence remained independently associated with lower BMI (β −5.3, 95% CI −7.3 to −3.4; p < 0.001). Conclusions: In ageing PWH, high MD adherence was associated with a more favourable clinical profile and healthier body composition, particularly lower central adiposity and BMI. Prospective and interventional studies are needed to clarify the role of this type of diet in PWH. Full article

Climate change and variability pose serious threats to natural and human systems. The Mediterranean and North Africa (MNA) are among the world’s climate change hotspots. An in-depth understanding of the decadal climate variability in this region is critical to support planning and management, as well as adaptation in important sectors such as water resources. Therefore, in this study, fifth-generation ECMWF atmospheric reanalysis (ERA5) precipitation data and the outputs of the Coordinated Regional Downscaling Experiment-COmmon Regional Experiment (CORDEX-CORE) regional models were used to characterize the decadal precipitation variability in MNA and its sub-regions (Western North Africa: WNA, Sahara: SAH, southern Mediterranean: SMED, and northern Mediterranean: NMED). The models showed overestimation in most areas and underestimation in a few areas relative to the ERA5 data, with the magnitude varying by region and season. The positive biases obtained from the regional climate models (RCMs) were higher than the positive biases obtained from the general circulation models (GCMs). The wet biases were dominant during the annual, summer, and autumn seasons over MNA and its sub-regions. Negative biases were mostly associated with GCMs, mainly HadGEM2-ES and/or NorESM1-M; meanwhile, they were linked with RCMs such as CCLM5-0-15 and/or RegCM4_v7 and were mostly obtained in winter and spring. The multi-model mean (MME) was better at reproducing the decadal precipitation patterns over MNA, SMED, and NMED at all time scales, while REMO2015-NorESM1-M and the MME performed better than the remaining models at the annual time scale over WNA and SAH. These findings are useful for improving climate modeling, the water resources management and related sectors, and climate adaptation strategies in the region, especially in North Africa. The short-period coverage of the simulated data available for this study constitutes a limitation to the findings. Full article

Wind erosion is a major driver of land degradation in drylands worldwide, yet the relative importance of climatic forcing and local surface conditions remains poorly understood. We quantified horizontal mass transport (HMT), characterized the particle-size distribution and organic matter of transported sediments, and identified the main environmental controls on wind erosion across three rangeland sites in the Patagonian steppe of southern Argentina. HMT was monitored over one year using passive sediment collectors (Mendeźs trap), while climatic erosivity, vegetation cover, and topsoil properties were concurrently assessed. Wind erosion exhibited substantial spatial variability, with annual HMT ranging from 0.22 to 2.35 kg m⁻¹ yr⁻¹ among sites. Transported sediments were enriched in both silt and organic matter relative to source soils, indicating the preferential export of fine, carbon-rich fractions during aeolian transport. Multivariate analyses revealed that wind erosion was more strongly associated with local vegetation cover and soil erodibility than with climatic erosivity. These findings suggest that surface conditions can override regional climatic controls on sediment transport in arid rangelands. Our results highlight the critical role of maintaining vegetation cover and soil surface stability to mitigate desertification processes and provide empirical evidence to improve wind erosion assessment and land management strategies in drylands. Full article

Xinjiang’s distinctive geography and climate provide important habitats for Falconidae species, yet their climate-driven habitat shifts and conservation gaps remain poorly understood. Using 2731 validated occurrence records and 26 environmental predictors, including bioclimatic, land-use, topographic, hydrological, anthropogenic, and Normalized Difference Vegetation Index (NDVI) predictors, we applied an optimized Maximum Entropy (MaxEnt) framework to project suitable habitats for seven falconid species under current conditions and three Shared Socioeconomic Pathway scenarios (1–2.6, 2–4.5, and 5–8.5) for 2041–2060, 2061–2080 and 2081–2100. Barycenter migration analysis, the Habitat Quality module of the Integrated Valuation of Ecosystem Services and Tradeoffs framework, and protected-area overlays were further integrated to identify conservation priorities. All models showed high discriminatory performance, with mean areas under the receiver operating characteristic curve exceeding 0.90. Current suitable habitats were mainly concentrated along river corridors and mountain foothills in the southern Altai, central-western Tianshan and northern Kunlun regions. Future responses were strongly species-specific. By 2081–2100 under Shared Socioeconomic Pathway 5–8.5, suitable habitat increased by 154.6% for Falco peregrinus and 79.5% for Falco tinnunculus but declined by 81.1% for Falco vespertinus; Falco subbuteo also showed overall expansion, with its suitable-habitat barycenter shifting by up to 291.9 km. Mean relative habitat quality was 0.514 [standard deviation = 0.185], while suitable habitat outside protected areas ranged from 35,346 to 304,866 km² among species, and high-quality priority conservation gaps reached 102,489 km² for Falco cherrug. These results demonstrate that climatic suitability does not necessarily correspond to high habitat quality or adequate protection and support species-specific, climate-adaptive conservation strategies for falconids in Xinjiang. Full article

The Indian Ocean Dipole (IOD) and the El Niño-Southern Oscillation (ENSO) are two major modes of interannual climate variability that interact across the Indo-Pacific region. Although the autumn IOD is known to influence ENSO with a lag of about one year, the decadal stability of this relationship remains poorly understood. Here we investigate the decadal variability of the lagged IOD–ENSO relationship using observations and 30 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Observational analyses reveal pronounced non-stationarity in the lagged IOD-ENSO linkage, characterized by a stronger (weaker) relationship during the negative (positive) phase of the Atlantic Multidecadal Oscillation (AMO). CMIP6 models exhibit a wide spread in their ability to reproduce this behavior, with only a subset capturing the observed decadal modulation. The inter-model differences are consistent with variations in the simulated amplitude of AMO variability. Models with more realistic AMO variability tend to better reproduce the observed decadal variability of the lagged IOD-ENSO linkage. These results suggest that AMO variability may be one contributing factor to the modulation of the lagged IOD–ENSO relationship, with potential implications for ENSO prediction. Full article

Objective: Due to limited freshwater supplies, Israel increasingly depends on desalination to fulfill its drinking water requirements. However, this process reduces mineral levels such as magnesium (Mg²⁺), calcium (Ca²⁺), and fluoride (F⁻), which could pose health concerns. In this study, we analyze the mineral concentrations across various water sources nationwide. Materials and Methods: We analyzed a national database on drinking water quality for levels of Ca²⁺, Mg²⁺, and F⁻ from 2014 to 2024. District-level concentrations were calculated and compared with national means and across primary water sources. Water sources were classified as primarily DSW (DSW) or primarily groundwater-based according to their dominant composition. Results: Nationwide median concentrations were 52 mg/L for Ca²⁺, 12 mg/L for Mg²⁺, and 0.15 mg/L for F⁻. Ca²⁺ and Mg²⁺ showed marked regional variation, with significantly higher mean levels in the Northern District (Ca²⁺: 72 mg/L, p < 0.006; Mg²⁺: 34 mg/L, p < 0.001) and lowest levels in southern regions, particularly the Southern District (Ca²⁺: 39 mg/L, p < 0.001; Mg²⁺: 7 mg/L, p < 0.001) compared to the national average. Fluoride concentrations were generally low, with higher levels in northern regions (0.23 mg/L, p < 0.001) and lower levels in Tel Aviv (0.07 mg/L, p < 0.001) and Jerusalem (0.11 mg/L, p < 0.001). By predominant water source, Ca²⁺ and Mg²⁺ concentrations were lowest in DSW (Ca²⁺: 42 mg/L; Mg²⁺: 9 mg/L) and highest in groundwater supplies (Ca²⁺: 83 mg/L; Mg²⁺: 34 mg/L). Concentrations of F⁻ ranged from 0.12 mg/L in predominantly DSW to 0.23 mg/L in areas supplied primarily by groundwater. Conclusions: Ca²⁺ levels aligned with international reports, while Mg²⁺ levels, especially in desalination-reliant areas, remained consistently low. F⁻ concentrations stayed below both the recommended maximums and the optimal levels advised by the U.S. Public Health Service. As desalination efforts grow, concerns have been raised about the potential public health risks associated with low-mineral drinking water, particularly cardiovascular disease and bone disorders. Full article

Understanding how historical climatic oscillations and contemporary dispersal interact to shape genetic diversity is central to interpreting population structure in long-distance migratory birds. The White Stork (Ciconia ciconia) has a broad trans-Eurasian distribution, yet populations from the Caucasus region remain underrepresented in population genetic studies. Here, we investigate mitochondrial and nuclear genetic variation in breeding populations from Armenia, a region located at the junction of Europe and Southwest Asia. We analyzed sequence variation in the mitochondrial control region and COI gene together with a nuclear intron (SPIN) from 102 individuals sampled across northern, central, and southern Armenia and integrated these data with publicly available Eurasian sequences. Genetic diversity indices, haplotype networks, mismatch distributions, and hierarchical analyses of molecular variance were used to evaluate spatial genetic structure and demographic history. Armenian populations exhibited high mitochondrial haplotype diversity but heterogeneous nucleotide diversity, consistent with complex demographic histories. AMOVA revealed no significant genetic differentiation among Armenian populations (FST = 0.019, p = 0.226) or between Armenia and Europe (FCT = −0.021, p = 0.754), indicating that Armenian breeding populations form part of a single, well-connected Western Palearctic mitochondrial gene pool. Mismatch distributions revealed a consistent secondary peak across all three populations, suggesting demographic complexity that may reflect the retention of older mitochondrial lineage diversity, though this interpretation remains tentative given the limited discriminatory power of mismatch analyses alone and requires confirmation through expanded sampling and complete mitogenome sequencing. These results indicate that Armenian White Stork populations are genetically diverse and well-connected to the broader Western Palearctic population, while also carrying signatures of a complex demographic history potentially shaped by Pleistocene lineage divergence and post-glacial admixture. Our findings provide a regional genetic baseline for an understudied part of the species’ range and highlight the South Caucasus as a candidate area for future genomic studies integrating complete mitogenomes and genome-wide nuclear markers. Full article

The Loess Plateau in China is highly susceptible to frequent landslides and other geological disasters, which have led to substantial losses of natural and human resources and are frequently reported in the news media. Yuzhong County, located east of Lanzhou City, is a mountainous region with considerable development potential. On 7 August 2025, this area experienced a large-scale geological disaster characterized by a compound event involving both landslides and debris flows, resulting in nearly several hundred casualties. With the ongoing urban expansion of Yuzhong County in recent years, the prediction and prevention of geological disasters have become increasingly critical. This study employed three machine learning algorithms—Multiple Logistic Regression (LR), Random Forest (RF), and XGBoost (XG)—to assess landslide susceptibility in Yuzhong County. A total of 169 historical landslide points, supplemented by additional sites identified through field investigations, were compiled, along with 200 non-landslide locations. Multiple environmental factors were incorporated into the models to analyze landslide susceptibility across different areas. Because LR can effectively capture the generalized influence of precipitation variability, it was selected as the primary model for the final susceptibility mapping. To more accurately evaluate the impact of precipitation on landslide occurrence, average seasonal precipitation across the four seasons was used as a predictive factor. To refine the risk assessment at the township level, both raster-based and landslide-unit-based evaluation approaches were adopted. Overlay analyses were then performed by integrating urban infrastructure, population distribution, and predicted landslide hazard zones, while also accounting for the potential influence of extreme precipitation events. The results reveal that the mountainous areas in eastern Mapo Township, southern Xiaokangying Township, southern Xiaguanying Town, and the south-central part of Qingshuiyi Township are high-risk zones prone to group-occurrence landslide disasters. Full article

Nepal is a small, landlocked country with marked elevational variation from the Terai plains to the Himalayas. Here, four indigenous goat populations (Chyangra, Sinhal, Khari, and Terai) are raised at different elevations. This study aimed to clarify the genetic structure of these populations and how they are formed and propagated across the Himalayan region. We analyzed 136 Nepalese goats using mitochondrial (mt) DNA D-loop and sex-determining region Y (SRY) 3′-untranslated region (UTR) sequences, as well as 50 K SNP array data. The mtDNA haplogroups D (0.162) and G (0.03) were detected only in Chyangra, whereas haplogroup B was predominant in Sinhal (0.42), followed by Khari (0.260). Regarding SRY haplotypes, Y2B was detected in all populations, whereas Y1AB (0.42) was found only in Chyangra. Genome-wide SNP analysis showed that Chyangra was genetically related to Tibetan and Central Asian goats, while Terai resembled South Asian goats. Interestingly, Sinhal formed a distinct cluster, whereas Khari exhibited an admixed genetic structure. These findings suggest that Nepalese goats originate from at least three ancestral lineages and that an additional migration route may have existed through the southern Himalayas. Full article

The 4 km/15 min downward surface shortwave radiation (DSSR) product from Fengyun-4B (FY-4B)/AGRI shows great potential for solar energy assessment in China, but its applicability requires further validation. This study conducts a comprehensive evaluation of the FY-4B DSSR product over Guangxi for 2025, using ground-observed irradiance from a dense network of 101 photovoltaic (PV) power stations. The overall comparison shows a correlation coefficient (R) of 0.84, a root-mean-square error (RMSE) of 161.78 W/m², a relative prediction error (RPE) of 51.02%, and a mean bias error (MBE) of 56.23 W/m², indicating systematic overestimation. Seasonally, the largest discrepancies occur in spring (MBE = 85.27 W/m², RPE = 53.12%) and summer (R = 0.82, RMSE = 184.10 W/m²). Diurnally, retrievals are most reliable around 09:00–13:00 local time, deteriorating notably in the early morning and, especially, the afternoon and evening. Spatially, errors are larger in the hilly, elevated terrain of northwestern Guangxi (e.g., Hechi) than in flatter southern and coastal cities, with RPE rising from roughly 40–60% at lower elevations to around 80% above 600–700 m. Sky-condition classification confirms that data quality follows clear > cloudy > overcast sky, while AOD-binned analysis shows aerosol loading playing a secondary but non-negligible role, especially under high-AOD pollution events. Solar zenith angle (SZA) also strongly affects accuracy: R peaks around 0.75–0.8 in the 30–50° SZA range and drops below 0.4 beyond about 75°. This study offers the most spatially and dimensionally comprehensive validation of FY-4B DSSR over Guangxi to date, characterizing accuracy across seasonal, diurnal, spatial, cloud, aerosol, solar-geometry, and elevation dimensions using a denser ground-truth network than previously available, with direct implications for photovoltaic resource assessment and power forecasting in subtropical hilly regions. Full article