Search Results (81)

In order to determine the impact of urbanization on raptors in the semi-desert conditions of southwestern Kazakhstan, an analysis of the spatio-temporal distribution of raptors is presented for the first time based on the results of surveys of the avifauna of Kyzylorda. Eight species of raptors were recorded: field Hen Harrier (Circus cyaneus), Marsh Harrier (C. aeroginosus), Eurasian Sparrowhawk (Accipiter nisus), Long-Legged Buzzard (Buteo rufinus), Eurasian Buzzard (B. buteo), Steppe Eagle (Aquila nipalensis), Eurasian Hobby (Falco subbuteo), and Common Kestrel (F. tinnunculus). The probability of raptors being present was negatively associated with dense urban low-rise buildings with limited greenery in the bay and the new part of the city. At the same time, the dense urban development with little or no greenery in the old central part of the city provides adequate habitat (including a foraging base and nesting sites) for the Common Kestrel. Raptor presence was positively associated with the Syrdarya River floodplain and wasteland with small groups of trees and/or shrubs. The landfill site located on the north-eastern edge of the city serves as a feeding ground for the Long-Legged and Eurasian Buzzards, while the airport area is inhabited by the Eurasian Buzzard, Steppe Eagle, and Common Kestrel. Based on this study, we would recommend that enterprises (e.g., grain storage facilities, airports) and local executive bodies who are interested in the conservation of raptors and regulating the population of the pigeons around their territories should retain or plant more native vegetation and shrubs and preserve areas with green spaces. Full article

The Inner Mongolia Plateau (IMP), situated in the arid and semi-arid ecological transition zone of northern China, is particularly vulnerable to both climate change and human activities. Understanding the spatiotemporal vegetation dynamics and their driving forces is essential for regional ecological management. This study employs Sen’s slope estimation, BFAST analysis, residual trend method and Geodetector to analyze the spatial patterns of Normalized Difference Vegetation Index (NDVI) variability and distinguish between climatic and anthropogenic influences. Key findings include the following: (1) From 1982 to 2022, vegetation cover across the IMP exhibited a significant greening trend. Zonal analysis showed that this spatial heterogeneity was strongly regulated by regional hydrothermal conditions, with varied responses across land cover types and pronounced recovery observed in high-altitude areas. (2) In the western arid regions, vegetation trends were unstable, often marked by interruptions and reversals, contrasting with the sustained greening observed in the eastern zones. (3) Vegetation growth was primarily temperature-driven in the eastern forested areas, precipitation-driven in the central grasslands, and severely limited in the western deserts due to warming-induced drought. (4) Human activities exerted dual effects: significant positive residual trends were observed in the Hetao Plain and southern Horqin Sandy Land, while widespread negative residuals emerged across the southern deserts and central grasslands. (5) Vegetation change was driven by climate and human factors, with recovery mainly due to climate improvement and degradation linked to their combined impact. These findings highlight the interactive mechanisms of climate change and human disturbance in regulating terrestrial vegetation dynamics, offering insights for sustainable development and ecosystem education in climate-sensitive systems. Full article

Methane (CH₄) is a potent greenhouse gas with a significant impact on short- and medium-term climate forcing, and its atmospheric concentration has been increasing rapidly in recent decades. This study aims to analyze spatio-temporal patterns of atmospheric methane concentrations between 2019 and 2025, focusing on comparisons between regions characterized by high and low emission intensities. Level-3 XCH₄ data from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite were used, which were aggregated into seasonal and annual composites. High-emission regions, such as the Mekong Delta, Nile Delta, Eastern Uttar Pradesh and Bihar, Central Thailand, Lake Victoria Basin, and Eastern Arkansas, were contrasted with low-emission areas including Patagonia, the Mongolian Steppe, Northern Scandinavia, the Australian Outback, the Sahara Desert, and the Canadian Shield. The results show that high-emission regions exhibit substantially higher seasonal amplitude in XCH₄ concentrations, with an average seasonal variation of approximately 30.00 ppb, compared to 17.39 ppb in low-emission regions. Methane concentrations generally peaked at the end of the year (Q4) and reached their lowest levels during the first half of the year (Q1 or Q2), particularly in agriculturally dominated regions. Principal component and cluster analyses further confirmed a strong spatial differentiation between high- and low-emission regions based on both temporal trends and seasonal behavior. These findings demonstrate the potential of satellite remote sensing to monitor regional methane dynamics and highlight the need for targeted mitigation strategies in major agricultural and wetland zones. Full article

Punjab, the most populous province in Pakistan, is currently facing substantial electricity shortages that are adversely affecting both residential and industrial sectors. To address this issue, the Cholistan Desert presents a promising solution due to its high solar irradiance, making it an ideal location for solar energy production. This study aims to identify the most suitable area for solar photovoltaic (PV) power plants in the Cholistan Desert using Geographic Information System (GIS) and machine learning techniques. The analysis included field survey data encompassing 14 conditioning factors such as geophysical, socio-economic, and resource conditions. Three machine learning models were utilized: Random Forest, XGBoost, and Multilayer Perceptron (MLP). The Random Forest model demonstrated superior performance with an AUC of 0.92, and feature importance was measured through SHAP. The resulting suitability map indicates that Bahawalnagar in the eastern region and Bahawalpur in the central region have 10.50% and 11.06% of their areas classified as having a “high” and “very high” probability for solar PV installation, respectively. For stakeholders in the wind industry, these regions also present potential for wind farm feasibility due to favorable wind conditions and flat terrain. The methodology can be adapted to prioritize wind energy sites by incorporating factors such as land availability, wind direction, and other related factors. Co-locating solar and wind farms in these regions could optimize land use, enhance grid stability, and support Pakistan’s renewable energy targets. Future research integrating real-time solar and wind data could further refine site selection and support multi-source renewable energy planning, providing actionable insights for policymakers and investors. Full article

Flash floods are highly destructive natural disasters, particularly in arid and semi-arid regions like Egypt, where data scarcity poses significant challenges for analysis. This study focuses on the Wadi Al-Barud basin in Egypt’s Central Eastern Desert (CED), where a severe flash flood occurred on 26–27 October 2016. This flash flood event, characterized by moderate rainfall (16.4 mm/day) and a total volume of 8.85 × 10⁶ m³, caused minor infrastructure damage, with 78.4% of the rainfall occurring within 6 h. A significant portion of floodwaters was stored in dam reservoirs, reducing downstream impacts. Multi-source data, including Landsat 8 OLI imagery, ALOS-PALSAR radar data, Global Precipitation Measurements—Integrated Multi-satellite Retrievals for Final Run (GPM-FR) precipitation data, geologic maps, field measurements, and Triangulated Irregular Networks (TINs), were integrated to analyze the flash flood event. The Soil Conservation Service Curve Number (SCS-CN) method integrated with several hydrologic models, including the Hydrologic Modelling System (HEC-HMS), Soil and Water Assessment Tool (SWAT), and European Hydrological System Model (MIKE-SHE), was applied to evaluate flood forecasting, watershed management, and runoff estimation, with results cross-validated using TIN-derived DEMs, field measurements, and Landsat 8 imagery. The SCS-CN method proved effective, with percentage differences of 5.4% and 11.7% for reservoirs 1 and 3, respectively. High-resolution GPM-FR rainfall data and ALOS-derived soil texture mapping were particularly valuable for flash flood analysis in data-scarce regions. The study concluded that the existing protection plan is sufficient for 25- and 50-year return periods but inadequate for 100-year events, especially under climate change. Recommendations include constructing additional reservoirs (0.25 × 10⁶ m³ and 1 × 10⁶ m³) along Wadi Kahlah and Al-Barud Delta, reinforcing the Safaga–Qena highway, and building protective barriers to divert floodwaters. The methodology is applicable to similar flash flood events globally, and advancements in geomatics and datasets will enhance future flood prediction and management. Full article

Biological soil crusts (BSCs) play a fundamental role in desert ecosystems by stabilizing soil, cycling nutrients, and retaining moisture. However, the assembly processes governing bacterial communities within BSCs remain largely unknown. This study aimed to reveal the spatiotemporal variations in the bacterial community diversity, co-occurrence patterns, and ecological assembly processes of BSCs and their underlying soils across different desert and seasonal conditions. We systematically analyzed the spatial differences in the bacterial diversity, co-occurrence networks, and community assembly processes of BSCs and their underlying soils using samples collected at various soil depths from different BSC types in different deserts. We discovered that BSC type and soil depth were the primary factors driving bacterial community assembly, while seasonal effects were weaker and more indirect, and mainly regulated community dynamics through changes in resource availability and environmental conditions. The underlying soils of moss- and lichen-BSCs exhibited higher bacterial diversity and richness than those of algae BSCs. In contrast, cyano-BSCs exhibited a lower diversity, but Cyanobacteria demonstrated the highest photosynthetic function. Among the different deserts, the community assembly of samples from the eastern Inner Mongolia deserts was largely influenced by environmental selection, whereas stochastic processes were more prominent in the central and western desert regions. A β-nearest taxon index (βNTI) analysis indicated that stochastic processes were dominant in surface BSC samples, while environmental selection played a stronger role in deeper layers. A co-occurrence network analysis revealed that surface BSC samples had a high degree of network connectivity, with those from moss- and lichen-BSCs being particularly high, and they also exhibited high modularity and local clustering that promoted the functional stability of the microbial communities. This study revealed the integrated effects of soil depth, BSC type, desert type, and resource availability on microbial community assembly in desert ecosystems. These findings provide a theoretical basis for the microbial management of BSCs and scientific insights to support restoration strategies in desert ecosystems. Full article

The dune density is an important parameter for representing the characteristics of desert geomorphology, providing a precise depiction of the undulating topography of the desert. Owing to the limitations of estimation methods and data availability, accurately quantifying dune density has posed a significant challenge; in response to this issue, we propose an innovative model to estimate dune density using a dune vertex search combined with four-directional orographic spectral decomposition. This study reveals several key insights: (1) Taklimakan Desert distributes approximately 5.31 × 10⁷ dunes, with a linear regression fit R² of 0.79 between the estimated and observed values. The average absolute error and root mean square error are calculated as 25.61 n/km² and 30.48 n/km², respectively. (2) The distribution of dune density across the eastern, northeastern, southern, and western parts of the Taklimakan Desert is relatively lower, while there is higher dune density in the central and northern areas. (3) The observation data constructed using the improved YOLOv8s algorithm and remote sensing imagery effectively validate the estimation results of dune density. The new algorithm demonstrates a high level of accuracy in estimating sand dune density, thereby providing crucial parameters for sub-grid orographic parameterization in desert regions. Additionally, its application potential in dust modeling appears promising. Full article

The arid and semi-arid regions of northwest China are characterized by sparse vegetation and fragile ecosystems, making them highly susceptible to the impacts of climate change and human activities. Based on observed meteorological data, the Normalized Difference Vegetation Index (NDVI), the Lund–Potsdam–Jena dynamic global vegetation model (LPJ), a vegetation recovery potential model, and the MK trend test method, this study investigated the spatiotemporal distribution of vegetation recovery potential in northwest China and its relationship with global warming and increasing precipitation. The results indicated that vegetation in northwest China significantly increased, with greening closely related to trends in warming and wetting during 1982–2019. However, the vegetation recovery potential declined due to climate change. Central and southern Xinjiang and central Qinghai exhibited higher grassland recovery potential, while the central Gobi Desert areas of northwest China had lower recovery potential. The eastern part of northwest China was highly sensitive to drought, with moderate vegetation growth and recovery potential. Remote sensing data indicated a 2.3% increase in vegetation coverage in the region, with an average vegetation recovery potential index (IVCP) of 0.31. According to the results of LPJ model, the average vegetation recovery potential index for northwest China was 0.14, indicating a 1.1% improvement potential in vegetation coverage. Overall, climate warming and wetting facilitated vegetation recovery in northwest China, particularly in mountainous areas. The findings provide valuable insights for ecological restoration efforts and offer practical guidance for combating desertification and enhancing sustainable development. Moreover, these results underline the importance of incorporating vegetation recovery potential into regional policy-making to improve environmental resilience in the face of ongoing climate change. Full article

This research offers a fresh understanding of desertification in Turkmenistan by utilizing satellite remote sensing data and machine learning techniques. With 80% of its area covered by desert, Turkmenistan has particular difficulties as a result of the harsh effects of desertification, which are made worse by climate change and irresponsible land use. Despite the fact that desertification has been the subject of numerous studies conducted worldwide, this study is among the first to use a multi-index approach to specifically focus on Turkmenistan. It does this by integrating six important desertification indicators within machine learning models like random forest (RF), eXtreme Gradient Boosting (XGBoost), naïve Bayes (NB), and K-nearest neighbors (KNN). These indicators include the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Normalized Difference Moisture Index (NDMI), Bare Soil Index (BSI), Enhanced Vegetation Index (EVI), and land surface temperature (LST). Based on Sentinel-2 satellite data processed by the Google Earth Engine (GEE) platform, the findings show that the country’s northern, central, and eastern regions are undergoing severe desertification. Moreover, RF and XGBoost performed better than the straightforward models like NB and KNN in terms of accuracy (96% and 96.33%), sensitivity (both 100%), and kappa (0.901 and 0.9095). By concentrating on Turkmenistan, this study fills a significant gap and provides a framework for tracking desertification in similar regions around the world. Full article

Serpentinites make up one of the most significant rock units associated with primary suture zones throughout the ophiolite sequence of the Arabian–Nubian Shield. Wadi Sodmein serpentinites (WSSs) represent dismembered parts of the oceanic supra-subduction system in the central Eastern Desert of Egypt. In this context, we present whole-rock major, trace, and rare earth elements (REE) analyses, as well as mineral chemical data, to constrain the petrogenesis and geotectonic setting of WSS. Antigorite represents the main serpentine mineral with minor amounts of chrysotile. The predominance of antigorite implies the formation of WSS under prograde metamorphism, similar to typical metamorphic peridotites of harzburgitic protolith compositions. The chemistry of serpentinites points to their refractory composition with notably low Al₂O₃, CaO contents, and high Mg# (90–92), indicating their origin from depleted supra-subduction zone harzburgites that likely formed in a forearc mantle wedge setting due to high degrees of hydrous partial melting and emplaced owing to the collision of the intra–oceanic arc with Meatiq Gneisses. Spinels of WSS generally exhibit pristine compositions that resemble those of residual mantle peridotites and their Cr# (0.625–0.71) and TiO₂ contents (<0.05 wt%) similar to forearc peridotite spinels. Moreover, WSS demonstrates a significant excess of fluid mobile elements (e.g., Th, U, Pb), compared to high-field strength elements (e.g., Ti, Zr, Nb, Ta), implying an interaction between mantle peridotites and fluids derived from the oceanic subducted-slab. The distinct U-shaped REE patterns coupled with high Cr# of spinel from WSS reflect their evolution from mantle wedge harzburgite protolith that underwent extensive melt extraction and re-fertilized locally. Full article

This study integrates aeromagnetic data with geological information to develop a consistent interpretation of both shallow and deep structural frameworks at various depths in the Missiakat Al Jukh area, located in the Central Eastern Desert, Egypt. The research begins by processing reduced-to-the-north magnetic pole (RTP) anomalies, using Fast Fourier Transformation (FFT) techniques to distinguish between local residual structures and broader regional features. This multi-scale approach enables a more detailed understanding of the geological complexity in the region, revealing its subsurface structures. Advanced geophysical methods such as upward continuation, Euler deconvolution, source parameter imaging (SPI), and global particle swarm optimization (GPSO) were applied to further refine the determination of structural depths, offering critical insights into the distribution and orientation of geological features at varying depths. The study reveals dominant structural orientations aligned in the NNW-SSE, ENE-WSW, north–south, and east–west directions, reflecting the region’s complex tectonic history. This research is of great importance in terms of sustainability. By delivering detailed subsurface maps and providing more accurate depth estimates of basement rocks (between 0.6 and 1.3 km), it contributes to sustainable resource exploration in the region. A better understanding of the geological structure helps minimize the environmental impact of exploration by reducing unnecessary drilling and concentrating efforts on areas with higher potential. Additionally, the use of non-invasive geophysical techniques supports the transition toward more environmentally conscious exploration practices. The integration of these advanced methods promotes a more sustainable approach to mineral and resource extraction, which is crucial for balancing economic growth with environmental preservation in geologically sensitive areas. Ultimately, this work provides a thorough geological interpretation that not only aids future exploration efforts but also aligns with the global push for sustainable and eco-friendly resource management. Full article

This paper investigates the mineralogical and geochemical characteristics, as well as the possible sources, of gold, silver, platinum group elements (PGE), copper, and lead found in the beach sands along Egypt’s Mediterranean coast. Using scanning electron microscopy and electron probe micro-analysis, this study determines the morphology and micro-chemistry of separated grains to assess their economic potential and how various minerals respond to different transport distances. The analysis reveals that gold grains are of high purity (94.11 to 98.55 wt.%; average 96 wt.% Au) and are alloyed with Ag (1.28–2.32 wt.%) and Cu (0.16–3.15 wt.%). Two types of gold grains were identified, indicating differences in transport distances. Variations in morphology, surface features, inclusion types, rims, and chemistry of the native metals, including gold grains, suggest differences in composition, weathering degree, transport distance, deposit types, and host rocks. The average Ag concentration in gold grains (1.86 wt.%) suggests a link to mesothermal or supergene deposits. Most silver, copper, and lead grains are spherical, with some variations in shape. Silver grains have 71.66–95.34 wt.% Ag (avg. 82.67 wt.%). Copper grains have 92.54–98.42 wt.% Cu (avg. 94.22 wt.%). Lead grains contain 74.22–84.45 wt.% Pb (avg. 79.26 wt.%). The identified platinum group minerals (PGM) belong to the Pt–Fe alloys and sperrylite, both of which are PPGE-bearing minerals. These metals likely originate from the weathering of upstream Nile tributaries surrounded by igneous and metamorphic rocks from Ethiopian and Central African regions, with a minor contribution from the Egyptian Eastern Desert Mountains. Full article

The Neoproterozoic granitic rocks of Mount Abu Kibash and Tulayah in the central Eastern Desert of Egypt are of geodynamic interest and provide us with important information about the evolution and growth of the northern part of the Arabian–Nubian Shield (ANS) continental crust. They are primarily composed of granodiorites and syenogranites based on new field, mineralogical, and geochemical analyses. The granodiorites are marked by an enrichment of LILEs such as Sr, K, Rb, Ba compared to HFSEs like Nb, Ta, Ti and show a higher concentration of LREEs relative to HREEs. This composition suggests a subduction-related setting and aligns with the characteristics of subducted I-type granites in the ANS. Chemistry of the analyzed primary amphiboles in the investigated granodiorites support a calc-alkaline nature, mixed source and subduction-related setting. The granodiorites represent an early magmatic phase in this setting, likely formed from a mix of mantle-derived mafic magmas and lower crust material, with subsequent fractional crystallization. On the other hand, syenogranites exhibit high SiO₂ (72.02–74.02 wt%), total alkali (7.82–8.01 wt%), and Al₂O₃ (13.79–14.25 wt%) levels, suggesting their derivation from peraluminous (A/CNK > 1) parental magmas. Their REE-normalized patterns are flat with a pronounced negative Eu anomaly, typical of post-collisional A2-type granites worldwide. These rocks originated from the partial melting of a juvenile lower crustal source (tonalite) in a post-collisional setting, driven by lithospheric delamination that facilitated mantle upwelling and underplating to the lower crust. Interaction between the upwelled mantle and lower crust led to fertilization (enrichment with HFSE and alkalis) of the lithosphere before partial melting. Fractional crystallization coupled with less considerable crustal assimilation are the main magmatic processes during the evolution of these rocks. The transition from subduction to post-collisional setting was accompanied by crustal uplifting, thickening and extensional collapse of ANS continental crust that caused emplacement of large masses of A-type granites in the northern ANS. Full article

Gold mining in Egypt’s Central Eastern Desert (ECED) has a rich history dating back to the Old Kingdom period. In recent years, there has been renewed interest from international mining companies, and several potential areas for gold mining have been identified. Extensive studies have been conducted on the deposition and occurrence of gold in the region, identifying over 100 areas of deposition. Aeromagnetic and radioactive surveys have played a crucial role in locating gold occurrences in ECED by utilizing data from these techniques to identify potential gold deposits. This study utilized geophysical data, including total aeromagnetic intensity (TM) and radiometric data, to identify hydrothermal zones and locate potential areas of gold occurrence. The radiometric ternary map was used to refine the search for gold deposits. Magnetic data were analyzed using edge detection tools to determine the structural framework of the area, facilitating the identification of regions with a high potential for gold occurrence. By integrating these geophysical datasets, this study provided a comprehensive understanding of the geological features and potential for gold mineralization in the study area. The area is divided into four sections by three shear zones, with high magnetic anomalies observed in the southeastern part. The radiometric data revealed that gold occurrence is associated with hydrothermal alteration zones, identified using the K/Th ratio and radiometric ternary map. However, not all these zones contain gold, and the area’s structure and magnetic suitability must be considered when selecting suitable locations for gold extraction. The study area presents a promising opportunity for gold exploration, with the integration of edge detection and radiometric analysis being crucial in identifying suitable locations for exploration. Full article

Nowadays, dried lake beds constitute the largest source of saline dust storms, with serious environmental and health issues in the surrounding areas. In this study, we examined the spatial–temporal distribution of monthly and annual dust events of varying intensity (dust in suspension, blowing dust, dust storms) in the vicinity of the desiccated Urmia Lake in northwestern (NW) Iran, based on horizontal visibility data during 2009–2022. Dust in suspension, blowing dust and dust storm events exhibited different monthly patterns, with higher frequencies between March and October, especially in the southern and eastern parts of the Urmia Basin. Furthermore, the intra-annual variations in aerosol optical depth at 500 nm (AOD₅₅₀) and Ångström exponent at 412/470 nm (AE) were investigated using Terra/Aqua MODIS (Moderate Resolution Imaging Spectroradiometer) data over the Urmia Lake Basin (36–39°N, 44–47°E). Monthly distributions of potential coarse aerosol (AE < 1) sources affecting the lower troposphere over the Urmia Basin were reconstructed, synergizing Terra/Aqua MODIS AOD₅₅₀ for AE < 1 values and HYSPLIT_4 backward trajectories. The reconstructed monthly patterns of the potential sources were compared with the monthly spatial distribution of Terra MODIS AOD₅₅₀ in the Middle East and Central Asia (20–70°E, 20–50°N). The results showed that deserts in the Middle East and the Aral–Caspian arid region (ACAR) mostly contribute to dust aerosol load over the Urmia Lake region, exhibiting higher frequency in spring and early summer. Local dust sources from dried lake beds further contribute to the dust AOD, especially in the western part of the Urmia Basin during March and April. The modeling (DREAM8-NMME-MACC) results revealed high concentrations of near-surface dust concentrations, which may have health effects on the local population, while distant sources from the Middle East are the main controlling factors to aerosol loading over the Urmia Basin. Full article