Search Results (70)

Establishing robust geochemical baselines in the hyper-arid Atacama Desert remains challenging because of extreme climatic gradients, polymetallic mineralisation, and decades of intensive mining. To disentangle natural lithogeochemical signals from anthropogenic inputs, a region-wide, multi-institutional soil dataset (1404 samples; 32 elements) was compiled. The analytical workflow integrated compositional data analysis (CoDA) with isometric log-ratio transformation (ILR), principal component analysis (PCA), robust principal component analysis (RPCA), and consensus anomaly detection via hierarchical (HC) and spectral clustering (SC), applied both with and without spatial coordinates to capture compositional structure and geographic autocorrelation. Optimal cluster solutions differed among laboratory subsets (k = 2–17), reflecting instrument-specific biases. The dual workflows flagged 76 (geochemical-only) and 83 (geo-spatial) anomalies, of which 33 were jointly identified, yielding high-confidence exclusions. Regional baselines for 13 priority elements were subsequently computed, producing thresholds such as As = 66.9 mg · kg⁻¹, Pb = 53.6 mg · kg⁻¹, and Zn = 166.8 mg · kg⁻¹. Incorporating spatial variables generated more coherent, lithology-aligned clusters without sacrificing sensitivity to geochemical extremes (Jaccard index = 0.26). These findings demonstrate that a reproducible, compositional-aware machine learning workflow can separate overlapping geogenic and anthropogenic signatures in heterogeneous terrains. The resulting baselines provide an operational reference for environmental monitoring in northern Chile and a transferable template for other arid mining locations. Full article

In arid environments such as the Namib Desert, non-rainfall water sources—including dew and fog—constitute indispensable yet understudied components of the regional hydrological cycle. These moisture inputs play a critical role in sustaining ecological functionality and biogeochemical processes, but remain among the least quantified facets of desert ecohydrology. The present study investigates multi-year trends in morning dew formation within the Namib Desert, utilizing observations from the Gobabeb–Namib Research Institute between 2015 and 2022. Meteorological data from the Southern African Science Service Centre for Climate and Adaptive Land Management (SASSCAL), in conjunction with direct field observations of dew, were used to develop an empirical equation to estimate dew occurrence. A sensitivity analysis verified the robustness of this formulation, and subsequent validation using field data confirmed its reliability (84.84% accuracy). During this eight-year period, the annual number of days with morning dew decreased from 170 in 2015 to 140 in 2022, representing an overall decline of approximately 18%. However, the total daily dew occurrence across 24 h remained relatively constant, indicating that the observed decline is confined primarily to morning condensation events. Dew formation was most prevalent during the wet season (December–May). Both monthly and annual analyses revealed a discernible declining trend in morning dew occurrence across this hyperarid ecosystem (p < 0.05). This decline corresponded with a gradual increase in both air and soil temperatures (approximately +0.03 °C yr⁻¹) and a slight but consistent decrease in relative humidity (approximately −0.26% yr⁻¹) between 2015 and 2022. The principal drivers of this decline include rising soil and air temperatures and decreasing atmospheric humidity. The analysis further identified an inverse relationship between air temperature and dew formation, implying that climatic warming intensifies evaporative demand and thereby suppresses dew condensation. Random forest analysis identified soil temperature, air temperature, and relative humidity as the most important predictors influencing dew occurrence, whereas wind speed and direction played lesser roles. Collectively, these findings underscore the vulnerability of dew-dependent ecosystems to anthropogenic climate change and highlight the imperative to continue investigating non-rainfall moisture dynamics in desert environments. Full article

Monitoring ecosystem dynamics in arid regions requires robust indicators that can capture spatial heterogeneity and diverse ecological drivers. In this study, we introduce and evaluate two novel ecological indices: the Arid-region Remote Sensing Ecological Index (ARSEI), specifically designed for desert environments, and the Composite Remote Sensing Ecological Index (CoRSEI), which integrates both desert and non-desert systems. These indices are compared with the traditional Remote Sensing Ecological Index (RSEI) in the Tarim River Basin from 2000 to 2023. Principal component analysis (PCA) revealed that RSEI maintained the highest structural compactness (average PCA1 = 87.49%). In contrast, ARSEI (average PCA1 = 78.62%) enhanced sensitivity to albedo and vegetation (NDVI) in arid environments. Spearman correlation analysis further demonstrated that ARSEI was more strongly correlated with NDVI (ρ = 0.49) and precipitation (ρ = 0.62) than RSEI, confirming its improved responsiveness under water-limited conditions. CoRSEI exhibited higher internal consistency and spatial adaptability (mean values ranging from 0.45 to 0.56), with slight ecological improvements observed between 2000 and 2023. Ecological drivers varied across habitat types. In desert areas, evapotranspiration, precipitation, and soil moisture were the main determinants of ecological status, showing high coupling and synchrony. In non-desert regions, soil moisture and precipitation remained dominant, but vegetation indices and disturbance factors (e.g., fire density) exerted stronger long-term influences. Partial dependence analyses further confirmed nonlinear, region-specific responses, such as the threshold effects of precipitation on vegetation growth. Overall, our findings highlight the importance of differentiated ecological modeling. ARSEI enhances sensitivity in desert ecosystems, whereas CoRSEI captures landscape-scale variability across desert and non-desert regions. Both indices contribute to more accurate long-term ecological assessments in hyper-arid environments. Full article

Gulf cities have embarked on ambitious public transport infrastructure initiatives in recent decades to foster more livable and sustainable cities. This investigation explores the interpretations and implementation of Transit-Oriented Development (TOD) principles in two prototypical urban districts: Doha’s West Bay, Qatar, and Riyadh’s King Abdullah Financial District (KAFD), Saudi Arabia. By following a comparative case study approach, the study explores how retrofitted (West Bay) and purpose-built (KAFD) TOD configurations fare regarding land use mix, density, connectivity, transit access, and environmental responsiveness. The comparative methodology was selected to specifically capture the spatial, climatic, and socio-economic complexities of TOD implementation in hyper-arid urban environments. Based on qualitative evidence from stakeholder interviews, spatial assessments, and geospatial indicators—such as metro access buffers, building shape compactness, and TOD proximity classification—the investigation reflects both common challenges and localized adaptations in hot-desert Urbanism. It emerges that, while benefiting from integrated planning and multimodal connectivity, KAFD’s pedestrian realm is delimited by climatic constraints and inactive active transport networks. West Bay, on the other hand, features fragmented public spaces and low TOD cohesion because of automotive planning heritages. However, it holds potential for retrofit through infill development and tactical Urbanism. The results provide transferable insights that can inform TOD strategies in other Gulf and international contexts facing similar sustainability and mobility challenges. By finalizing strategic recommendations for urban livability improvement through context-adaptive TOD approaches in Gulf cities, the study contributes to the wider discussion of sustainable Urbanism in rapidly changing environments and supplies a reproducible assessment frame for future TOD planning. This study contributes new knowledge by advancing a context-adaptive TOD framework tailored to the unique conditions of hyper-arid Gulf cities. Full article

As global urbanization accelerates in ecologically fragile regions, Nature-Based Solutions (NBS) have emerged as a critical paradigm for integrating environmental sustainability with urban resilience. Particularly in hyper-arid environments, the deployment of NBS must navigate unique climatic, hydrological, and socio-political complexities. This paper advances a conceptual framework that synthesizes the International Union for Conservation of Nature’s (IUCN) tripartite typology—protection, sustainable management, and restoration/creation—within a broader systems-oriented governance lens. By engaging with international precedents and context-specific urban dynamics, the study explores how adaptive, multiscale strategies can translate ecological principles into actionable urban design and planning practices. Through a comparative lens and grounded regional inquiry, the research identifies critical leverage points and institutional enablers necessary to operationalize NBS under desert constraints. While highlighting both the structural potential and the contextual limitations of existing initiatives in the Eastern Province of Saudi Arabia, the analysis underscores the necessity of coupling typological coherence with flexible regulatory and participatory mechanisms. Empirical findings from the Saudi case reveal persistent institutional fragmentation, heavy reliance on top-down implementation, and limited hydrological monitoring as key constraints, while also pointing to emerging governance mechanisms under Vision 2030—such as cross-sectoral coordination and pilot participatory frameworks—that can support the long-term viability of NBS in hyper-arid cities. Building on these insights, the study distills a set of strategic lessons that provide clear guidance on hydrological integration, adaptive governance, and socio-cultural legitimacy, offering a practical roadmap for operationalizing NBS in desert urban contexts. Full article

Environmental stress drives plant communities toward conservative ecological strategies through increased wood density (WD) within the Wood Economics Spectrum (WES). However, hyper-arid regions like the Coastal Atacama Desert (CAD) challenge this pattern, where woody plants exhibit acquisitive traits and decreased WD with increasing aridity. The underlying anatomical mechanisms remain poorly understood. This study examined how extreme aridity in the CAD shapes wood economics strategies, testing whether anatomical changes prioritize hydraulic safety over efficiency within the WES. Six shrub communities along an aridity gradient were sampled, measuring composition and abundance of 29 species across 20 plots per site. Community-weighted means of eight wood traits—including WD, vessel density/diameter, parenchyma fraction, fiber fraction, and lumen fractions—were analyzed. PCA, triangular and linear models assessed trait variation along the aridity gradient. Unexpectedly, WD increased at both gradient extremes but through different tissue compositions, with no clear shift from acquisitive to conservative strategies. Instead, vessel traits (density and diameter) were key, reflecting an independent hydraulic safety–efficiency trade-off. PC2 strongly correlated with aridity, showing reduced vessel size and increased density under greater aridity. Findings reveal that hyper-aridity disrupts traditional wood economics, with hydraulic adaptation—not WD-mediated resource use—driving community assembly. This highlights the dominance of safety–efficiency trade-offs in structuring shrub communities in extreme deserts, emphasizing hydraulic traits over conventional resource strategies. Full article

This study analyzes spatiotemporal aridity dynamics in Central Kazakhstan (1960–2022) using a monthly Aridity Index (AI = P/PET), where P is precipitation and PET is potential evapotranspiration, Mann–Kendall trend analysis, and climate zone classification. Results reveal a northeast–southwest aridity gradient, with Aridity Index ranging from 0.11 to 0.14 in southern deserts to 0.43 in the Kazakh Uplands. Between 1960–1990 and 1991–2022, southern regions experienced intensified aridity, with Aridity Index declining from 0.12–0.15 to 0.10–0.14, while northern mountainous areas became more humid, where Aridity Index increased from 0.40–0.44 to 0.41–0.46. Seasonal analysis reveals divergent patterns, with winter showing improved moisture conditions (52.4% reduction in arid lands), contrasting sharply with aridification in spring and summer. Summer emerges as the most extreme season, with hyper-arid zones (8%) along with expanding arid territories (69%), while autumn shows intermediate conditions with notable dry sub-humid areas (5%) in northwestern regions. Statistical analysis confirms these observations, with northern areas showing positive Aridity Index trends (+0.007/10 years) against southwestern declines (−0.003/10 years). Key drivers include rising temperatures (with recent degradation) and variable precipitation (long-term drying followed by winter and spring), and PET fluctuations linked to temperature. Since 1991, arid zones have expanded from 40% to 47% of the region, with semi-arid lands transitioning to arid, with a northward shift of the boundary. These changes are strongly seasonal, highlighting the vulnerability of Central Kazakhstan to climate-driven aridification. Full article

The spatial distribution of ephemeral and perennial dryland plant species is increasingly modified and restricted by ever-changing climates and development expansion. At the interface of biodiversity conservation and developmental planning in desert landscapes is the growing need for adaptable tools in identifying and monitoring these ecologically fragile plant assemblages, habitats, and, often, heritage sites. This study evaluates usage of Sentinel-2 time series composite imagery to discriminate vegetation assemblages in a hyper-arid landscape. Spatial predictor spaces were compared to classify different vegetation communities: spectral components (PCs), vegetation indices (VIs), and their combination. Further, the uncertainty in discriminating field-verified vegetation assemblages is assessed using Shannon entropy and intensity analysis. Lastly, the intensity analysis helped to decipher and quantify class transitions between maps from different spatial predictors. We mapped plant assemblages in 2022 from combined PCs and VIs at an overall accuracy of 82.71% (95% CI: 81.08, 84.28). A high overall accuracy did not directly translate to high class prediction probabilities. Prediction by spectral components, with comparably lower accuracy (80.32, 95% CI: 78.60, 81.96), showed lower class uncertainty. Class disagreement or transition between classification models was mainly contributed by class exchange (a component of spatial allocation) and less so from quantity disagreement. Different artefacts of vegetation classes are associated with the predictor space—spectral components versus vegetation indices. This study contributes insights into using feature extraction (VIs) versus feature selection (PCs) for pixel-based classification of plant assemblages. Emphasising the ecologically sensitive vegetation in desert landscapes, the study contributes uncertainty considerations in translating optical satellite imagery to vegetation maps of arid landscapes. These are perceived to inform and support vegetation map creation and interpretation for operational management and conservation of plant biodiversity and habitats in such landscapes. Full article

A novel actinobacterial strain, designated E54^T, was isolated from a hyper-arid desert soil sample collected from the Kumtagh Desert in Dunhuang, Gansu Province, China. Phylogenetic analysis based on 16S rRNA gene sequences placed strain E54^T within the genus Lentzea, showing highest similarity to Lentzea waywayandensis DSM 44232^T (98.9%) and Lentzea flava NBRC 15743^T (98.5%). However, whole-genome comparisons revealed that the average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between E54^T and these related strains were below the thresholds for species delineation. Strain E54^T exhibited typical morphological characteristics of the genus Lentzea, forming a branched substrate. It grew optimally at 28–30 °C, pH 7.0–9.0, and tolerated up to 10% NaCl. The cell wall contained meso-diaminopimelic acid, the predominant menaquinone was MK-9(H₄), and major fatty acids included iso-C_16:0. The polar lipid profile comprised diphosphatidyl glycerol, phosphatidyl ethanolamine, phosphatidyl inositol, hydroxyphosphatidyl ethanolamine, and an unidentified lipid. The characteristic amino acid type of the cell wall was meso-DAP. Whole-cell hydrolysis experiments revealed the characteristic cell wall sugar fractions: ribose and galactose. The genome of strain E54^T is approximately 8.0 Mb with a DNA G+C content of 69.38 mol%. Genome mining revealed 39 biosynthetic gene clusters (BGCs), including non-ribosomal peptide synthetases (NRPS), polyketide synthases (PKS), terpenes, and siderophores. Comparative antiSMASH-based genome analysis across 38 Lentzea strains further demonstrated the genus’ remarkable biosynthetic diversity. NRPS and type I PKS (T1PKS) were the most prevalent BGC types, indicating a capacity to synthesize structurally complex and pharmacologically relevant metabolites. Together, these findings underscore the untapped biosynthetic potential of the genus Lentzea and support the proposal of strain E54^T as a novel species. The strain E54^T (=JCM 34936^T = GDMCC 4.216^T) should represent a novel species, for which the name Lentzea xerophila sp. nov. is proposed. Full article

In recent decades, the use of off-road vehicles (ORVs) for challenging outdoor trips has increased significantly worldwide, impacting soil, vegetation, and wildlife. This study was conducted in Sde Zin, Israel, a hyper-arid desert zone. The area has a high concentration of trails created unintentionally over the years by ORVs. The study sought to examine whether the degraded trails will be restored naturally or if there is a need for active intervention. Five ORV trails were selected, with a plot of 40 × 15 m in each trail, comprising three subplot treatments: one session of disk tillage, no tillage, and an adjacent control subplot. Soil and vegetation parameters were measured for two consecutive years. The results indicated that the measured soil parameters did not differ between treatments except for the degree of soil compaction, which was a significant factor in plant survival and restoration. The highest H′ Shannon diversity was found in the disk-tillage treatment, where the plant assemblage differed from that of the non-tillage and control subplots. The conclusion derived from this study is that active management to prevent soil compaction is needed in severely degraded desert areas to stimulate soil and vegetation restoration processes. Full article

Surface urban heat island (SUHI) effects are intensifying in arid desert cities due to rapid urban expansion, limited vegetation, and increasing impervious and barren land surfaces. This leads to serious ecological and socio-environmental challenges in cities. This study investigates the relationship between landscape composition and land surface temperature (LST) in Phoenix and Tucson, two rapidly growing cities located in the Sonoran Desert of the southwestern United States. Landsat-9 OLI-2/TIRS-2 satellite imagery was used to derive the LST value and calculate spectral indices. A multi-resolution grid-based approach was applied to assess spatial correlations between land cover and mean LST across varying spatial scales. The strongest positive correlations were observed with barren land, followed by impervious surfaces, while green space showed a negative correlation. Furthermore, the Urban Thermal Field Variation Index (UTFVI) and the Ecological Evaluation Index (EEI) assessments indicated that over one-third of both cities are exposed to strong SUHI effects and poor ecological quality. The findings highlight the critical need for ecologically sensitive urban planning, emphasizing the importance of the morphological structure of cities, the necessity of planning holistic blue–green infrastructure systems, and the importance of reducing impervious surfaces to decrease LST, mitigate SUHI and SUHI impacts, and increase urban resilience in desert environments. These results provide evidence-based guidance for landscape planning and climate adaptation in hyper-arid urban environments. Full article

The densities of carbon, nitrogen, and phosphorus (C-N-P) reflect the adaptation and response of desert plants to hyper-arid environments. However, the allocation strategies for biomass and C-N-P densities among various plant life forms remain poorly understood. This study involved the collection of samples representing both aboveground and belowground biomass (to depths of 200 cm) from three desert plant species—both herbaceous and shrubby—and evaluating their C-N-P densities. The investigation focused on the distribution strategies and drivers influencing total C-N-P densities within the plant–soil system. The results indicated that the biomass of the shrub Tamarix ramosissima (8.88 ± 1.22 kg m⁻²) was significantly greater than that of the herbaceous plants Alhagi sparsifolia (0.96 ± 0.15 kg m⁻²) and Karelinia caspia (0.72 ± 0.09 kg m⁻²). The total C density among the three species was observed as follows: T. ramosissima (9.26 ± 0.99 kg m⁻²) > A. sparsifolia (6.21 ± 0.85 kg m⁻²) > K. caspia (6.18 ± 1.12 kg m⁻²). Notably, no significant differences were detected in the total N and P densities across the species. Additionally, for A. sparsifolia and K. caspia, the roots exhibited greater biomass and C-N-P densities. Further analysis revealed that soil pools accounted for 56.34–95.10% of total C density, 90.39–98.63% of total N density, and 99.86–99.97% of total P density in the plant–soil system. The order of total C-N-P densities was established as C > P > N, decoupling total P density from other environmental factors. Total C and N densities in the three plant species were predominantly influenced by soil physicochemical properties, with biotic factors and microbial biomass playing secondary roles. This study improves the understanding of C-N-P densities strategies of dominant vegetation for restoration and sustainable management in hyper-arid deserts. Full article

This research addresses the critical issue of urban heat islands (UHI), in which urban areas experience significantly higher temperatures than their surroundings, adversely affecting human comfort and well-being. Focusing on Inglewood, a city neighboring Los Angeles, California, and Phoenix, Arizona, this study uses a comprehensive methodology involving microclimate analysis-based Universal Thermal Climate Index (UTCI) calculations to assess the impact of horizontal green surfaces and different levels of tree canopies on outdoor thermal stress mitigation. Phoenix was selected due to its hyper-arid desert climate, providing a contrasting context to assess the effectiveness of green infrastructure under extreme heat conditions. The results demonstrate that these interventions effectively reduce strong and moderate heat stress levels (32 °C < UTCI < 38 °C and 26 °C < UTCI < 32 °C); the model with maximum tree canopy achieved an 18.48% reduction in strong heat stress in Inglewood, while combined interventions led to a maximum reduction of 18.92%. However, the findings also reveal that under extreme heat conditions, particularly in hyper-arid environments such as Phoenix, the interventions may have a limited effect, with localized increases in extreme heat stress attributed to microclimate dynamics, reduced vegetation cooling efficiency, and modeling limitations. Despite these challenges, the overall reduction in average UTCI values underscores the potential of integrated green infrastructure strategies for mitigating urban heat stress. This study provides urban planning strategies for integrating these interventions to create more sustainable and resilient urban environments, supporting policymakers and urban planners in their efforts to reduce the effects of UHI. Full article

Precipitation events have been occurring more frequently in the hyper-arid region of the Taklamakan Desert (TD) under recent climate change. However, in this water-limited environment, the microphysical characteristics of precipitation, as well as their link to rainfall intensity, remain unclear. To address this, this study utilizes dual-frequency precipitation radar (DPR) data of the Global Precipitation Measurement (GPM) satellite from 2014 to 2023 to analyze the microphysical characteristics of different precipitation types (stratiform and convective) in the TD during the summer. The results show that liquid water path (LWP) is a key factor influencing precipitation type: when LWP is insufficient, stratiform precipitation is more likely to occur (84.1%), while convective precipitation is difficult to occur (15.9%). Microphysical process analysis indicates that in convective precipitation, abundant low-level moisture leads to the growth of liquid particles primarily through the collision–coalescence process (59.7%), resulting in larger raindrop diameters (1.7 mm) and lower concentrations (31.9 mm⁻¹ m⁻³). In contrast, stratiform precipitation, with limited LWP, primarily involves the melting and breaking-up of high-level ice-phase particles, leading to smaller raindrop diameters (1.2 mm) and higher concentrations (34.3 mm⁻¹ m⁻³). The warm rain process plays a significant role in raindrop formation in both types of precipitation. The greater (lesser) the amount of LWP, the larger (smaller) the contribution of collision–coalescence (break-up) processes, and the larger (smaller) the raindrop diameter and precipitation intensity. Full article

Glacial retreat is a major global challenge, particularly in arid and semi-arid regions where glaciers serve as critical water sources. This research focuses on glacial retreat and its impact on land cover and land use changes (LULC) in the Barroso Mountain range, Tacna, Peru, which is a critical area for water resources in the hyperarid Atacama Desert. Employing advanced remote sensing techniques through the Google Earth Engine (GEE) cloud computing platform, we analyzed historical trends (1985–2022) using Landsat satellite imagery. A normalized index classification was carried out to generate LULC maps for the years 1986, 2001, 2012, and 2022. Future projections until 2042 were developed using Cellular Automata–Markov (CA–Markov) modeling in QGIS, incorporating six predictive environmental variables. The resulting maps presented an overall accuracy (OA) greater than 83%. Historical analysis revealed a dramatic glacier reduction from 44.7 km² in 1986 to 7.4 km² in 2022. In contrast, wetlands expanded substantially from 5.70 km² to 12.14 km², indicating ecosystem shifts potentially driven by glacier meltwater availability. CA–Markov chain modeling projected further glacier loss to 3.07 km² by 2042, while wetlands are expected to expand to 18.8 km² and bodies of water will reach 4.63 km². These future projections (with accuracies above 84%) underline urgent implications for water management, environmental sustainability, and climate adaptation strategies, particularly with regard to downstream hydrological risks and ecosystem resilience. Full article