Search Results (6,775)

Soil salinization threatens agricultural sustainability in arid zones, yet quantitative attribution of its spatiotemporal dynamics to multi-source drivers remains scarce at regional scales. To address this, we developed an explainable framework merging Sentinel-1/2, ERA5-Land, and topographic-hydrological indices with XGBoost, trained under weak supervision with proxy labels and independently validated using field-measured ECe. A 7-group, 44-feature ensemble with spatial block 5-fold cross-validation ensured robust assessment. SHapley Additive exPlanations (SHAP) quantified driver contributions and enabled a novel dominant driver zoning (DDZ) framework. Monitoring the Hexi Corridor and Tarim Basin (2017–2024) revealed contrasting trajectories: Hexi’s dynamics were primarily climate-driven (Aridity Index), whereas 19.2% of Tarim showed significant salinization along oasis–desert margins co-dominated by elevation, soil indices, and temperature. The model achieved spatial cross-validation R² values around 0.65. DDZ mapping showed climate dominance in 98.2% of Hexi compared to 76.5% in Tarim, where terrain and optical factors were more influential. The weak supervision strategy overcomes scarce in-situ measurements, while the DDZ maps identified that Land-use-dominated zones recorded the highest salinity, offering clear directives for targeted salinity control in arid basins. Full article

The objective of this study was to evaluate the potential of age Opuntia-derivated digestate (OpDcm) as a nutrient source for photosynthetic microbial consortia (PMC), aiming to reduce dependence on mineral media and promote the valorization of locally available biomass in arid and semi-arid regions. Batch cultures were performed in bubble column photobioreactors (BCPBR) and open raceway (ORPBR) photobioreactors using different proportions of OpDcm and BG11₀ to assess biomass production, chlorophyll a dynamics, and physicochemical responses of a PMC dominated by Nostoc sp. Chemical characterization showed that OpDcm contained higher levels of K, Ca, Mg, and Mn than BG11₀, providing a robust ionic matrix for initial growth; however, potential limitations in P, Mg, and Fe were identified. In both BCPBR and ORPBR systems, OpDcm demonstrated nutrient compositions that stimulated biomass production in the PMC at levels comparable to those achieved with BG11₀ medium. Statistical analyses showed that specific treatments, particularly T1 (10% OpDcm in BCPBR) and T3 (10% OpDcm + 2.5% BG11₀ in ORPBR), produced biomass yields similar to or higher than those obtained with the conventional BG11₀ medium. However, chlorophyll a concentration was lower in OpDcm treatments due to limited light transmission and micronutrient constraints. The N–NH₄⁺ dynamics in BCPBR and ORPBR exhibited pronounced variability among the evaluated culture media, spanning from negligible changes (<1 mg L⁻¹) over the entire cultivation period to sustained ammonium production rates of 2–3 mg L⁻¹ day⁻¹. Morphological analysis confirmed a consortium dominated by Nostoc sp., supported by pH values within the optimal range (8–9). Overall, the use of age-Opuntia-derived digestates demonstrated it can serve as a partial or total substitute for a low-cost nutrient source for cyanobacterial cultivation, underscoring their relevance to circular bioeconomy strategies for producing photosynthetic biomass. Full article

Groundwater is one of the key factors affecting the changes and evolution of surface processes in arid regions, determining the direction and scope of the evolution of surface eco-hydrological processes. To achieve sustainable water resource management in arid areas, this study aims to systematically explore the dynamic changes in groundwater level and their ecological effects on the basis of multi-source remote sensing data by multivariate statistical methods. The results show that groundwater levels in the Bayin River Basin increased from 2895.35 m in 2005 to 2906.75 m in 2022 at a rate of 6.7 m/decade, driven by increased runoff and irrigation. Conversely, groundwater levels in urbanized areas near Delingha City slightly decreased by approximately 0.3 m/decade, with a general west-to-east declining spatial gradient. These changes have generated cascading ecological effects. Overall, rising groundwater has coincided with increased vegetation index, wetland extent, and soil moisture. Annual average NDVI rose from 0.18 in 2000 to 0.23 in 2022, an increase of 27.7%, and wetland area expanded from 349.25 km² in 2005 to 355.25 km² in 2022. Soil moisture content showed an insignificant upward trend form 0.14% in 2003 to 0.15% in 2022, with the slope of 0.01%/yr. However, soil salinization has exhibited an aggravating trend, with salinization index (SI) values of 0.25, 0.26, and 0.31 in 2000, 2010, and 2020, respectively. Affected by human activities and geological constraints, the ecological effects associated with groundwater level changes display pronounced regional heterogeneity. This study provides a solid basis for regional water resource regulation and further quantification of water conveyance benefits. Full article

Ecosystem service assessment provides a critical basis for optimizing regional ecological management and promoting sustainable development. From the water–land–carbon coupling perspective, this study established a technical framework for quantifying individual services, coupling a composite index, and analyzing multidimensional driving mechanisms. The InVEST model was applied to quantify three core ecosystem services: water yield, habitat quality, and carbon storage. A Composite Ecosystem Service Index (CESI) was constructed through normalization and weighted summation. Multidimensional driving factors were identified using the Optimal Parameter-Based Geographical Detector. Taking Ningxia during 2004–2024 as the study area, the results showed that the CESI exhibited a fluctuating upward trend with significant spatial heterogeneity, characterized by a south–high and north–low pattern. Land use transitions were dominated by bidirectional conversions between cropland and grassland, while impervious area expanded rapidly and barren land decreased overall. The spatial differentiation of CESI was jointly controlled by natural and anthropogenic factors, with land use type, precipitation, and digital elevation model showing the strongest explanatory power, and all two-factor interactions displaying pronounced enhancement effects. This study provides a reproducible framework for ecosystem service assessment in arid and semi-arid regions, supporting ecological restoration, land use optimization, and the coordinated development of ecology and economy under water–land–carbon synergy. Full article

Groundwater is the primary source of livestock watering across the arid pasturelands of western Kazakhstan, yet no systematic field hydrochemical assessment has been published for this region in over 40 years. This study presents the first systematic field-based hydrochemical characterisation of groundwater sources used for pasture livestock watering in the West Kazakhstan Region and Aktobe Region, filling a critical data gap that has persisted since the Soviet era. Specifically, it characterises the hydrochemistry, water quality, and infrastructure condition of groundwater sources, and evaluates the groundwater resource potential against current and projected livestock water demand. A total of 139 groundwater samples were collected along 11,182 km of field routes during May–July 2025, and analysed for 25 physicochemical parameters; hydrochemical classification was performed using AquaChem 11, and spatial analysis was conducted in ArcGIS 10.8. The groundwater chemistry distribution is bimodal: fresh bicarbonate-calcium-magnesium waters (TDS < 3.0 g/L) constitute approximately 80% of samples, while highly mineralised chloride-sulphate-sodium waters (TDS up to 9.91 g/L) occur in salt-dome-influenced discharge zones. Nitrate concentrations exceeded 50 mg/L in 23–36% of samples, with maxima of 635 mg/L, reflecting intensive anthropogenic contamination near livestock facilities. Predictive exploitable fresh groundwater resources exceed current livestock demand by a factor of 162. The principal constraint on pasture water supply is not resource scarcity but the non-operational status of 51–75% of inspected watering infrastructure, a legacy of post-Soviet institutional collapse that requires urgent rehabilitation. Full article

The management of water resources is a critical factor in the emergence of civilizations, particularly in arid regions like the Arabian Peninsula. The ancient Marib Dam represents a systematic application of hydraulic planning within the Sabaean civilization. This study analyzes the scientific rationale behind the dam’s site selection by assessing key hydrological and geomorphological factors using Geographic Information Systems (GISs) and Weighted Overlay Analysis (WOA). The analysis revealed that the dam’s location precisely corresponds with a (very high) potential runoff accumulation zone, a critical area constituting only 0.8% of the total landscape studied. By providing this quantitative assessment, this study moves beyond historical interpretation to offer the first geospatial evidence that the dam’s site selection was deliberate and quantitatively informed, establishing a replicable model for the field of archaeohydrology. Full article

Restoration of degraded shrublands is a major challenge for combating desertification in arid and semi-arid regions. Caragana korshinskii Kom., a dominant sand-fixing shrub widely planted in northern China, often shows growth decline and structural degradation as stand age increases. Stubble management is widely used to rejuvenate degraded shrublands; however, its influence on nutrient cycling and carbon-nitrogen-phosphorus (C-N-P) stoichiometric coupling within the leaf-soil system remains unclear. Here, we conducted a two-factor field experiment in a 30-year-old degraded C. korshinskii plantation in the Kubuqi Desert, northern China, manipulating stubble height and stubble density. Moderate stubble height (10 cm) significantly increased leaf N concentration (27.37 g kg⁻¹) and improved soil C and N availability, whereas higher stubble height (20 cm) led to elevated leaf N:P ratios (24.2), indicating stronger phosphorus limitation. In addition, all stubble density treatments significantly reduced leaf C:N, C:P, and N:P ratios. Among them, the two stubbled after one retained exhibited the most pronounced effect, with C:N and C:P decreasing to 14 and 273, respectively, and N:P to 20, suggesting an improved nutrient balance and allocation efficiency. Multivariate analyses showed that lower stubble heights combined with alternate-plant stubble patterns (H2D1 and H2D2) enhanced leaf-soil nutrient coupling and promoted coordinated recovery of C-N-P stoichiometry during regeneration. Overall, stubble management regulates shrub rejuvenation mainly by modifying leaf-soil nutrient coupling rather than single-element responses. It is recommended that, in the management of degraded C. korshinskii shrublands, a stubble height of approximately 10 cm combined with staggered cutting (alternate-plant or every two plants) be prioritized as an optimized management regime. Full article

Accurate evapotranspiration (ET) estimation is critical for sustainable water management in arid environments. This study estimates actual ET over the Al-Hofuf region, Al-Ahsa Oasis, Saudi Arabia, during 2024 using a cloud-based remote sensing approach. Landsat 9 Level-2 imagery was combined with ERA5-Land meteorological data to quantify spatial and temporal ET variations across a 25 km buffer. Vegetation dynamics were characterized using the Normalized Difference Vegetation Index (NDVI) to derive crop coefficients (Kc) within a Kc–ET₀ framework, where reference ET (ET₀) was obtained from ERA5-Land potential evaporation. All processing utilized Python (Version 3.14) on Google Colab and Google Earth Engine for scalable computation. Eighty-eight cloud-free Landsat 9 scenes were processed following cloud and shadow masking. Mean NDVI, Kc, and daily ET values were compiled into a comprehensive time-series dataset. Model performance was evaluated through cross-validation with MODIS MOD16A2 and internal consistency checks, demonstrating strong statistical agreement (R² = 0.82, NSE = 0.71, PBIAS = +8.3%). Results revealed pronounced seasonal variability closely linked to vegetation activity and atmospheric demand, with peak ET occurring during summer months (June–July: 7.2–7.5 mm day⁻¹) and minima in winter (January–February: 2.0–2.6 mm day⁻¹). Findings demonstrate that cloud-based techniques provide reliable, cost-effective ET monitoring in data-scarce, groundwater-dependent regions. Validation confirms Kc-ET₀ estimates reliably capture spatial and temporal patterns, supporting practical irrigation management applications. This approach aids precision irrigation and long-term water sustainability planning in Al-Hofuf, contributing significantly to national water conservation objectives under Saudi Arabia’s Vision 2030 and National Water Strategy. Full article

Optimizing fertilizer management is crucial for increasing crop yields while reducing environmental impact. However, traditional methods rely on extensive field trials, which are costly and limit their scalability. To overcome these limitations, this study developed data-driven yield prediction models (YPM) for wheat, rice, and maize by integrating multiple feature selection and machine learning algorithms with explainable ensemble learning, namely stacking regression (SR) and voting mean (VM). The optimal YPM was subsequently combined with the hybrid optimization strategy to construct an intelligent fertilization decision model (IFDM), and the economic–environmental benefits were subsequently evaluated. The best-performing models were SHAP-SR for wheat and rice and GBM-SR for maize, achieving R² values of 0.79, 0.69, and 0.67, and RMSEs of 681.69, 725.35, and 1091.49 kg ha⁻¹, respectively. Based on the IFDM, the recommended application ranges for nitrogen (N), phosphorus (P₂O₅), and potassium (K₂O) were as follows: for wheat, 122.1–256.3, 45.4–98.2, and 30.6–60.7 kg ha⁻¹; for rice, 170.8–261.2, 55.1–91.4, and 40.6–98.5 kg ha⁻¹; and for maize, 157.5–293.4, 84.2–156.4, and 30.1–62.7 kg ha⁻¹. Simulation-based evaluation suggested that adopting these recommendations could potentially increase average yields by 9.2–12.4% and enhance economic–environmental benefits by 32.86–97.73% across the three crops. This study indicates that coupling interpretable ensemble learning with a hybrid optimization strategy can support efficient decision-making for field-scale fertilization and provides a data-driven and cost-effective approach for precision fertilization, with potential applicability to arid agricultural regions under similar agro-ecological conditions. Full article

As urban areas expand, the sustainable management of municipal water becomes a critical challenge, especially in arid and semi-arid regions facing severe water scarcity. Accurate assessment of urban plant water requirements (PWR) is essential for developing sustainable landscape architecture and resilient green infrastructure. In this study, a new quantitative equation (PWR_q) was developed as a regional proof of concept to adjust reference evapotranspiration estimates for hyper-arid conditions. A Tree Morphology Coefficient (K_tm) is introduced to combine canopy features (form, height) and leaf traits (size, density) with an updated drought-resistance coefficient (K_dr). Field measurements of 277 mature trees, representing 27 native and introduced species in Riyadh and Jeddah, Saudi Arabia, were analyzed. The framework explicitly includes an empirical multiplier to account for extreme urban heat island (UHI) effects and aerodynamic canopy scaling. Instead of direct empirical validation, the PWR_q model was benchmarked against established reference indices: Water Use Classification of Landscape Species (WUCOLS) and Simplified Landscape Irrigation Demand Estimation (SLIDE), showing strong alignment with established categorical indices and structural traits. The results confirm that the morphology-based method effectively makes previously subjective classifications objective. Notably, the quantitative assessment found that the dominant introduced species require about 3.5 times more water than native species. As a proof of concept, future research should empirically validate these findings against direct physical measurements, such as sap flow sensors or lysimeters. The proposed framework presents a practical, objective decision-support tool for municipal policymakers and landscape architects to optimize species selection, implement nature-based solutions (NBS), and achieve long-term sustainability in urban greening. Full article

Ectomyelois ceratoniae (Zeller), the date moth, is a major pest of date palm (Phoenix dactylifera L.), responsible for severe post-harvest losses in arid and Mediterranean regions. The Sterile Insect Technique (SIT) is an environmentally friendly control method whose effectiveness depends on selecting irradiation doses that ensure sterility while preserving insect quality. This study evaluated the histopathological effects of ⁶⁰Co gamma irradiation on the digestive system of fifth-instar larvae of E. ceratoniae. Larvae were exposed to doses of 0 (control), 250, 300, 350, and 450 Gy, and the mesenteron, proctodeum, and Malpighian tubules were analyzed using Mallory’s trichrome staining. Quantitative measurements included epithelial thickness, intestinal stem cell density, Malpighian tubule diameter, and a histological integrity index. Gamma irradiation induced pronounced dose-dependent alterations. These included thinning and disorganization of the intestinal epithelium, a marked reduction in stem cell density, swelling of Malpighian tubules, and a progressive loss of tissue integrity. Severe degeneration and functional collapse of digestive tissues were observed at doses ≥ 350 Gy. The results indicate that 300–350 Gy represents a critical irradiation range inducing irreversible digestive damage compatible with effective sterilization. These findings provide histopathological reference criteria for optimizing dose selection and quality control in SIT programs targeting E. ceratoniae. Full article

The diversity of cyanobacteria from the semi-arid region of Rajasthan, India, remains vastly unexplored and warrants systematic investigation. We isolated two cyanobacterial strains (SN2022/33 & AT2016/25) of non-heterocytous, filamentous cyanobacterium from samples of sandy soil biological crusts and investigated them using a polyphasic approach. Based on 16S rRNA gene sequence identity, both strains formed a distinct lineage, with 16S sequence identity (p-distance) < 95% to the closest sister genera Trichocoleus, Venetifunis, Trichothermofontia, and Pinocchia. Analyses of 16S-23S Internal Transcribed Spacer (ITS) secondary structures (D1-D1′, BoxB, and V3 helixes) yielded substantial differences from phylogenetically associated taxa. Morphologically, both strains corresponded to members of the family Trichocoleusaceae (Leptolyngbyales), with tapered filaments and conical-pointed end cells. Most significantly, this taxon exhibited a form of true branching, with prolific unilateral or bilateral extrusions, something that had previously been the exclusive purview of members of the Nostocaceae. The combined evidence from conventional and molecular studies supports the recognition of the isolates as a novel taxon hereby described as Edaphifilum ginni gen. et sp. nov., in accordance with the International Code of Nomenclature (ICN) for Algae, Fungi, and Plants. Full article

Fog-dependent Tillandsia landbeckii in the hyper-arid Atacama Desert lacks the red-edge reflectance pattern that supports vegetation monitoring, motivating shortwave infrared (SWIR) approaches. We evaluated a newly developed UAV-borne multispectral SWIR camera system for estimating plant water status and additional plant functional traits (fresh and dry biomass, and N uptake) from four spectral bands (1100, 1200, 1510, and 1650 nm) across 20 destructively sampled plots. Of five traits tested, only canopy water content (CWC) retained statistically robust spectral associations after multiple-testing correction, with most significant predictors concentrated in the 1200–1510 nm wavelength region. A physically interpretable predictor, the mean spectral slope between 1200 and 1510 nm, yielded conditional cross-validated $R_{\mathrm{cv}}^2=0.51$ (${\mathrm{RMSE}}_{\mathrm{cv}}\approx 170$ g m⁻²), though fully selection-corrected estimates were substantially lower ($R_{\mathrm{cv}}^2=0.10$–$0.20$), reflecting feature-selection instability at the given sample size. The absence of robust biomass- and nitrogen-related signals is physically interpretable given the species’ atypical surface optics. While expanded sampling and independent validation remain necessary to establish transferable performance estimates, these results demonstrate that SWIR-based water-status retrieval is feasible for this spectrally challenging species, opening a pathway toward functional monitoring of fog-dependent desert ecosystems. Full article

In the face of intensifying climate change, agricultural water security in semi-arid zones has emerged as a critical frontier for water governance. This study provides a systematic and critical analysis of the scientific literature to map current research frontiers and structural gaps. The methodology integrated the PRISMA 2020 protocol and a modified Methodi Ordinatio, spanning a search period from 2014 to 2026 across the Science Direct and SciELO databases. From an initial broad screening, 136 high-impact articles were selected based on rigorous inclusion and exclusion criteria. The findings reveal a significant fragmentation of knowledge, characterized by a high prevalence of small-scale studies (25 articles) and limited interdisciplinarity. Notably, a governance-centric approach is present in only 20% of the literature, while the Water–Energy–Food Nexus appears in just 6%, signaling a major disconnect in holistic management. Based on these results, this study identifies water governance and socioeconomic integration as the most pressing research gaps. Consequently, an integrated conceptual framework is proposed, built upon three pillars: Governance, Technology, and Environment (GET). This study concludes that advancing the frontiers of agricultural water security requires moving beyond isolated solutions toward a structured, systemic, and interdisciplinary integration. Full article

Rangelands occupy over half of the Earth’s terrestrial surface and play an important role in supporting biodiversity and livelihoods. However, widespread degradation—particularly in arid and semi-arid regions—has compromised their ecological function. Traditional monitoring approaches that rely on vegetation cover metrics from optical satellite imagery fail to capture the three-dimensional structure of vegetation, which is critical for assessing ecosystem condition and guiding restoration and management efforts. This study demonstrates the application of high-density airborne LiDAR (ALS) data (~15–20 points/m²) to identify and map vegetation structural types across 370,000 hectares of semi-arid rangelands in Western Australia. Using an unsupervised fuzzy c-means clustering algorithm on seven minimally correlated ALS-derived structural metrics, we identified eight statistically distinct vegetation structural classes. The resulting structural map revealed spatial heterogeneity in vegetation structure, including in areas with similar vegetation cover, with high confidence in structural attribution in 74.5% of the study area. The rangeland-specific structural classes developed in this study, which incorporate measures of classification certainty, offer a robust framework for vegetation structural mapping in field data-scarce environments. This framework can support ecological condition assessments and provide a basis for rangeland management and restoration planning. Full article