Search Results (9,089)

Spineless cactus, known for its high heat tolerance and low water requirements, offers a sustainable alternative for animal feed in regions where conventional crops struggle to thrive. This study aimed to evaluate the carcass characteristics, leg tissue composition, and non-carcass constituents of lambs fed increasing levels (0, 15, 30, and 45% based on dry matter) of spineless cactus as a replacement for Tifton hay. Additionally, we estimated body weight and carcass traits using biometric measurements (BM). Forty male lambs, with an average initial body weight of 23.6 ± 2.58 kg, were subjected to a feedlot regime. Empty body weight was the only variable that showed a significant orthogonal contrast between the control group (0%) and those fed spineless cactus (p < 0.05). A quadratic regression effect (p < 0.05) was observed for the weights of the cold half carcass, neck, shoulder, and leg cuts. No significant effects were found on non-carcass components or biometric measurements. Biometric measurements showed strong positive correlations with slaughter weight and carcass characteristics. Based on these findings, replacing 30% of Tifton hay with spineless cactus is recommended as the optimal level, as it maintains carcass quality, tissue composition, and non-carcass traits. Moreover, biometric measurements prove to be effective tools for predicting slaughter weight and carcass characteristics, offering practical value for farmers seeking efficient and sustainable production strategies. The inclusion levels of 24.25% to 27.50% of spineless cactus in the diet of confined sheep appear to be the most efficient, promoting high-value commercial cuts without compromising carcass quality parameters. These levels balance productive performance and sustainability, especially in semi-arid regions. Full article

Land is a limited yet vital resource, which is fundamental for food security and national stability. Ensuring its effective use requires modern tools to support informed decision making. This study evaluates land suitability for irrigation in the Kyzylorda region of Kazakhstan, with the objective of identifying areas appropriate for crop expansion. A multidimensional approach was employed, integrating soil properties, topography, proximity to water sources, and existing land use patterns, with suitability classes defined according to the Food and Agriculture Organization’s framework. The Analytic Hierarchy Process, based on pair-wise comparisons and Saaty’s scale, was used to assign weights to each factor. The findings reveal that 30% of highly suitable land and 80% of suitable land remain uncultivated. Conversely, 10% of the current cropland is located in marginally suitable area—likely a result of historical land use decisions or the limited availability of optimal land. This research responds to the specific challenges of arid climates and water scarcity by providing a decision-support tool that promotes sustainable land use, strengthens food security, and encourages responsible land management. Full article

Plants inhabiting arid regions often harbor microbial communities that contribute to their resilience under extreme conditions. Yet, the genomic diversity and functional potential of bacterial endophytes associated with desert-adapted plants, particularly in Africa, remain largely unexplored. In this study, we investigated Microbacterium endophytes from the xerophytic cucurbit Citrullus colocynthis L. (Cucurbitaceae), collected in a semi-arid environment in central Morocco. Using culture-based isolation, phenotypic characterization, and whole-genome sequencing, we analyzed three representative isolates from leaf and root tissues. Genome-based taxonomy combined with polyphasic analyses identified two novel species, Microbacterium xerophyticum sp. nov. and Microbacterium umsixpiens sp. nov., with genome sizes of approximately 4.0 Mb and 3.9 Mb, respectively. Functional annotation revealed traits consistent with endophytism in water-limited ecosystems, including oxidative and osmotic stress responses, metal homeostasis, and high-affinity phosphate uptake. Differences in siderophore acquisition and nitrogen metabolism suggest niche partitioning between the two species. These findings document two novel bacterial species from a medicinal plant native to arid ecosystems, broaden the known diversity of plant-associated Microbacterium, and provide region-specific genomic references with adaptive traits relevant to host resilience under arid conditions. Full article

The optimal groundwater level is critical for maintaining the coordinated and healthy development of the ecological–agricultural production system in arid oasis regions. This study comprehensively considered factors such as ecological safety, soil salinization prevention and control, and ground subsidence constraints to determine the optimal groundwater level in a region. GIS technology and Visual MODFLOW Flex 6.1 software were used to construct a three-dimensional groundwater numerical model, and regional comprehensive evaluation values were applied to simulate and predict the spatiotemporal evolution of groundwater levels under different regulation schemes. Results indicated the following: (1) There were significant spatial differences in the study area. The optimal groundwater depths in agricultural and engineering/living areas were 2–4 and 3–4 m, respectively, as determined using methods such as capillary rise height and total sum of middle layers. (2) In long-term (≥10a) regulation, areas with a reduced regional comprehensive evaluation value > 0.20 exhibited the highest groundwater recharge rate (17.10%), while those with a reduced regional comprehensive evaluation value > 0.32 showed the best coverage of optimal groundwater levels. The opposite trend was observed in short-term regulation. (3) Considering both groundwater recharge and optimal groundwater level regulation, the Y₂ scheme demonstrated the best regulation effect. The findings of this study can provide theoretical references for the multi-objective optimization management of water resources in arid oasis regions. Full article

The Tibetan Plateau is a globally critical climate-sensitive and ecologically fragile region. Vegetation phenology serves as a key indicator of ecosystem responses to climate change and simultaneously influences regional carbon cycling, water regulation, and ecological security. However, systematic quantitative assessments of phenological responses under the combined effects of multiple climate factors remain limited. This study integrates multi-source remote sensing data (MODIS MCD12Q2) and ERA5-Land meteorological data from 2001 to 2023, leveraging the Google Earth Engine (GEE) cloud platform to extract key phenological metrics, including the start (SOS) and end (EOS) of the growing season, and growing season length (GSL). Sen’s slope estimation, Mann–Kendall trend tests, and partial correlation analyses were applied to quantify the independent effects and spatial heterogeneity of temperature, precipitation, solar radiation, and evapotranspiration (ET) on GSL. Results indicate that: (1) GSL on the Tibetan Plateau has significantly increased, averaging 0.24 days per year (Sen’s slope +0.183 days/yr, Z = 3.21, p < 0.001; linear regression +0.253 days/yr, decadal trend 2.53 days, p = 0.0007), primarily driven by earlier spring onset (SOS: Sen’s slope −0.183 days/yr, Z = −3.85, p < 0.001), while autumn dormancy (EOS) showed limited delay (Sen’s slope +0.051 days/yr, Z = 0.78, p = 0.435). (2) GSL changes exhibit pronounced spatial heterogeneity and ecosystem-specific responses: southeastern warm–wet regions display the strongest responses, with temperature as the dominant driver (mean partial correlation coefficient 0.62); in high–cold arid regions, warming substantially extends GSL (Z = 3.8, p < 0.001), whereas in warm–wet regions, growth may be constrained by water stress (Z = −2.3, p < 0.05). Grasslands (Z = 3.6, p < 0.001) and urban areas (Z = 3.2, p < 0.01) show the largest GSL extension, while evergreen forests and wetlands remain relatively stable, reflecting both the “climate sentinel” role of sensitive ecosystems and the carbon sequestration value of stable ecosystems. (3) Multi-factor interactions are complex and nonlinear; temperature, precipitation, radiation, and ET interact significantly, and extreme climate events may induce lagged effects, with clear thresholds and spatial dependence. (4) The use of GEE enables large-scale, multi-year, pixel-level GSL analysis, providing high-precision evidence for phenological quantification and critical parameters for carbon cycle modeling, ecosystem service assessment, and adaptive management. Overall, this study systematically reveals the lengthening and asymmetric patterns of GSL on the Tibetan Plateau, elucidates diverse land cover and climate responses, advances understanding of high-altitude ecosystem adaptability and climate resilience, and provides scientific guidance for regional ecological protection, sustainable management, and future phenology prediction. Full article

This study aimed to assess the potential of machine learning models applied to high spatial resolution images from UAVs for estimating the aboveground biomass (AGB) of forage grass cultivated in the Brazilian semiarid region. The fresh and dry AGB were determined in Cenchrus ciliare plots with an area of 0.04 m². Spectral data were obtained using a multispectral sensor (Red, Green, and NIR) mounted on a UAV, from which 45 vegetation indices were derived, in addition to a structural variable representing plant height (H95). Among these, H95, GDVI, GSAVI2, GSAVI, GOSAVI, GRDVI, and CTVI exhibited the strongest correlations with biomass. Following multicollinearity analysis, eight variables (R, G, NIR, H95, CVI, MCARI, RGR, and Norm G) were selected to train Random Forest (RF), Support Vector Machine (SVM), and XGBoost models. RF and XGBoost yielded the highest predictive performance, both achieving an R² of 0.80 for AGB—Fresh. Their superiority was maintained for AGB—Dry estimation, with R² values of 0.69 for XGBoost and 0.67 for RF. Although SVM produced higher estimation errors, it showed a satisfactory ability to capture variability, including extreme values. In modeling, the incorporation of plant height, combined with spectral data obtained from high spatial resolution imagery, makes AGB estimation models more reliable. The findings highlight the feasibility of integrating UAV-based remote sensing and machine learning algorithms for non-destructive biomass estimation in forage systems, with promising applications in pasture monitoring and agricultural land management in semi-arid environments. Full article

This study addresses water scarcity in arid regions by developing low-temperature-sintered porous ceramics for agricultural water management, utilizing coal gangue solid waste as the primary resource. Systematic single-factor experiments first identified the optimal sintering temperature (615 °C) and polystyrene content (25%) that critically balance pore formation and structural integrity. Building on this, orthogonal experiment optimization yielded an optimal formulation exhibiting exceptional comprehensive performance (coal gangue 20 g, starch 25 g, glass powder 11 g, polystyrene 27 g): 149.70% water absorption, 57.75 h water retention, 77.28% porosity, and 0.55 MPa compressive strength. The material’s graded pore structure, achieved through composite pore-formers (polystyrene/starch) and diatomaceous earth, underlies its enhanced capillary action. The pot experiment of Chinese cabbage confirmed its effect, shortened the emergence time of seedlings to <24 h, and significantly improved the emergence rate and the growth of seedlings in the early stage (7 days). This work provides a new way for the value of coal gangue in dryland agriculture and ecological restoration. Full article

The Tarim River Basin, a core region for economic development and ecological security in China’s inland arid areas, faces the pressing challenge of synergistically improving land use efficiency to resolve human-land conflicts under water resource constraints and achieve sustainable development. Based on the “economic-social-ecological” benefit coordination theory, this study constructs a land use efficiency evaluation system with 16 indicators and integrates the coupling coordination degree model and gravity model to quantitatively analyze the spatiotemporal differentiation patterns and coupling mechanisms of land use efficiency in the basin from 1990 to 2020. Results show that economic and social benefits of land use increased during this period, exhibiting a “high-north, low-south” spatial pattern, while ecological benefits remained relatively high but declined gradually. The coupling coordination degree of subsystem benefits displayed significant spatial heterogeneity, with an overall upward trend, where composite factors emerged as the primary constraint. Spatially, land use efficiency coupling coordination evolved from “core polarization” to “axial expansion” and finally “networked synergy,” with stronger linkages concentrated in oasis irrigation districts. These findings provide theoretical support for ecological conservation, water management, and policy-making in southern Xinjiang, offering pathways to synergize the “economic-social-ecological” system and promote sustainable development in arid regions. Full article

Hylocereus species are promising for enhancing fruit productivity in arid regions, but high solar radiation often leads to yield loss. This study aimed to evaluate the short-term impact of different shading levels on the physiological performance, productivity, and post-harvest quality of Hylocereus costaricensis under semi-arid conditions. Plants were grown in the field under two shade levels, i.e., 35 and 50% and their performances were compared to plants under control, i.e., 0% of shade or full sunlight. The nighttime CO₂ assimilation and productivity increased significantly by 310.5 and 114.6% and 34.3 and 50.14% for plants under 35 and 50% of shade, respectively, compared to the control. A Principal Component Analysis (PCA) revealed that shade enhanced skin betalain (BETS) and phenolic content (PETP), whereas non-shaded plants expressed traits more closely associated with plant and fruit photoprotective pigment synthesis, i.e., total carotenoids and yellow flavonoids, respectively, along with total sugar accumulation, underscoring the significant impact of shading on both metabolic activity and overall agronomic outcomes. Shading within the 35% to 50% range is effective to cope with high solar radiation by improving photosynthetic capacity, productivity, and post-harvest quality, especially regarding the accumulation of pigments such as betalains, indicating that shade as an agro-technique is a valuable approach for the cultivation of Hylocereus species in dryland regions. Full article

The Xishan–Yongding River cultural belt is a key component of the three major cultural belts of Beijing and its water heritage; as a representative of the intensive distribution of semi-arid climate, analyzing its spatial and temporal distribution characteristics is crucial for the development of systematic conservation strategies. This study is based on a dataset developed from field surveys and historical documentation and has been spatially analyzed using visual analytical methods and using a Geographic Information System (GIS). In this study, kernel density estimation was used to identify areas of high density, standard elliptic deviation was used to assess the distribution of water heritage sites over time, and the mean nearest neighbor index was used to determine the spatial clustering pattern of these sites. Regarding type and quantity, water heritage in the cultural belt is diverse, with non-water heritage sites, such as temples and inscriptions, being the most prevalent. In terms of temporal distribution, water heritage spans a long period, with the largest number dating to the Qing Dynasty. The centers of distribution across different periods exhibit a trend from south to north and from mountainous regions to plains, exhibiting a gradual concentration. Spatially, water heritage within the cultural belt follows a “multi-core, contiguous distribution” pattern, with three high-density zones, two medium-density zones, and six low-density zones. The distribution of water heritage is influenced by a combination of natural factors, such as river systems, settlements, elevation, and slope, alongside human factors, including historical culture and the political environment. The findings of this research offer a detailed analysis of the regional characteristics and underlying mechanisms of the temporal and spatial distribution of water heritage within the Xishan–Yongding River cultural belt. Full article

Most risk assessment and source apportionment studies of the heavy metals in the surface soils in China have focused primarily on East China, whereas studies focused on Northwest China, particularly regarding heavy metals in surface soils in the central and western areas, remain limited. In this study, surface soils in the central–western Ali region were investigated, and the concentrations of nine heavy metals were determined. Moreover, the distribution patterns and ecological risks of these heavy metals were elucidated via a combination of the geoaccumulation index, pollution load index ($PLI$), comprehensive potential ecological risk index ($RI$), and integrated X-ray diffraction (XRD)–multivariate statistical techniques. Additionally, the pollution characteristics and sources were analyzed. The results indicated the following: (1) The spatial distribution of heavy metal pollution is closely linked to the geological background, and high–pollution zones (e.g., Cr, Ni, Co, Cu, As, and Cd) conform well with the distributions of ultramafic rocks and iron/chromite ore beds. The geoaccumulation index revealed that Cd caused slight and moderate contamination at 29.1% and 5.5% of the sites, respectively, whereas As affected 14.6% of the sites. The pollution load index indicated moderate pollution in 20% of the sites, and the potential ecological risk index indicated that 41.8% of the sites posed moderate risks, which was largely driven by Cd (mean $E_r^i$ = 43.1). The comprehensive ecological risk index ($RI$ = 115) confirmed a moderate risk level overall. Principal component analysis revealed three primary sources: natural weathering (Cr–Ni–Co–Cu, 39.1%); a mixed source influenced by nonagricultural anthropogenic activities such as transport and regional deposition, combined with natural processes such as arid climate and alkaline soil conditions that influence Cd mobility (Cd–Mo–Pb, 20.8%); and industrial/mining activities (As–Sb, 14.2%). Mineralogical analyses further indicated that heavy metals are present via lattice substitution, adsorption, and precipitation. This study systematically clarifies the composite pollution pattern and sources of heavy metals in the alpine Ali region, supporting targeted contamination control. Full article

Durum wheat (Triticum durum Desf.) underpins semolina value chains in water-limited regions, yet Peru remains import-dependent due to constrained local adaptation. We evaluated eleven elite lines plus the commercial variety ‘INIA 412 Atahualpa’ across three contrasting semi-arid sites in Arequipa (Santa Elena, San Francisco de Paula, Santa Rita) during 2023–2024 to identify genotypes maximizing performance and stability. Grain yield, thousand-kernel weight (TKW), hectoliter weight, and plant height were analyzed with combined analysis of variance (ANOVA), the additive main effects and multiplicative interaction (AMMI) and genotype and genotype-by-environment (GGE) biplots, complemented by AMMI stability value (ASV) and weighted average of absolute scores and best yield index (WAASBY). Grain yield and hectoliter weight showed significant genotype × environment (G × E) interaction, while plant height was driven mainly by genotype and environment with limited interaction. For grain yield, AMMI (PC1: 55.2%) and GGE (PC1 + PC2: 90.2%) revealed crossover responses and three practical mega-environments: TD-053 “won” at San Francisco de Paula, TD-037 at Santa Elena, and TD-033 at Santa Rita. Additionally, WAASBY-integrated rankings favored TD-033 (93.7%) and TD-014 (84.72%), followed by TD-026/TD-020 (>57%), whereas TD-062 (9.1%) and TD-043/TD-061 underperformed. Quality traits highlighted TD-044 and TD-014 for high hectoliter weight and TD-014/TD-062 for high TKW with contrasting stability. Overall, TD-033 and TD-014 were adaptable across environments, providing selection guidance to strengthen Peru’s durum breeding pipeline under climate variability. Full article

Drought is a major climatic hazard affecting water resources, agriculture, and livelihoods in semi-arid regions, with increasing severity under climate change. This study assessed long-term drought in Dura City, Palestine, from 2000 to 2023 using the Standardized Precipitation Index (SPI) at 3-, 6-, and 12-month timescales. Monthly precipitation and temperature data were obtained from local meteorological stations, with mean annual precipitation of 408 mm and average summer and winter temperatures of 28 °C and 12 °C, respectively. Trends were analyzed using the Mann–Kendall test and Sen’s slope estimator. SPI-3 values ranged from −3.13 to 3.87, including 67 moderates to severe drought months and 12 extreme wet months. SPI-6 ranged from −2.97 to 2.53, showing 34 drought months and 40 wet months, while SPI-12 ranged from −1.94 to 2.32, reflecting generally stable long-term precipitation. Annual rainfall exhibited no significant trend (Sen’s slope = −1.34 mm/year, p = 0.785), whereas yearly average temperature increased significantly by 0.054 °C/year (p = 0.02), raising evapotranspiration and drought risk. Results indicate high short- and medium-term drought variability despite stable annual precipitation, underscoring the need for integrated water management strategies, including rainwater harvesting, groundwater protection, and efficient irrigation, to improve resilience under evolving climate conditions. Full article

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

A multiproxy study of a new Pleistocene locality at Ivantzevo, Moscow Region, was conducted to reconstruct paleoenvironments from the Middle Pleistocene to the Last Pleniglacial. Lacustrine deposits and peat accumulated in a wetland within a fluvioglacial depression formed during the Dnieper–Moscow glaciation. Silts and clays were deposited during MIS 7 and the Moscow (Saale) Glaciation (MIS 6), while peat accumulation began in the Mikulino (Eemian) (MIS 5e). The wetland persisted for approximately fifty millennia, until the Middle Valdai (Weichselian). Interglacial peat deposits contain well-preserved pollen and macrofossils, and the recovered fossil insect assemblage is unique for European Russia. Chronology was established using multiple OSL and ²³⁰Th/U dates, combined with pollen-based correlations to type sections north and west of the region. The reconstructed ecosystem dynamics are divided into eleven stages. The transition from the last interglacial to the second stadial of the Valdai involved seven phases: (1) expansion of boreal spruce forest, (2) spread of thermophilic broad-leaved forests with hazel, (3) development of open forest–steppe ecosystems with groves of deciduous trees, (4) re-establishment of forest cover with birch and, later, mixed pine, spruce, and birch forests, (5) emergence of cold steppe combined with shrub-dominated tundra, (6) return of boreal spruce forest, and (7) abrupt replacement of forest by cold steppe and shrub tundra. Climatic reconstructions indicate that these ecosystem dynamics closely corresponded to changes in precipitation and aridity. Full article