Search Results (5,857)

The Loess Plateau (China) is an ecologically fragile region where understanding the impact of forest naturalness on soil carbon content is critical for ecological restoration and enhancing carbon sequestration. This study investigates this relationship in the Cuiying Mountain area (Yuzhong County, Lanzhou City), a representative landscape of the semi-arid Loess Plateau. The Cuiying Mountain ecosystem is characterized by coniferous forests and Gray-cinnamon soils. We assessed forest naturalness using several key indicators: herb coverage, shrub coverage, tree biodiversity, and stand structural attributes. The results revealed a generally low level of forest naturalness at Cuiying Mountain. Although herb coverage was high, shrub coverage was minimal (2.1%), and tree biodiversity was low (Shannon index = 0.09). The stand structure was simple, characterized by considerable variation in individual tree sizes and a single canopy layer (mean mingling degree = 0.14). This structural simplicity aligns with the area’s history of plantation management. Furthermore, analysis of soil physicochemical properties and their relationship with plant diversity identified plant diversity as a significant factor influencing soil carbon content. The strongest correlation was observed between plant species number and topsoil organic carbon (r = 0.77), indicating a particularly pronounced effect of plant diversity on surface soil organic carbon. In summary, while forest naturalness at Cuiying Mountain is generally low, increased plant diversity enhances the accumulation of litter/root exudates and carbonates, suggesting that enhancing plant diversity is an effective strategy for increasing total soil carbon content. This study provides valuable insights for refining ecological restoration practices and strengthening the soil carbon sink function in forest ecosystems across the Loess Plateau and similar semi-arid regions. Full article

Groundwater quality in the semi-arid region of Oum El Bouaghi, Northeastern Algeria, was assessed for irrigation suitability using hydrogeochemical analyses, water quality indices, and GIS techniques. The study analyzed 23 groundwater samples during dry and wet seasons in 2022–2023, several physicochemical parameters were measured. Results revealed neutral to slightly alkaline pH levels, except for one acidic sample, with salinity (EC: 527–5001 µS·cm⁻¹) exceeding WHO guidelines, particularly during the dry season due to evaporation and anthropogenic activities. Hydrogeochemical facies showed dominance of Na⁺-HCO₃⁻ and Ca²⁺-Cl⁻/SO₄²⁻ water types, indicating rock–water interactions and evaporation control, as confirmed by Gibbs plots. The IWQI classified water into five categories, with severe restrictions (IWQI < 40) in 13% of samples during the dry season, improving slightly in the wet season. Indices such as SAR, Na%, and RSC indicated low to moderate sodium hazard, while KR and PS highlighted salinity risks in specific areas. Spatial analysis revealed localized pollution hotspots, with the (GPI) identifying minimal to high contamination levels, linked to agricultural and geogenic sources. These findings underscore needs for sustainable groundwater management, including monitoring, optimized irrigation practices, and mitigation of anthropogenic impacts, to ensure long-term agricultural viability in this water-scarce region. Full article

Water-extractable carbon is thought to originate from labile organic carbon pools and has been used as an active carbon indicator for soil evaluation in numerous studies. This study aims to explore the regional variation patterns of water-extractable organic carbon (WEOC) and the environmental impact factors associated with it. It examines the variability of WEOC under different climatic conditions and land use types, including grasslands and woodlands, thereby enhancing our understanding of WEOC. We measured the WEOC in the surface soil layers (0–10 cm) of woodlands and grasslands in arid and semi-arid regions. Additionally, we analyzed the effects of varying climatic conditions and land use types on WEOC based on data from literature research. WEOC distribution patterns diverged spatially from soil organic carbon (SOC). WEOC fractions decreased with increasing precipitation, and surface soil WEOC accumulation was observed in arid regions. This accumulation was more pronounced in forest-land, resulting in a more marked divergence in WEOC concentrations between woodlands and grasslands in arid regions. We inferred that the inconsistent correlation between WEOC and SOC across regions arises from their distinct distribution patterns along environmental humidity gradients. Owing to the climate sensitivity of WEOC, its surface soil accumulation in arid areas may increase the vulnerability of soil ecosystems, rendering them more susceptible to environmental disturbances. Such susceptibility could drive organic carbon loss and soil quality degradation. These findings hold promise for improving our understanding of WEOC dynamic, and will also give insight into refining soil carbon balance models and soil management strategies to address environmental changes. Full article

Santa Ana winds are extreme meteorological events that strongly affect the U.S.–Mexico border region, often associated with droughts, high fire risk, and hydrological imbalance. Understanding the temporal behavior of key atmospheric variables during these events is crucial for integrated water resource management in semi-arid regions such as the Guadalupe Basin in northern Baja California. In this study, we explored the predictive capability of several hybrid deep learning architectures—Long Short-Term Memory (LSTM), Convolutional Neural Network combined with LSTM (CNN–LSTM), and Bidirectional LSTM with Attention (BiLSTM–Attention)—to model the temporal evolution of wind speed, wind direction, temperature, relative humidity, and atmospheric pressure using Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data from 1980 to 2020. Model performance was evaluated using RMSE, MAE, and R² metrics and compared against persistence and climatology baselines. The BiLSTM–Attention model achieved the best overall performance, showing particularly high accuracy for temperature (R² = 0.95) and relative humidity (R² = 0.76), while maintaining angular errors below 35° for wind direction. The results demonstrate the potential of hybrid deep learning models to capture nonlinear temporal dependencies in meteorological time series and provide a methodological framework to enhance hydrometeorological understanding and water resource management in the Guadalupe Basin under Santa Ana wind conditions. Full article

Mining-induced subsidence has significantly altered the structure of the vadose zone in coal mining areas, where soil cracks act as preferential pathways controlling water infiltration and redistribution. In this study, a Hydrus-2D dual-domain seepage model incorporating geometric parameterization of cracks was developed to simulate water migration in the vadose zone of a typical subsidence area in the Ordos Basin. The model integrates field-measured crack geometry, soil texture, and rainfall characteristics to quantitatively analyze preferential flow formation under twelve combinations of crack width, soil type, and rainfall intensity. The results show that (i) crack width dominates preferential flow behavior, with wider cracks (≥5 cm) deepening the wetting front from approximately 107 cm to 144 cm within 120 h and sustaining high conductivity after rainfall; (ii) soil texture governs infiltration pathways, as sandy soils promote deeper wetting fronts (up to 99 cm, ~40% deeper than loam) and layered soils induce interface retention or “jump” infiltration; and (iii) rainfall intensity controls infiltration depth, with storm events producing wetting fronts more than four times deeper than those under light rain. Overall, this study demonstrates the feasibility and significance of integrating crack parameterization into vadose-zone hydrological modeling using Hydrus-2D, providing a quantitative basis for understanding rapid infiltration–migration–recharge processes and supporting ecological restoration and water resource management in arid and semi-arid mining regions. Full article

The latest exploration developments and discoveries from the eastern Mediterranean documented that Neogene formations can act as source-rocks for hydrocarbon generation and their exploitation delivered large amounts of mostly biogenic gas to the market. Examples of such offshore gas-fields include the Zohr-Egypt, Leviathan/Tamar-Israel, and Aphrodite-Cyprus. Having attracted the oil majors’ attention for hydrocarbons exploration in southern Greece (e.g., Exxon-Mobil, Chevron), by using onshore geologic analogs, we suggest relevant perspectives in the country’s offshore sector. Our study focuses on Miocene marine deposits exploration, from Gavdos Island, southern Greece, evaluating their characteristics as potential source-rocks affected by a paleodepositional framework. By integrating fieldwork, organic (Rock-Eval VI-pyrolysis, CHNS) and inorganic geochemical data (XRF), the current results indicate gas-prone organic matter with variable preservation status, reflecting a few oxidation episodes during deposition under generally dysoxic-to-suboxic conditions. Paleoclimatic weathering indices (CIA, C.I., Sr/Cu, Rb/Sr) suggest predominantly arid to semi-arid regimes punctuated by short-lived humid phases that locally enhance organic accumulation and nutrient supply. Variations in paleosalinity and stratification, particularly within the Messinian section, are interpreted as precursors to the Messinian Salinity Crisis. Our findings highlight the potential for hydrocarbon-prone intervals in the deeper-offshore Eastern Mediterranean basins, where most favorable conditions for organic-carbon preservation and maturation are documented by the discoveries. Full article

Biochar application in dry regions holds promise for improving soil properties, but its impact on soil salinity remains controversial. To evaluate the short-term effect of biochar on soil salinity under dry conditions, we conducted a meta-analysis of 149 observations from 40 peer-reviewed publications conducted in Mediterranean, arid, and semi-arid climates, or under simulated dry/saline conditions. Overall, biochar addition significantly increased soil electrical conductivity (EC) by 34.63% compared to controls. However, this effect was highly dependent on pedoclimatic conditions, soil pH, biochar feedstock types, pH and EC, irrigation practices, and management factors. The most substantial increases in salinity occurred when applying biochar produced from high-ash feedstocks (e.g., seafood shell powder, peanut shell), at high application rates (>20 t ha⁻¹), to soils with low initial organic carbon content, or in the absence of a leaching fraction. In contrast, the use of biochar made from low-ash ligneous materials at rates ≤ 20 t ha⁻¹ did not significantly increase soil EC. Random forest analysis identified biochar EC, initial soil EC, and biochar pH as the most influential factors. We conclude that the risk of biochar-induced salinization in drylands can be effectively minimized by selecting appropriate lower-EC biochar, applying it at moderate application rates, and implementing irrigation with a leaching fraction. These findings provide critical guidelines for the sustainable implementation of biochar technology in water-scarce environments. Full article

Salinity is a long-standing global environmental stressor of terrestrial agroecosystems, with important implications for viticulture sustainability, especially in arid and semi-arid environments. Salt-induced physiological and biochemical disruptions to grapevines undermine yield and long-term vineyard sustainability. This review aims to integrate physiological, molecular, and omics-based insights to elucidate how grapevine rootstocks confer salinity tolerance and to identify future breeding directions for sustainable viticulture. This review critically assesses the ecological and molecular processes underlying salt stress adaptation in grapevine (Vitis spp.) rootstocks, with an emphasis on their contribution to modulating scion performance under saline conditions. Core adaptive mechanisms include morphological plasticity, ion compartmentalization, hormonal regulation, antioxidant defense, and activation of responsive genes to stress. Particular emphasis is given to recent integrative biotechnological developments—including transcriptomics, proteomics, metabolomics, and genomics—that reveal the intricate signaling and regulatory networks enabling rootstock-mediated tolerance. By integrating advances across eco-physiological, agronomic, and molecular realms, this review identifies rootstock selection as a promising strategy for bolstering resilience in grapevine production systems confronted by salinization, a phenomenon increasingly exacerbated by anthropogenic land use and climate change. The research highlights the value of stress ecology and adaptive root system strategies for alleviating the environmental consequences of soil salinity for perennial crop systems. Full article

Companies face multi-criteria problems every day, such as prioritizing projects, investments, and suppliers. In this respect, the literature offers countless methods, some of which provide partial and flawed solutions. Therefore, identifying and replacing a flawed method with a more efficient one is fundamental. However, this replacement is not straightforward because each method has a different evaluation structure. More specifically, in this study, the Mapping method uses scoring evaluations, whereas the Analytic Hierarchy Process (AHP) uses pairwise comparisons. In other words, scoring evaluations are incompatible with pairwise comparison evaluations. This incompatibility prevents one method from being replaced by another without loss of information. This is a significant gap because the re-evaluation process is expensive, time-consuming, and may even be impossible if the experts are no longer available. This study presents a novel approach to automatically substitute prioritization methods without loss of information. The approach was applied to a real-world case involving forty-four Brazilian companies. The specific case shows the prioritization of four projects evaluated by scores, combined with three new projects evaluated by pairwise comparisons. The application of the approach offers specific and general contributions. For example, substituting prioritization methods without loss of information, such as the Mapping method with AHP. Flexibility in choosing the evaluation method that offers greater psychological comfort to the experts. Obtaining transitive pairwise comparison matrices independently of the number of new projects evaluated. Full article

Carnauba (Copernicia spp.) is a palm tree native to the Brazilian semi-arid region, valued for its significant economic, social, and environmental importance. This resilient species possesses adaptive mechanisms that enable it to endure prolonged periods of soil water scarcity and conditions of flooding and salinity. However, despite its relevance, there is a notable lack of scientometric data on this species in the literature, representing a significant research gap. This study aimed to analyze the state of research on carnauba palm from 2007 to 2022. Datasets were collected from the Web of Science central database, totaling 658 publications related to the terms “carnauba” or “copernicia”. The bibliometric software VOSviewer was used to create visual maps of keyword co-occurrence networks, providing deeper insights into the progress and research trends on the topic. Since 2014, the number of publications on carnauba has steadily increased, peaking between 2019 and 2021. The most prominent focus in these articles is on carnauba wax, with extensive research on its properties and applications in the food production chain. This significance is also reflected in the keyword co-occurrence networks. However, studies combining carnauba with soil sciences remain underexplored. Given carnauba’s importance in environmental and soil conservation, future research linking these areas could become a key avenue for advancing knowledge on the subject. Full article

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

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

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

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