Search Results (368)

The genus of Nitraria L. are Tertiary-relict desert sand-fixing plants, which are an important forage and agricultural product, as well as an important source of medicinal and woody vegetable oil. In order to provide a theoretical basis for better protection and utilization of species in the Nitraria L., this study collected global distribution information within the Nitraria L., along with data on 29 environmental and climatic factors. The Maximum Entropy (MaxEnt) model was used to simulate the globally suitable distribution areas for Nitraria L. The results showed that the mean AUC value was 0.897, the TSS average value was 0.913, and the model prediction results were excellent. UV-B seasonality (UVB-2), UV-B of the lowest month (UVB-4), precipitation of the warmest quarter (bio18), the DEM (Digital Elevation Model), and annual precipitation (bio12) were the key variables affecting the distribution area of Nitraria L, with contributions of 54.4%, 11.1%, 8.3%, 7.4%, and 4.1%, respectively. The Nitraria L. plants are currently found mainly in Central Asia, North Africa, the neighboring Middle East, and parts of southern Australia and Siberia. In future scenarios, except for a small expansion of the 2030s scenario model Nitraria L., the potential suitable distribution areas showed a decreasing trend. The contraction area is mainly concentrated in South Asia, such as Afghanistan and Pakistan, North Africa, Libya, as well as in areas of low suitability in northern Australia, where there was also significant shrinkage. The areas of expansion are mainly concentrated in the Qinghai–Tibet Plateau to the Iranian plateau, and the Sahara Desert is also partly expanded. With rising Greenhouse gas concentrations, habitat fragmentation is becoming more severe. Center-of-mass migration results also suggest that the potential suitable area of Nitraria L. will shift northwestward in the future. This study can provide a theoretical basis for determining the scope of Nitraria L. habitat protection, population restoration, resource management and industrial development in local areas. Full article

Soil salinization is a significant global ecological issue that leads to soil degradation and is recognized as one of the primary factors hindering the sustainable development of irrigated farmlands and deserts. The integration of remote sensing (RS) and machine learning algorithms is increasingly employed to deliver cost-effective, time-efficient, spatially resolved, accurately mapped, and uncertainty-quantified soil salinity information. We reviewed articles published between January 2016 and December 2023 on remote sensing-based soil salinity prediction and synthesized the latest research advancements in terms of innovation points, data, methodologies, variable importance, global soil salinity trends, current challenges, and potential future research directions. Our observations indicate that the innovations in this field focus on detection depth, iterations of data conversion methods, and the application of newly developed sensors. Statistical analysis reveals that Landsat is the most frequently utilized sensor in these studies. Furthermore, the application of deep learning algorithms remains underexplored. The ranking of soil salinity prediction accuracy across the various study areas is as follows: lake wetland (R² = 0.81) > oasis (R² = 0.76) > coastal zone (R² = 0.74) > farmland (R² = 0.71). We also examined the relationship between metadata and prediction accuracy: (1) Validation accuracy, sample size, number of variables, and mean sample salinity exhibited some correlation with modeling accuracy, while sampling depth, variable type, sampling time, and maximum salinity did not influence modeling accuracy. (2) Across a broad range of scales, large sample sizes may lead to error accumulation, which is associated with the geographic diversity of the study area. (3) The inclusion of additional environmental variables does not necessarily enhance modeling accuracy. (4) Modeling accuracy improves when the mean salinity of the study area exceeds 30 dS/m. Topography, vegetation, and temperature are relatively significant environmental covariates. Over the past 30 years, the global area affected by soil salinity has been increasing. To further enhance prediction accuracy, we provide several suggestions for the challenges and directions for future research. While remote sensing is not the sole solution, it provides unique advantages for soil salinity-related studies at both regional and global scales. Full article

Desert vegetation is undergoing complex and diverse changes due to global climate change and human activities. To effectively utilize water resources and promote ecological recovery in desert areas, it is necessary to clarify the main driving mechanisms of vegetation growth in these regions. In this study, based on MODIS and Landsat 8 remote sensing image data, the vegetation changes and driving mechanisms before and after water diversion in the Kubuqi Desert from 2001 to 2020 were quantitatively analyzed using multiple linear regression, random forest, support vector machine, and deep neural network. The results show that the average NDVI in the study area has increased from 0.08 to 0.13 over the past 20 years, and the year of NDVI mutation corresponded with the lowest precipitation, which occurred in 2010. After the water diversion, under the combined influence of human and natural factors, NDVI increased steadily without any abrupt changes, indicating that water is the main limiting factor for vegetation growth. The change of NDVI also showed obvious spatial heterogeneity, among which the improvement of the southwest irrigation area was the most significant, and the area with NDVI above 0.1 showed an expanding trend, and the maximum value exceeded 0.4. This demonstrates that moderate water diversion can reduce desert areas, expand lake areas, and promote vegetation growth, yielding positive ecological effects. The integration of multiple linear regression, support vector machines, random forests, and deep neural network methods effectively reveals the driving mechanisms of NDVI and indirectly informs future water diversion intervals. Overall, these research results can provide a reliable reference for the efficient development of water diversion projects and have high application value. Full article

The Gran Desierto de Altar, located in Sonora, Mexico, represents an arid region that offers an opportunity to study microbial life under extreme conditions. This study analyzed the bacterial diversity present in two distinct types of desert sediments: sand dunes (SDs) and salt crusts (SCs) by culture-dependent and culture-independent methods. Environmental DNA was obtained for 16S rRNA gene amplicon sequencing to obtain taxonomic information using QIIME2. In SD, the bacterial communities comprised 24 phyla, with Actinobacteriota (30–40%), Proteobacteria (22–27%), Bacteroidota (9–11%), Firmicutes (7–10%), and Chloroflexi (3–6%) emerging as the most abundant. Notably, in SC, the archaeal phylum Halobacterota was predominant (37–58%). SC hosted 12 bacterial phyla, the most abundant being Firmicutes (14–30%), Bacteroidota (3–24%), and Proteobacteria (1–12%). Bacteria belonging to the phylum Firmicutes, including Metabacillus niabensis, Bacillus subtilis, Bacillus licheniformis, and Alkalibacillus haloalkaliphilus, were isolated using nutrient and saline media. Overall, our findings indicate that the taxonomic composition of the samples analyzed from the Gran Desierto de Altar is consistent with that found in arid environments worldwide. This study provides a basis for future studies focusing on microbial diversity, genetic potentials, and resistance mechanisms of microorganisms from arid environments. Full article

The red prickly pear fruit (Opuntia ficus-indica L. Mill), endemic from Mexico’s semi-desert regions and present in North Africa and Southern Europe, particularly Italy and Spain, is a valuable source of nutrients, bioactive compounds, and polysaccharides. This study used non-destructive techniques like microscopy and Raman and infrared (IR) spectroscopy to characterize polysaccharides extracted from two red prickly pear varieties. The polysaccharides constitute approximately 80% of the peel and 39–18% of the pulp; microscopy provided insights into its microstructural details, while Raman and IR spectroscopy enabled the identification of its specific functional groups. The results revealed distinct microstructural attributes: mucilage displays a microstructure influenced by the ratio of acidic to neutral sugar monomers; pectin exhibits a low degree of methoxylation alongside a characteristic egg-box structure facilitated by calcium ions; hemicellulose presents a delicate, porous layer; and cellulose reveals a layered microstructure supported by thin or robust fibers and calcium crystals. The functional groups identified via Raman and IR spectroscopy provided specific information that could be used to infer chemical interactions influenced by functional groups like hydroxyl, carboxyl, and methyl, suggesting potential binding, stabilization, and water retention properties that enhance their utility as functional ingredients in food products. These findings, obtained using non-destructive methods, enhance the understanding of the compositional and microstructural characteristics of polysaccharides in the red prickly pear, which, in turn, can be used to predict their promising technological applications as functional ingredients. Full article

Salix psammophila, C. Wang & Chang Y. Yang, a desert-adapted shrub, is recognized for its exceptional drought tolerance and plays a vital role in ecosystem maintenance. However, research on S. psammophila has been limited due to the lack of an efficient and reliable genetic transformation method, including gene functional studies. The Agrobacterium-mediated transient overexpression assay is a rapid and powerful tool for analyzing gene function in plant vivo. In this study, tissue culture seedlings of S. psammophila were utilized as the recipient materials, and the plant expression vector pCAMBIA1301, containing the GUS reporter gene, was transferred into the seedlings via an Agrobacterium-mediated method. To enhance the efficiency of the system, the effects of secondary culture time, Agrobacterium concentration, infection time, and co-culture duration on the transient transformation efficiency of S. psammophila were explored. The optimal combination for the instantaneous transformation of S. psammophila tissue culture seedlings mediated by Agrobacterium was determined as follows: a secondary culture time of 30 d, a value of OD₆₀₀ of 0.8, an infection time of 3 h, and a co-culture duration of 48 h. Subsequently, the effectiveness of the transformation system was validated using the S. psammophila drought response gene SpPP2C80. To further confirm the accuracy of the system, SpPP2C80-overexpressing Arabidopsis was constructed and drought resistance analysis was performed. The results were consistent with the transient overexpression of SpPP2C80 in S. psammophila tissue culture seedlings, indicating that this system can be effectively employed for studying gene function in S. psammophila. These findings provide essential information for investigating gene function in non-model plants and pave the way for advancements in molecular biology research in S. psammophila. Full article

Urban settlements can support significant biodiversity and provide a wide range of ecosystem services. Remote sensing (RS) offers valuable tools for monitoring and conserving urban biodiversity. Our research, funded by the Italian Recovery and Resilience Plan (National Biodiversity Future Centre—Urban Biodiversity), undertakes a systematic scientific review to assess the current status and future prospects of urban biodiversity evaluation using RS. An extensive literature search of indexed peer-reviewed papers published between 2008 and 2023 was conducted on the Scopus database, using a selective choice of keywords. After screening the titles, abstracts, and keywords of 500 articles, 117 relevant papers were retained for meta-data analysis. Our analysis incorporated technical (e.g., sensor, platform, algorithm), geographic (e.g., country, city extent, population) and ecological (biodiversity target, organization level, biome) meta-data, examining their frequencies, temporal trends (Generalized Linear Model—GLM), and covariations (Cramer’s V). The rise in publications over time is linked to the increased availability of imagery, enhanced computing power, and growing awareness of the importance of urban biodiversity. Most research focused on the Northern Hemisphere and large metropolitan areas, with smaller cities often overlooked. Consequently, data coverage is predominantly concentrated on Mediterranean and temperate habitats, with limited attention given to boreal, desert, and tropical biomes. A strong association was observed between the source of RS data (e.g., satellite missions), pixel size, and the purpose of its use (e.g., modeling, detection). This research provides a comprehensive summary of RS applications for evaluating urban biodiversity with a focus on the biomes studied, biodiversity targets, and ecological organization levels. This work can provide information on where future studies should focus their efforts on the study of urban biodiversity using remote sensing instruments in the coming years. Full article

In planning and monitoring measures to protect wildlife in an area, it is important to have a reliable baseline estimate of population size and trends. There has been minimal published information on a small population of elephants, a keystone and endangered species, in a large area west of Etosha National Park in Namibia, known locally as the Northern Highlands. It is a highly remote, mountainous area in which it is difficult to count elephants. It is semi-desert, where the protection of wildlife is at increasing risk from climate change events, and research on the elephant population is a priority. We interviewed 34 community game guards in the Northern Highlands, focusing on the number of elephants and distinguishing features in known groups. Based on the collated knowledge, and analysis to reduce double counting of known groups, we estimate that there are between 78 and 212 elephants in the Northern Highlands, with a best estimate of 128. The wide range is an indication of the current uncertainties in the method. However, we conclude that this low-cost method, if adapted based on lessons from this pilot study, would be applicable for longer-term ecological monitoring in areas that have a low population density. Full article

In this brief article, the green toad (Bufotes sitibundus) and the Levant water frog (Pelophylax bedriagae) were compared to better understand the adaptations needed by amphibians, specifically the green toad, to survive in arid regions and to inhabit a wide range of habitats. The information mainly comes from data gathered in Israel, a nation experiencing a shift from Mediterranean to desert ecosystems where both amphibian species can be found. Using these data, a qualitative model is put forward that showcases the differences between these two amphibians and illustrates how the green toad has adapted to arid environments. For instance, green toads travel to breeding and spawning sites during the rainy season. During this journey, they often have to cross roads, which puts them at risk of being hit by vehicles. The main distinction between the green toad and the water frog is that the green toad moves from land environments to water, while the water frog stays in its aquatic habitat for its entire life cycle. Full article

Remote agricultural regions in desert areas, such as Ghardaïa in southern Algeria, face significant challenges in energy supply due to their isolated locations and harsh climatic conditions. Harnessing solar energy through photovoltaic (PV) systems offers a sustainable solution to these energy needs. This study aims to identify suitable areas for PV power installations in Ghardaïa, utilizing a geographic information system (GIS) combined with the fuzzy analytical hierarchy process (AHP). Various environmental, economic, and technical factors, such as solar radiation, land use, and proximity to infrastructure, are incorporated into the analysis to create a multi-criteria decision-making framework. The integration of fuzzy logic into AHP enables a more flexible evaluation of these factors. The results revealed the presence of ideal locations for installing photovoltaic stations, with 346,673.30 hectares identified as highly suitable, 977,606.84 hectares as very suitable, and 937,385.97 hectares as suitable. These areas are characterized by high levels of solar radiation and suitable infrastructure availability, contributing to reduced implementation costs and facilitating logistical operations. Additionally, the proximity of these locations to agricultural areas enhances the efficiency of electricity delivery to farmers. The study emphasizes the need for well-considered strategic planning to achieve sustainable development in remote rural areas. Full article

Urban growth is vast in the United Arab Emirates (UAE) due to economic development, and there is a need to consider liveability and sustainable ecosystems for future urban expansion. Promising strategies for sustainability focus on minimizing a building’s effects on the environment and improving residents’ quality of life, which is important in the desert and when confronting the issues of water and climate change. Sustainable practices that impact the livelihood of people in the UAE include factors such as walkable areas, open space, policing, healthcare, education, housing, and ensuring friendly transport that enhance the overall quality of life of residents in the region. Recognizing and appreciating the UAE’s cultural values is crucial when incorporating these aspects, allowing references to the nation’s character when creating communal areas. The primary research included quantitative surveys of three identified communities, composed of fifty participants each, where the findings indicate partial to full compliance, with 85.7% of the liveability indices being about public transport and green space. Through this analysis, liveability and sustainability principles need to be trialed and incorporated into future urban development to embrace the ecology as well as the inhabitants. To realize these targets, the proposed study adopted a four-part approach. Initially, an analysis of related studies concerning the UAE or the Gulf area was carried out to obtain important liveability and quality-of-life factors. A total of 6 dimensions and 51 indicators were extracted from the literature to inform the next stage. Subsequently, the authors identified and evaluated the design of three chosen communities in various cities in the UAE concerning liveability and sustainability indices. Consequently, a conceptual redesign of a typical community was made, illustrating the improved quality of life and sustainability. Lastly, a survey with respective facets from an urban planning architect and environmental scientist cum environmental economist was conducted to evaluate the practicality of the proposed design. This research gives a comprehensive picture of how liveability and sustainable ecosystem concepts need to be implemented in the UAE urban context and offers a direction to develop lively, context-specific, culturally attached, and sustainable urban environments for the present day and for the future. Full article

Soil bulk density is a crucial indicator for assessing soil matter storage and soil quality. Due to the complexity of sampling soil bulk density, particularly in deeper layers, it is essential to study the spatial distribution patterns of soil bulk density and their influencing factors. To address the gap in large-scale studies of vertical (from surface to deeper layers) and horizontal (across a broad area) variations in soil bulk density in arid regions, this study focuses on Changji Prefecture, located in the central northern slope of the Tianshan Mountains and characterized by typical vertical zonation. By integrating classical statistics, geostatistics, and geographic information systems (GISs), this study investigates the spatial distribution patterns and driving factors of soil bulk density. The results indicate that soil bulk density in Changji Prefecture increases with soil depth, with significantly lower values in the surface layer than in deeper layers. Spatially, despite minimal variation in latitude, there is considerable elevation difference within the study area, with the lowest elevations in the central region. Soil bulk density exhibits a spatial distribution pattern of higher values in the northeast (desert areas) and lower values in the southwest (forest areas). The nugget effect in the surface layer (0–20 cm) is substantial at 44.9%, while the deeper layers (20–100 cm) show nugget effects below 25%, suggesting that the influence of both natural and anthropogenic factors on deep soil bulk density is limited and mainly affects the surface layer. Stepwise regression analysis indicates that among topographic factors, slope and elevation are the primary controls of spatial variability in soil bulk density across layers. This research demonstrates that, in arid regions, soil bulk density is influenced primarily by natural factors, with limited impact from human activities. These findings provide valuable data support and theoretical guidance for soil management, agricultural planning, and sustainable ecosystem development in arid regions. Full article

Surface roughness, interpreted in the wide sense of surface texture, is a generic term referring to a variety of aspects and scales of spatial variability of surfaces. The analysis of solid earth surface roughness is useful for understanding, characterizing, and monitoring geomorphic factors at multiple spatiotemporal scales. The different geomorphic features characterizing a landscape exhibit specific characteristics and scales of surface texture. The capability to selectively analyze specific roughness metrics at multiple spatial scales represents a key tool in geomorphometric analysis. This research presents a simplified geostatistical approach for the multiscale analysis of surface roughness, or of image texture in the case of images, that is highly informative and interpretable. The implemented approach is able to describe two main aspects of short-range surface roughness: omnidirectional roughness and roughness anisotropy. Adopting simple upscaling approaches, it is possible to perform a multiscale analysis of roughness. An overview of the information extraction potential of the approach is shown for the analysis of a portion of the Taklimakan desert (China) using a 30 m resolution DEM derived from the Copernicus Glo-30 DSM. The multiscale roughness indexes are used as input features for unsupervised and supervised learning tasks. The approach can be refined both from the perspective of the multiscale analysis as well as in relation to the surface roughness indexes considered. However, even in its present, simplified form, it can find direct applications in relation to multiple contexts and research topics. Full article

The Amuyo Ponds (APs) are a group of three brackish hydrothermal lagoons located at 3700 m above sea level in a pre-Andean setting in the Atacama Desert. Each pond shows a conspicuous green (GP), red (RP), or yellow (YP) coloration, and discharges water rich in arsenic and boron into the Caritaya River (Camarones Basin, northern Chile). Microorganisms are subjected to harsh environmental conditions in these ponds, and the microbial composition and diversity in the Amuyo Ponds’ sediments are unknown. The microbial life colonizing AP sediments was explored by metagenomics analyses, showing a diverse microbial life dominated by members of the bacterial domain, with nearly 800 bacterial genome sequences, and sequences associated with Archaea, Eukarya, and viruses. The genus Pseudomonas was more abundant in GP and YP sediments, while the genera Pseudomonas, Aeromonas, and Shewanella were enriched in RP sediments. Archaeal composition was similar in all sediments, and enriched with methanogens sequences from the Archaeoglobi and Halobacteria classes. Abundant fungi sequences were detected in all sediments from the phyla Blastocladiomycota and Ascomycota. We also report putative functional capabilities related to virulence and defense genes, the biosynthesis of secondary metabolites, and tolerance to arsenic. Thirteen bacterial and fourteen viral metagenome-assembled genomes were reconstructed and informed here. This work expands our knowledge on the richness of the microorganisms in the APs and open further studies on the ecology and genomics of this striking Andean geosite. Full article

Expanding projects to reclaim marginal land is the most effective way to reduce land use pressures in densely populated areas, such as Egypt’s Nile Valley and Delta; however, this requires careful, sustainable land use planning. This study assessed the agricultural potential of the El-Dabaa area in the northern region of the Western Desert, Egypt. It focused on assessing land capability, evaluating crop suitability, mapping soil variability, and calculating crop water requirements for twenty different crops. In this work, we evaluated land capability using the modified Storie index model and assessed soil suitability using the land use suitability evaluation tool (LUSET). We also calculated crop water requirements (CWRs) utilizing the FAO-CROPWAT 8.0 model. Additionally, we employed ArcGIS 10.8 to create spatial variability maps of soil properties, land capability classes, and suitability classes. Using a systematic sampling grid, 100 soil profiles were excavated to represent the spatial variability of the soil in the study area, and the physicochemical parameters of the soil samples were analyzed. The results indicated that the study area is primarily characterized by flat to gently sloping surfaces with deep soils. Furthermore, there are no restrictions on soil salinity or alkalinity, no sodicity hazards, and low CaCO₃ levels. On the other hand, the soils in the study area are coarse textured and have low levels of CEC and organic matter (OM), which are the major soil limiting factors. As a result, the land with fair capability (Grade 3) accounted for the vast majority of the study area (87.3%), covering 30599.4 ha. Land with poor capability (Grade 4) accounted for 6.5% of the total area, while non-agricultural land (Grade 5) accounted for less than 1%. These findings revealed that S2 and S3 are the dominant soil suitability classes for all the studied crops, indicating moderate and marginal soil suitabilities. Furthermore, there were only a few soil proportions classified as unsuitable (N class) for fruit crops, maize, and groundnuts. Among the crops studied, barley, wheat, sorghum, alfalfa, olives, citrus, potatoes, onions, tomatoes, sunflowers, safflowers, and soybeans are the most suitable for cultivation in the study area. The reference evapotranspiration (ETo) varied between 2.6 and 5.9 mm day⁻¹, with higher rates observed in the summer months and lower rates in the winter months. Therefore, the increase in summer ETo rates and the decrease in winter ones result in higher CWRs during the summer season and lower ones during the winter season. The CWRs for the crops we studied ranged from 183.9 to 1644.8 mm season⁻¹. These research findings suggest that the study area is suitable for cultivating a variety of crops. Crop production in the study area can be improved by adding organic matter to the soil, choosing drought-resistant crop varieties, employing effective irrigation systems, and implementing proper management practices. This study also provides valuable information for land managers to identify physical constraints and management needs for sustainable crop production. Furthermore, it offers valuable insights to aid investors, farmers, and governments in making informed decisions for agricultural development in the study region and similar arid and semiarid regions worldwide. Full article