Search

Mountains play a crucial role in shaping the climate of an area and subsequently, the environments and species that are suited to those particular conditions. Understanding the relationships between environmental conditions and their influence on the occurrence of a species is necessary to make informed decisions when conserving relevant habitats. This study evaluated and compared the potential for different interactions between climatic variables to describe the environmental preferences and the range of the Ladakh urial, a narrowly distributed sub‐species of Ovis vignei, in the arid Himalayas. Species distribution models were created from spatially thinned presence‐only occurrence data of 50 locations using a Maximum Entropy (Maxent) model. For this, we subdivided the modeled distribution into environmental categories with varying degrees of suitability. We identified a high cold precipitation to annual precipitation ratio typical of cold desert climates well suited to describe the highest quality environments for urial. The inverse, low warm precipitation to annual precipitation ratio was found to better describe the urial's range at the lower end of potential habitat. In this comparison, we observed that with the exclusion of unsuitable cold steppe habitat with a higher warm precipitation to annual precipitation ratio, we were able to refine the extent of this species range but at a trade‐off to the accurate description of high‐quality environments. This study demonstrated the strong potential of cold arid climatic conditions to describe the distribution of urial in India, which have implications for identifying important areas for the conservation and management of the species in the high altitude rangelands of Ladakh. [ABSTRACT FROM AUTHOR]

Crops' water requirement is generally higher than the annual average precipitation in arid environments characterized by scarce freshwater resources. While using saline water for irrigation can help sustain agriculture in water-stressed regions, several challenges arises concerning productivity and soil salinization. However, adoption of efficient irrigation techniques such as drip irrigation, irrigation scheduling, and deficit irrigation can help optimize water productivity and mitigate salinity problems in irrigated agriculture. In southern Tunisia, potato is considered among the main cultivated horticultural crops due to its high economic value while it is considered as a crop sensitive to salinity. This crop (cv. Spunta) was the subject of long-term studies (2002-2020) conducted during the fall period in the arid region of Médenine. The crop response to full and deficit irrigation with saline water was assessed for several seasons under contrasting climatic conditions. Scheduling using the soil water balance (SWB) method consisted of the total and/or partial replacement of accumulated crop evapotranspiration (ETc), as derived from climatic data and crop coefficients. The impact of decreasing amounts of irrigation waters on crop yield and soil salinity with waters having a salinity ranging between 3 and 7 dS m-1 was evaluated. Results showed improvements in yield (30% to 37%) obtained with the SWB strategy under actual farming conditions, supporting the use of this strategy for irrigation. Appropriate scheduling also seems to be a key element in saving water (15%-22%) and in reducing risks of soil salinization. In the dry environment of southern Tunisia, optimum supply seems to correspond to a replacement of 100% to approximately 70%-80% of ETc. Applying such irrigation levels resulted in a lower salinity buildup in the root zone and higher crop water productivity. Natural salt leaching seems to be more effective under a more humid soil profile. Yield decreases and soil salinity increases almost linearly (r² = 0.60) with decreasing irrigation water amounts. Future work should focus on the integration of management practices when using saline water. Investigating the relationship and interaction between irrigation amounts, cultivar, fertilizer supply, and salt leaching will help in resolving productivity and environmental issues. [ABSTRACT FROM AUTHOR]

This review aims to be a reference article on designing and manufacturing different SAP materials for use in agriculture. The structure used for the content described reveals significant progress in the agricultural sector in recent years. SAP materials to enhance sandy soil compactness, topology, and mechanical properties (swelling, water harvesting, and nutrient release). SAPs in agriculture also promote a 60–80% swelling rate, slow release of nutrients for plants to last longer, and maximum water retention. This systematic review examined methods for designing, manufacturing, and processing SAPs for their properties and impact on agriculture in arid areas and plant growth. SAP materials are designed and manufactured in three morphologies. The first is the preparation of technical processes for manufacturing SAP (hydrogel) powder. Second, SAPs are prepared by mixing the monomer solution and crosslinking agent and converting the SAP solution into fibers using an electrospinning machine and wet spinning technique. Finally, the sheet was produced using a spun lace (hydroentangling) machine that converts SAP fibers into sheets. Similarly, the production processes used a spun-bond machine that converts SAP powder into sheets and a sheet modeling machine that converts SAP fibers into SAP sheets. Furthermore, many SAP materials used for agriculture in arid areas, functional monomers, initiators, and cross-liner agents can be manufactured as powders, fibers, and sheets and have high success rates. This is demonstrated by the excellent maximum absorbent capacity, and maximum water retention of the sheets, followed by those of the fibers and powders. This is supported by the quantitative standards for SAP morphology manufacturing process cost, water absorption, and water retention time. Highlights: Characteristics of SAPs for use in agriculture. Design and manufacture of SAPs suitable for agriculture. Evaluation of SAP performance for use in agriculture. The appropriate SAP morphology should be chosen to ensure the maximum planting performance. [ABSTRACT FROM AUTHOR]

In nature, microbes do not thrive in seclusion but are involved in complex interactions within- and between-microbial kingdoms. Among these, symbiotic associations with mycorrhizal fungi and nitrogen-fixing bacteria are namely known to improve plant health, while providing resources to benefit other microbial members. Yet, it is not clear how these microbial symbionts interact with each other or how they impact the microbiota network architecture. We used an extensive co-occurrence network analysis, including rhizosphere and roots samples from six plant species in a natural desert in AlUla region (Kingdom of Saudi Arabia) and described how these symbionts were structured within the plant microbiota network. We found that the plant species was a significant driver of its microbiota composition and also of the specificity of its interactions in networks at the microbial taxa level. Despite this specificity, a motif was conserved across all networks, i.e., mycorrhizal fungi highly covaried with other mycorrhizal fungi, especially in plant roots—this pattern is known as assortativity. This structural property might reflect their ecological niche preference or their ability to opportunistically colonize roots of plant species considered non symbiotic e.g., H. salicornicum, an Amaranthaceae. Furthermore, these results are consistent with previous findings regarding the architecture of the gut microbiome network, where a high level of assortativity at the level of bacterial and fungal orders was also identified, suggesting the existence of general rules of microbiome assembly. Otherwise, the bacterial symbionts Rhizobiales and Frankiales covaried with other bacterial and fungal members, and were highly structural to the intra- and inter-kingdom networks. Our extensive co-occurrence network analysis of plant microbiota and study of symbiont assortativity, provided further evidence on the importance of bacterial and fungal symbionts in structuring the global plant microbiota network. [ABSTRACT FROM AUTHOR]

Constructed wetlands (CWs) have been widely recognised for efficiently removing many pollutants from wastewater, making them vital for environmental bioremediation. The substrates used in constructed wetlands are crucial in determining their overall performance, notably their ability to improve nitrogen and phosphorus removal from wastewater. This study aims to investigate the possibility of removing pollutants from wastewater using a pilot scale vertical flow constructed wetland (VFCW) planted with Phragmites australis applied to various substrates, such as gravel and sand in an arid climate in Southeast Algeria. The study involved using four basins, filled with sand and gravel. Two were planted with Phragmites australis and the others were left as a control without vegetation. The efficiency of the filtration systems was evaluated based on various physicochemical and organic parameters. Results showed that the highest hydraulic retention time is in the 7 days. The removal efficiency values are 84.38% for biological oxygen demand (DBO5), 77.45% for chemical oxygen demand (COD), and 83.30% for total solid matter (TSS) in the planted gravel filter. The planted sand filter had even higher removal efficiency values, with 89.59%, 85.80%, and 86.63% for DBO5, COD, and TSS, respectively. Nitrate concentration increased in all filters due to the complete transformation of ammonium into nitrate. NO2 -, NH4 +, and PO4 3-removal efficiencies were also higher in the planted sand filter 74.45%, 95.43%, and 77.64%, respectively. [ABSTRACT FROM AUTHOR]

Dryland ecosystems cover 40% of our planet's land surface, support billions of people, and are responding rapidly to climate and land use change. These expansive systems also dominate core aspects of Earth's climate, storing and exchanging vast amounts of water, carbon, and energy with the atmosphere. Despite their indispensable ecosystem services and high vulnerability to change, drylands are one of the least understood ecosystem types, partly due to challenges studying their heterogeneous landscapes and misconceptions that drylands are unproductive "wastelands." Consequently, inadequate understanding of dryland processes has resulted in poor model representation and forecasting capacity, hindering decision making for these at‐risk ecosystems. NASA satellite resources are increasingly available at the higher resolutions needed to enhance understanding of drylands' heterogeneous spatiotemporal dynamics. NASA's Terrestrial Ecology Program solicited proposals for scoping a multi‐year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. A primary goal of the scoping study is to gather input from the scientific and data end‐user communities on dryland research gaps and data user needs. Here, we provide an overview of the ARID team's community engagement and how it has guided development of our framework. This includes an ARID kickoff meeting with over 300 participants held in October 2023 at the University of Arizona to gather input from data end‐users and scientists. We also summarize insights gained from hundreds of follow‐up activities, including from a tribal‐engagement focused workshop in New Mexico, conference town halls, intensive roundtables, and international engagements. Plain Language Summary: Drylands are landscapes with limited water availability, which cover 40% of Earth's land surfaces, support billions of humans, and play a substantial role in Earth's weather and climate systems. However, these ecosystems are under threat from droughts and heatwaves. They are also poorly understood because of challenges measuring their highly diverse vegetation types and interspersed vegetation cover and because of incorrect perceptions that they are unimportant "wastelands." These limitations make it challenging to manage their landscapes and quantify how drylands are driving Earth's weather and climate. NASA solicited proposals for a multi‐year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. The ARID scoping study aims to design a plan for how NASA satellite, aircraft, and field instruments can be used to better understand dryland ecosystems and their response to change. A primary scoping goal is to engage with scientists and data‐users, especially those who manage land, to understand research and management priorities in drylands. Here, we discuss details of our meeting with over 300 scientists and data‐users in Tucson, AZ in October 2023. We also highlight feedback from our tribal‐focused workshop in New Mexico, conference town halls, and international meetings. Key Points: Adaptation and Response in Drylands (ARID) is a 1‐year scoping study for a multi‐year NASA Terrestrial Ecology dryland field campaignAn ARID workshop was held in Tucson, Arizona in October 2023 with more than 30 data end‐users and 300 scientists in attendanceFurther input from hundreds of researchers and end‐users was obtained through workshops, conference townhalls, and tribal engagement [ABSTRACT FROM AUTHOR]

Abstract This review aims to be a reference article on designing and manufacturing different SAP materials for use in agriculture. The structure used for the content described reveals significant progress in the agricultural sector in recent years. SAP materials to enhance sandy soil compactness, topology, and mechanical properties (swelling, water harvesting, and nutrient release). SAPs in agriculture also promote a 60–80% swelling rate, slow release of nutrients for plants to last longer, and maximum water retention. This systematic review examined methods for designing, manufacturing, and processing SAPs for their properties and impact on agriculture in arid areas and plant growth. SAP materials are designed and manufactured in three morphologies. The first is the preparation of technical processes for manufacturing SAP (hydrogel) powder. Second, SAPs are prepared by mixing the monomer solution and crosslinking agent and converting the SAP solution into fibers using an electrospinning machine and wet spinning technique. Finally, the sheet was produced using a spun lace (hydroentangling) machine that converts SAP fibers into sheets. Similarly, the production processes used a spun-bond machine that converts SAP powder into sheets and a sheet modeling machine that converts SAP fibers into SAP sheets. Furthermore, many SAP materials used for agriculture in arid areas, functional monomers, initiators, and cross-liner agents can be manufactured as powders, fibers, and sheets and have high success rates. This is demonstrated by the excellent maximum absorbent capacity, and maximum water retention of the sheets, followed by those of the fibers and powders. This is supported by the quantitative standards for SAP morphology manufacturing process cost, water absorption, and water retention time. Graphical Abstract

Abstract In nature, microbes do not thrive in seclusion but are involved in complex interactions within- and between-microbial kingdoms. Among these, symbiotic associations with mycorrhizal fungi and nitrogen-fixing bacteria are namely known to improve plant health, while providing resources to benefit other microbial members. Yet, it is not clear how these microbial symbionts interact with each other or how they impact the microbiota network architecture. We used an extensive co-occurrence network analysis, including rhizosphere and roots samples from six plant species in a natural desert in AlUla region (Kingdom of Saudi Arabia) and described how these symbionts were structured within the plant microbiota network. We found that the plant species was a significant driver of its microbiota composition and also of the specificity of its interactions in networks at the microbial taxa level. Despite this specificity, a motif was conserved across all networks, i.e., mycorrhizal fungi highly covaried with other mycorrhizal fungi, especially in plant roots—this pattern is known as assortativity. This structural property might reflect their ecological niche preference or their ability to opportunistically colonize roots of plant species considered non symbiotic e.g., H. salicornicum, an Amaranthaceae. Furthermore, these results are consistent with previous findings regarding the architecture of the gut microbiome network, where a high level of assortativity at the level of bacterial and fungal orders was also identified, suggesting the existence of general rules of microbiome assembly. Otherwise, the bacterial symbionts Rhizobiales and Frankiales covaried with other bacterial and fungal members, and were highly structural to the intra- and inter-kingdom networks. Our extensive co-occurrence network analysis of plant microbiota and study of symbiont assortativity, provided further evidence on the importance of bacterial and fungal symbionts in structuring the global plant microbiota network.

In this study, prominent dust source areas are identified along with their plume extent using high temporal frequency satellite observations. Hourly dust plume observations of the Dust Belt from geostationary‐orbit satellites are analyzed for the 2017‐12–2022‐11 period. To identify dust source areas and their extents, we back‐track plumes to their source, assessing source areas in terms of emission frequency, contribution, and plume extent patterns. This method advances over traditional source allocation techniques that rely on polar‐orbiting satellites based on a few daily passes and meteorological wind fields for backtracking. Our findings indicate that Boreal summer is the most intense season for most sources, except in the Southern Sahara, which experiences winterly winds. Our analysis also reveals significant contributions from regions within the Sahara that experience expansive but infrequent dust storms, highlighting the importance of considering both frequency and magnitude in understanding dust emissions. Plain Language Summary: This study focuses on the role of mineral dust, a significant climate constituent originating mainly from arid regions. Identifying where dust comes from and where it goes is essential for understanding how it affects the climate. To do so, we employ high temporal frequency satellite data to backtrack dust plumes to their sources, revealing key dust‐emitting regions and their seasonal variations. We also quantify each source area's frequency and magnitude of emissions and the spatial distribution of emanating dust plumes. Our findings show that summer is the peak season for most areas, except for the strongest dust sources, located in Southern Sahara, which peak in winter driven by seasonal winds. Additionally, some Saharan source areas exhibit severe storms but have been under‐emphasized because they were measured by the frequency of their storms. Key Points: High‐temporal‐resolution images from geostationary‐orbit satellites enable precise back‐tracking of dust source areasDust source areas are analyzed in terms of their emission frequency, contribution to the regional atmosphere, and corresponding plume extentSummer is the peak dust emission season for most sources in West Asia and Sahara and ephemeral lake beds are active during the dry season [ABSTRACT FROM AUTHOR]

A distinct coal break occurs widely in the late Early Jurassic in Central Asia, the cause of which, however, is still debated largely due to the uncertainty of its age constraint. In the Junggar Basin of northwestern China, this coal break coincides with the Sangonghe Formation, which is well exposed along the basin margins, and is mainly composed of lacustrine deposits rich in a variety of fossils, including plants, pollens and spores, bivalves, clam shrimps, insects and some vertebrates. Here we name them as the Sangonghe biota and review their biostratigraphic framework. The Sangonghe biota constrains the Sangonghe Formation to the late Pliensbachian to the early Aalenian. Abundant thermophilous plants and Classopollis, together with frequent occurrences of red beds and carbonate nodules in the middle part of the Sangonghe Formation, are indicative of an arid climate in Central Asia at that time. This arid interlude should be responsible for the coal break, which may be related to the global warming in the early Toarcian. However, more precise dating evidence is needed to substantiate this. [ABSTRACT FROM AUTHOR]

In the context of climate change, studying changes in rainfall patterns is a crucial area of research, remarkably so in arid and semi-arid regions due to the susceptibility of human activities to extreme events such as droughts. Employing predictive models to calculate drought indices can be a useful method for the effective characterization of drought conditions. This study applies two type of machine learning methods—long short-term memory (LSTM) and Neural Hierarchical Interpolation for Time Series Forecasting (N-HiTS)—to develop and deploy artificial neural network models with the aim of predicting the regional standardized precipitation index (SPI) in four regions of Zacatecas, Mexico. The predictor variables were a set of climatological time series data spanning from 1964 to 2020. The results suggest that the N-HiTS model outperforms the LSTM model in the prediction and forecasting of SPI time series for all regions in terms of performance metrics: the Mean Squared Error, Mean Absolute Error, Coefficient of Determination and ξ correlation coefficient range from 0.0455 to 0.5472, from 0.1696 to 0.6661, from 0.9162 to 0.9684 and from 0.9222 to 0.9368, respectively, for the regions under study. Consequently, the outcomes revealed the successful performance of the N-HiTS models in accurately predicting the SPI across the four examined regions. [ABSTRACT FROM AUTHOR]

This study proposes an innovative and sustainable solution for road repair using a variant of cold asphalt concrete obtained by combining petroleum sludges, serpentinites, and vitrified clay shales from the Moa region. This proposal aims to manage industrial waste more efficiently and reduce dependence on conventional construction material resources, thereby promoting sustainability in road repair. [ABSTRACT FROM AUTHOR]

Landscape productivity and resource dispersion are key drivers of the movement patterns of many species. In less productive environments, home ranges are generally larger as individuals travel further to access resources. The greater bilby (Macrotis lagotis) has been reintroduced to several feral predator exclosures to reduce their extinction risk. Understanding how landscape productivity and resource dispersion influence bilby space use is critical to enable effective management of populations in exclosures. At two exclosures, we tested three hypotheses: 1. Bilbies would preferentially utilize habitats with sandy substrates (<20% clay content), as they are suitable for digging burrows and foraging pits; 2. Home ranges would be larger at the arid site compared to the semi‐arid site due to lower productivity and patchier distribution of preferred habitats; and 3. Bilbies would travel further each night at the arid site to access preferred habitats. Rainfall was used as an indicator of productivity, and dispersion of preferred habitats as an indicator of resource dispersion. The study was undertaken during average rainfall conditions and under similar bilby population densities at both sites. GPS loggers recorded home ranges and movements of 10 bilbies at the arid site, and 11 bilbies at the semi‐arid site. Seventeen of the 21 bilbies preferentially utilized habitats with sandy substrates, which were less abundant at the arid site. There were no significant differences in home range size or nightly movements between the sites for either sex. We suggest the average rainfall conditions at both sites, and the dietary flexibility of bilbies, supported the maintenance of relatively small and stable home ranges (particularly for females). The effects of landscape productivity and resource dispersion on bilby space use are more likely to be evident during extended periods of below average rainfall. Bilby home range studies during low rainfall conditions (e.g. drought) are required for the effective, long‐term management of exclosure populations. [ABSTRACT FROM AUTHOR]

Drylands are characterized by high spatial variability in resource availability due to sporadic rainfall, topography of the landscape and important effects of animals. Resource availability gradients may trigger patterns in decomposer population abundances and activity, which could affect ecosystem functions such as decomposition. Here, we examined the influence of resource availability gradients on the importance of termites in the decomposition of wood and grass litter. We placed wood blocks and grass litter baits in bags accessible and inaccessible to termites across wood and grass resource gradients as determined by the presence or absence of a top mammalian predator and across topographic gradients during a 9‐month period in arid Australia. We hypothesized that grass‐eating termite activity would track grass abundance and wood‐eating termite activity would track wood abundance. Termites were the predominant decomposition agent at these sites. Termites contributed to 99.5% of wood decomposition and 83.9% of grass decomposition during our study period. For wood, the termite effect was spatially variable and increased with habitat wood availability, which was greatest on dunes and where top predators were absent. However, the contribution of termites to grass litter decomposition did not track grass availability or termite abundance. The highest effects of termites on grass decomposition rates were found in habitats where the absence of top predators led to low grass availability. Our findings highlight how spatial variability in resources in addition to other factors that we do not document but are known to be influenced by the presence of top predators, such as insectivore predation rates, across the landscape could affect ecosystem functions such as decomposition. [ABSTRACT FROM AUTHOR]

Camel milk stands as a vital resource for infants in arid and semi-arid regions. Despite representing a modest 0.36% of global milk production, its nutritional composition is remarkable. With 3.4% protein, 4.4% lactose, and 3.5% fat, it offers a unique blend of nutrients that is comprised of higher levels of essential vitamins and minerals compared with cow's milk. Notably, its vitamin C content surpasses that of cow's milk by a significant margin. This nutritional powerhouse is particularly beneficial for individuals allergic to cow's milk, as it lacks ß-lactoglobulin. Beyond its nutritional profile, camel milk contains nanobodies that stimulate immune responses, unsaturated fatty acids for heart health, and insulin-like proteins that are stomach-friendly. Moreover, its probiotic bacteria aid in reducing cholesterol absorption and possess antibacterial properties, further enhancing its health benefits. In essence, camel milk transcends its role as mere sustenance, emerging as a potent superfood with the potential to address various health complications. [ABSTRACT FROM AUTHOR]

Key message: The yield of epicuticular waxes of Bulnesia retama was increased mainly by water stress, and marginally by UV-B. Natural populations from the most stressful ecoregions showed higher productivity and plasticity. Bulnesia retama is a tree/shrub endemic to the arid and semi-arid zones of South America. This species produces outer stem waxes that can be used in industry, and has been exploited in the past degrading natural populations. Considering the need to diversify marginal dryland economies by making sustainable use of local resources, we aimed to study the productivity of outer stem waxes of natural populations of B. retama from three eco-regions with different environmental stress (rainfall and altitude). We studied the wax productivity of the three populations in response to water stress and UV-B. We conducted two pot experiments with seedlings propagated from seeds of the different environmental backgrounds. We regulated water availability by differential irrigation and manipulated UV-B using selective absorbance filters. We collected stem waxes by the traditional method of brushing dry stems. We found that water stress was the main promoter of stem wax production in this species, while the effect of UV-B was marginal, and was only detected in combination with water stress. Seedlings from the most stressful eco-regions showed the highest stem wax productivity and were the most plastic to variations in environmental conditions. Environmental stress, particularly water stress, was the determining factor in the outer stem wax yield of this species, and in the productive potential of different natural populations, which could be related to ecotypes with different wax yield potential. This knowledge can be used for exploiting this resource sustainably, to select ecotypes for cultivation, and to develop productive varieties through classical breeding. [ABSTRACT FROM AUTHOR]

ABSTRACT Mountains play a crucial role in shaping the climate of an area and subsequently, the environments and species that are suited to those particular conditions. Understanding the relationships between environmental conditions and their influence on the occurrence of a species is necessary to make informed decisions when conserving relevant habitats. This study evaluated and compared the potential for different interactions between climatic variables to describe the environmental preferences and the range of the Ladakh urial, a narrowly distributed sub‐species of Ovis vignei, in the arid Himalayas. Species distribution models were created from spatially thinned presence‐only occurrence data of 50 locations using a Maximum Entropy (Maxent) model. For this, we subdivided the modeled distribution into environmental categories with varying degrees of suitability. We identified a high cold precipitation to annual precipitation ratio typical of cold desert climates well suited to describe the highest quality environments for urial. The inverse, low warm precipitation to annual precipitation ratio was found to better describe the urial's range at the lower end of potential habitat. In this comparison, we observed that with the exclusion of unsuitable cold steppe habitat with a higher warm precipitation to annual precipitation ratio, we were able to refine the extent of this species range but at a trade‐off to the accurate description of high‐quality environments. This study demonstrated the strong potential of cold arid climatic conditions to describe the distribution of urial in India, which have implications for identifying important areas for the conservation and management of the species in the high altitude rangelands of Ladakh.

Abstract Dryland ecosystems cover 40% of our planet's land surface, support billions of people, and are responding rapidly to climate and land use change. These expansive systems also dominate core aspects of Earth's climate, storing and exchanging vast amounts of water, carbon, and energy with the atmosphere. Despite their indispensable ecosystem services and high vulnerability to change, drylands are one of the least understood ecosystem types, partly due to challenges studying their heterogeneous landscapes and misconceptions that drylands are unproductive “wastelands.” Consequently, inadequate understanding of dryland processes has resulted in poor model representation and forecasting capacity, hindering decision making for these at‐risk ecosystems. NASA satellite resources are increasingly available at the higher resolutions needed to enhance understanding of drylands' heterogeneous spatiotemporal dynamics. NASA's Terrestrial Ecology Program solicited proposals for scoping a multi‐year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. A primary goal of the scoping study is to gather input from the scientific and data end‐user communities on dryland research gaps and data user needs. Here, we provide an overview of the ARID team's community engagement and how it has guided development of our framework. This includes an ARID kickoff meeting with over 300 participants held in October 2023 at the University of Arizona to gather input from data end‐users and scientists. We also summarize insights gained from hundreds of follow‐up activities, including from a tribal‐engagement focused workshop in New Mexico, conference town halls, intensive roundtables, and international engagements.

Crops’ water requirement is generally higher than the annual average precipitation in arid environments characterized by scarce freshwater resources. While using saline water for irrigation can help sustain agriculture in water-stressed regions, several challenges arises concerning productivity and soil salinization. However, adoption of efficient irrigation techniques such as drip irrigation, irrigation scheduling, and deficit irrigation can help optimize water productivity and mitigate salinity problems in irrigated agriculture. In southern Tunisia, potato is considered among the main cultivated horticultural crops due to its high economic value while it is considered as a crop sensitive to salinity. This crop (cv. Spunta) was the subject of long-term studies (2002–2020) conducted during the fall period in the arid region of Médenine. The crop response to full and deficit irrigation with saline water was assessed for several seasons under contrasting climatic conditions. Scheduling using the soil water balance (SWB) method consisted of the total and/or partial replacement of accumulated crop evapotranspiration (ETc), as derived from climatic data and crop coefficients. The impact of decreasing amounts of irrigation waters on crop yield and soil salinity with waters having a salinity ranging between 3 and 7 dS m−1 was evaluated. Results showed improvements in yield (30% to 37%) obtained with the SWB strategy under actual farming conditions, supporting the use of this strategy for irrigation. Appropriate scheduling also seems to be a key element in saving water (15%–22%) and in reducing risks of soil salinization. In the dry environment of southern Tunisia, optimum supply seems to correspond to a replacement of 100% to approximately 70%–80% of ETc. Applying such irrigation levels resulted in a lower salinity buildup in the root zone and higher crop water productivity. Natural salt leaching seems to be more effective under a more humid soil profile. Yield decreases and soil salinity increases almost linearly (r2 = 0.60) with decreasing irrigation water amounts. Future work should focus on the integration of management practices when using saline water. Investigating the relationship and interaction between irrigation amounts, cultivar, fertilizer supply, and salt leaching will help in resolving productivity and environmental issues.

Abstract Changes in water availability have a substantial impact on the sustainability and maintenance of agriculture, with water footprint (WF) being a robust methodology to assess these transformations. The Guadalupe Valley is one of the places with the highest agricultural production in Mexico. Despite its semi-arid climatic conditions, it provides high-quality crops that are well-positioned in the world. The historical trend of rainfall and temperatures between 1987 and 2017 was analyzed to identify climatic patterns in the territory. Through the calculations of the water footprint of Grapevine and Olive crops, the sensitivity of the crops to recurrent water deficit and their adaptation in their yields to drought episodes was identified. The reduction in precipitation and occurrence of extreme temperatures have contributed significantly towards augmenting crop evapotranspiration and, consequently, intensifying crop irrigation demands. As a result, there has been an apparent increase in the consumption of WFagricultural since 2007. Thus, the period of highest WFagricultural consumption was 2014 (Extremely dry), as opposed to 2011 (Very wet). In particular, the lowest WFgreen consumptions were observed in extremely dry years, that is, > 20% of the WFagricultural intensifying drought events. Therefore, these periods were compensated with higher uses of WFblue and WFgray, which are inversely correlated with precipitation, where vine crops consume 73% more WFagricultural compared to olive plantations, showing greater interannual variability. These results contribute to analyzing the temporal evolution of water consumption for agriculture, providing a basis for rational water use strategies.

Seasonal and regional variations in biochemical and physiological parameters of Artemisia campestris (L.) were investigated. The quantification of proline by the formation of a coloured complex was done by coupling proline with ninhydrin. The determination of soluble sugars and the extraction of chlorophyll from the leaves were carried out. The seasonal average leaf proline concentration of plants from the arid region was higher than that from the semi-arid region. The more the seasonal temperature increases, the greater the concentration of proline, as with the concentrations of soluble sugars in the two study regions. The distribution and accumulation of certain minerals (e.g. Sodium and Potassium) in the plant can be modified to increase resistance to heat stress. [ABSTRACT FROM AUTHOR]

The evaluation of water resources management practices is essential for water usage decisions in regions with limited water resources. The literature provides numerous assessment frameworks, but many ignore the unique characteristics and conditions of some special arid and semi-arid regions, such as the Gulf Cooperation Council (GCC) countries, which lack any permanent rivers or lakes. Thus, this study, the first in a two-part series, seeks to develop a conceptual Sustainable Water Resources Management Assessment Framework (SWRM-AF). General and particular criteria explain how components and indicators were identified. The conceptual SWRM-AF provided here has four components (environment, economy, society, and infrastructure) and 24 indicators. Almost every indicator has been selected from the literature and is briefly explained and justified. This research presents, possibly for the first time, clear and straightforward directions for evaluating each indicator in colour-coded tables. To create a more holistic framework for arid and semi-arid regions, social indicators like "intervention acceptability" and environmental indicators for assessing the impacts of desalination treatment plants have been added to form a unique framework applicable to such regions. Therefore, the components and indicators of conceptual SWRM-AF could work collectively to aid the process of decision-making. The next phase is validating this framework using a participatory approach. [ABSTRACT FROM AUTHOR]

A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates (winter and non-winter) of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers (such as global impervious surface and global tree cover) to create binary masks from which to generate a balanced set of training data applied to a random forest classifier. For the land cover masks, stepwise threshold adjustments were applied to reflectance, spectral index values, and Euclidean distance layers, with 62 combinations evaluated. Global (all seven scenes) and regional (arid, tropics, and temperate) adaptive thresholds were computed. An annual 95th and 5th percentile NDVI composite was used to provide temporal corrections to the decision functions, and these corrections were compared against the original model. The accuracy assessment found that the regional adaptive thresholds for both the two-date land cover and the temporally corrected land cover could accurately map land cover type within nine-class (68.4% vs. 73.1%), six-class (79.8% vs. 82.8%), and five-class (80.1% vs. 85.1%) schemes. Lastly, the five-class and six-class models were compared with a manually labeled deep learning model (Esri), where they performed with similar accuracies (five classes: Esri 80.0 ± 3.4%, region corrected 85.1 ± 2.9%). The results highlight not only performance in line with an intensive deep learning approach, but also that reasonably accurate models can be created without a full annual time series of imagery. [ABSTRACT FROM AUTHOR]

Considering several logistical limitations associated with live trapping in arid environments, owl pellet analysis provides a potentially useful alternative to estimate small mammal diversity. Owl pellet analysis has been used to estimate local small mammal diversity under the assumption that the method can reliably reflect the composition of local small mammal assemblages. However, the validity of owl pellet contents for use in ecological assessments has not been established. Thus, the present study aimed to determine the potential for eastern barn owl (Tyto delicatula) pellet analysis to improve the monitoring of small mammals in arid Australia. We analysed two ecological datasets from Pilungah Reserve on the northern boundary of the Simpson Desert in central Australia to assess their effectiveness for detecting expected small mammal species: 250 owl pellets collected from a known roosting site and 5 years of small mammal records from historical, long‐term trapping surveys. Species composition and detection probability of mammals varied depending on the method used. Owl pellet analysis returned higher species richness overall, while traditional trapping methods indicated a higher probability of detecting certain mammal species (e.g., the wongai ningaui Ningaui ridei, brush‐tailed mulgara Dasycercus blythi and the hairy‐footed dunnart Sminthopsis hirtipes). Importantly, analysis of owl pellets revealed two mammal species that had never been detected at the study site (dusky hopping mouse Notomys fuscus and Carpentarian false antechinus Pseudantechinus cf. mimulus). We suggest that owl pellet analysis could be particularly valuable when used as a precursor or in concert with traditional trapping to monitor and assist in the conservation of small mammal species in arid environments. [ABSTRACT FROM AUTHOR]

Abstract In this study, prominent dust source areas are identified along with their plume extent using high temporal frequency satellite observations. Hourly dust plume observations of the Dust Belt from geostationary‐orbit satellites are analyzed for the 2017‐12–2022‐11 period. To identify dust source areas and their extents, we back‐track plumes to their source, assessing source areas in terms of emission frequency, contribution, and plume extent patterns. This method advances over traditional source allocation techniques that rely on polar‐orbiting satellites based on a few daily passes and meteorological wind fields for backtracking. Our findings indicate that Boreal summer is the most intense season for most sources, except in the Southern Sahara, which experiences winterly winds. Our analysis also reveals significant contributions from regions within the Sahara that experience expansive but infrequent dust storms, highlighting the importance of considering both frequency and magnitude in understanding dust emissions.

The objective was to determine a mathematical model to calculate the deposition velocity of the mud resulting from the washing of aggregates from the Jobo Base Business Unit of Sagua de Tánamo, which is transported by pipelines. Sampling, granulometric and densimetric analyzes were carried out and a complete factorial experiment design with four tests and two replications each was used. The input variable, percentage of solids, was studied at four levels (4%, 12%, 20% and 28%). It was determined that the clay contained in the mud, due to its predominant granulometry of less than 40 µm, classifies as silt. It was also revealed that the density of the solid is 1,901 kg/m3. The results of the deposition velocity determined by indirect measurement and those predicted by calculations using the Durand model were compared, with the aim of improving its precision and reliability, obtaining a relative coincidence error of less than 5%. A correction function is determined that quantifies the relationship between gravitational sedimentation velocity and deposition velocity. [ABSTRACT FROM AUTHOR]

In the context of climate change, studying changes in rainfall patterns is a crucial area of research, remarkably so in arid and semi-arid regions due to the susceptibility of human activities to extreme events such as droughts. Employing predictive models to calculate drought indices can be a useful method for the effective characterization of drought conditions. This study applies two type of machine learning methods—long short-term memory (LSTM) and Neural Hierarchical Interpolation for Time Series Forecasting (N-HiTS)—to develop and deploy artificial neural network models with the aim of predicting the regional standardized precipitation index (SPI) in four regions of Zacatecas, Mexico. The predictor variables were a set of climatological time series data spanning from 1964 to 2020. The results suggest that the N-HiTS model outperforms the LSTM model in the prediction and forecasting of SPI time series for all regions in terms of performance metrics: the Mean Squared Error, Mean Absolute Error, Coefficient of Determination and ξ correlation coefficient range from 0.0455 to 0.5472, from 0.1696 to 0.6661, from 0.9162 to 0.9684 and from 0.9222 to 0.9368, respectively, for the regions under study. Consequently, the outcomes revealed the successful performance of the N-HiTS models in accurately predicting the SPI across the four examined regions.

A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates (winter and non-winter) of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers (such as global impervious surface and global tree cover) to create binary masks from which to generate a balanced set of training data applied to a random forest classifier. For the land cover masks, stepwise threshold adjustments were applied to reflectance, spectral index values, and Euclidean distance layers, with 62 combinations evaluated. Global (all seven scenes) and regional (arid, tropics, and temperate) adaptive thresholds were computed. An annual 95th and 5th percentile NDVI composite was used to provide temporal corrections to the decision functions, and these corrections were compared against the original model. The accuracy assessment found that the regional adaptive thresholds for both the two-date land cover and the temporally corrected land cover could accurately map land cover type within nine-class (68.4% vs. 73.1%), six-class (79.8% vs. 82.8%), and five-class (80.1% vs. 85.1%) schemes. Lastly, the five-class and six-class models were compared with a manually labeled deep learning model (Esri), where they performed with similar accuracies (five classes: Esri 80.0 ± 3.4%, region corrected 85.1 ± 2.9%). The results highlight not only performance in line with an intensive deep learning approach, but also that reasonably accurate models can be created without a full annual time series of imagery.

Subterranean mammals representing a single subspecies occurring along an aridity gradient provide an appropriate model for investigating adaptive variation in thermal physiology with varying levels of precipitation and air temperature (Tair). This study examined the thermal physiological adaptations of common mole-rats (Cryptomys hottentotus hottentotus) across five populations along an aridity gradient, challenging the expectation that increased aridity would lead to reduced metabolic rate (MR), lower body temperatures (Tb), and broader thermoneutral zones (TNZ). No significant, consistent differences in MR, Tb, or thermal conductance were observed between populations, suggesting uniform thermoregulatory mechanisms across habitats. Instead, behavioral strategies such as huddling and torpor may play a more prominent role than physiological adaptations in managing temperature regulation and water balance. The study also observed osmoregulatory differences, with populations employing distinct behavioral cooling strategies in response to water availability. These results underscore the need for further research into the responses of subterranean species to climate change, particularly in understanding how increasing global temperatures and aridification might influence species distribution if they lack the physiological capacity to adapt to future climatic conditions., (© 2024. Published by The Company of Biologists Ltd.)

Lichens are significant components of the biological soil crust communities in gypsum ecosystems and are involved in several processes related to ecosystem functioning, such as water and nutrient cycles or protection against soil erosion. Although numerous studies centered on lichen taxonomy and ecology have been performed in these habitats, global information about lichen species from gypsum substrates or their distributional ranges at a global scale is lacking. Thus, we compiled a global data set of recorded lichen species growing on gypsum. This review is based on systematic searches in two bibliographic databases (Web of Science and the more specialized database Mattick's Literature Index) using various keywords related to the substrate or ecology (i.e., gypsum, gypsiferous, semiarid, saxicolous, terricolous). In addition, we revised lichen literature from countries with gypsum soils using Mattick's, Hamburg University's Worldwide checklist, and different national lichen checklists. Ultimately the review includes a total of 321 studies. This data set included 6114 specimen records belonging to 336 recorded lichen species from 26 countries throughout the world. The results showed large differences in the number of species recorded among countries, reflecting differences in the sampling effort. We provide a table with the number of studies and species in relation to gypsum surface in order to account for the bias produced by sampling effort. The number of studies carried out per country was not related to the gypsum surface but probably to other factors, such as accessibility to field sampling, economic or political factors, or the presence of a wider community of lichenologists. Thus, Spain and Germany hosted the highest number of recorded species (160 and 114 species, respectively). Outside the European continent, only a few countries had a large number of species: Morocco (46), United States (42), and Iran (37). Remarkably, countries from the southern hemisphere (i.e., Australia, Chile, Namibia, and South Africa) showed a low number of studies from gypsum lands, supporting the stated biases observed in sampling efforts among countries. Considering the most studied countries, the results show that Teloschistaceae was the most represented family in gypsum ecosystems followed by Verrucariaceae and Cladoniaceae. Regarding particular species, Psora decipiens and Squamarina lentigera were some of the most widespread and abundant species in these habitats. This data set constitutes a basic and first step toward a much more comprehensive database, to be periodically updated in future releases, which also serves to identify countries or territories where future studies should be accomplished. There are no copyright restrictions on the data; please cite this data paper if the data are used in publications and teaching events. [ABSTRACT FROM AUTHOR]

• The habitat template as the approach to design sustainable green roofs in Lima, Peru. • Some Lomas systems have similar edaphic conditions as extensive green roofs. • Lomas herb species with succulence and clonal capacity are ideal for green roofs in Lima. • Shrubs may fit better on semi-intensive green roofs due to their deep roots and erect growth. • Green roofs can function as alternative habitats for endangered Lomas species. Ongoing urbanisation and climate change threaten urban green (UG) spaces in Lima, exacerbated by conventional design and management methods. Extensive green roofs (GRs) are a promising alternative in Lima's context as they provide numerous benefits and are adapted to arid conditions. This study aimed to develop sustainable GRs in Lima by using the Lomas ecosystems as a habitat template. We analysed abiotic conditions and plant traits of Lomas communities and compared them with those of GRs. We compared species composition and edaphic properties from five Lomas around Lima with those of arid GR systems. Lomas and GR species were further classified into functional groups based on their functional traits. Amancaes, Lachay and Villa Maria del Triunfo (VMT) have soils with similar characteristics as arid GRs, and the most suited Lomas species were found there. The 'herb functional group', consisting of herbs with succulence and clonal capacity, may be suitable for GRs due to arid adaptations and creeping and clumping growth patterns. Given the endangered status of several Lomas species within this group, introducing them to GRs in Lima offers a conservation opportunity, helping their survival and establishing urban complementary habitats. Shrub species such as Heliotropium , Atriplex , Croton , and Trixis are the most frequent shrubs in Lomas and are crucial for preserving the structure and biodiversity of the ecosystem. However, the 'shrub functional group' may be better suited for semi-intensive GRs due to their deeper root systems and erect growth. The habitat template approach can aid biodiversity conservation by incorporating threatened and endemic Lomas species into GR systems. [ABSTRACT FROM AUTHOR]

Where they occur at high densities, herbivores are likely to impact ecosystems by functioning as nutrient vectors that shift nutrients from areas where they graze to other locations. Such lateral shifts in nutrients are important to understand as they can alter the balance of species interactions and composition of ecological communities. In arid Australia, kangaroo (Macropus spp.) populations have irrupted due to suppression of their chief predator and their presence can have marked impacts on vegetation and soils in areas where they graze. Kangaroos are hypothesised to facilitate the transport of nutrients by ingesting organic material and depositing it in the form of faecal matter and urine under the shade of trees where they rest during the day. Here, we investigate the role that kangaroos and shade play as nutrient vectors and nutrient sinks, respectively. We compared kangaroo visitation and soil nutrients under experimental shades with unshaded areas in an arid landscape with little natural shade. Kangaroo visitation was greatest at shaded plots. Dung accumulation was greater at shaded plots than unshaded plots. Total carbon (TC) was greater in soils within shaded plots than control plots; however, there was no difference in TC between shaded plots and procedural control plots. There was no difference in total nitrogen and plant available phosphorus between shaded, control and procedural control plots. Our findings demonstrate that the presence of shade in an arid landscape influences the microhabitat choice of kangaroos, but only partially supports the hypothesis that nutrients concentrate within the soil under shade. • Accumulation of kangaroo dung was greater in shaded plots than unshaded plots. • Kangaroos frequented shaded plots more than unshaded plots. • A significant difference in total carbon was found between shade and control plots. [ABSTRACT FROM AUTHOR]

Changes in water availability have a substantial impact on the sustainability and maintenance of agriculture, with water footprint (WF) being a robust methodology to assess these transformations. The Guadalupe Valley is one of the places with the highest agricultural production in Mexico. Despite its semi-arid climatic conditions, it provides high-quality crops that are well-positioned in the world. The historical trend of rainfall and temperatures between 1987 and 2017 was analyzed to identify climatic patterns in the territory. Through the calculations of the water footprint of Grapevine and Olive crops, the sensitivity of the crops to recurrent water deficit and their adaptation in their yields to drought episodes was identified. The reduction in precipitation and occurrence of extreme temperatures have contributed significantly towards augmenting crop evapotranspiration and, consequently, intensifying crop irrigation demands. As a result, there has been an apparent increase in the consumption of WF agricultural since 2007. Thus, the period of highest WF agricultural consumption was 2014 (Extremely dry), as opposed to 2011 (Very wet). In particular, the lowest WF green consumptions were observed in extremely dry years, that is, > 20% of the WF agricultural intensifying drought events. Therefore, these periods were compensated with higher uses of WF blue and WF gray , which are inversely correlated with precipitation, where vine crops consume 73% more WF agricultural compared to olive plantations, showing greater interannual variability. These results contribute to analyzing the temporal evolution of water consumption for agriculture, providing a basis for rational water use strategies., (© 2024. The Author(s).)