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Dry root rot (DRR) caused by Rhizoctonia bataticola [(Taub.) Butler] is an emerging disease of chickpea (Cicer arietinum L.) and a serious constraint to chickpea production in warm and arid regions. To identify the genomic regions conferring resistance to DRR, a total of 182 F9 derived Recombinant Inbred Lines (RILs) were developed from the cross between a susceptible line BG 212 and moderately resistant breeding line ICCV 08305. The parental lines and RILs were screened against Rb 6 isolate of R. bataticola using paper towel method under controlled environment at ICRISAT during 2016 and 2017. The RILs were genotyped with cost-effective SNP genotyping platform, Affymetrix® Axiom®CicerSNP array. As a result, a high-density genetic map with 13,110 SNP markers spanning 1224.11 cM with an average inter marker distance of 0.09 cM was developed. A single minor QTL ('qDRR-8') explaining 6.70% PVE with LOD scores 3.34 was identified on CaLG08 for DRR resistance which could be further explored for mining candidate genes and the linked SNP markers could be further validated for application in marker-assisted selection of DRR resistance in chickpea breeding programs. [ABSTRACT FROM AUTHOR]

Photovoltaic systems (PV) have been extensively used worldwide as a reliable and effective renewable energy resource due to their environmental and economic merits. However, PV systems are prone to several environmental and weather conditions that impact their performance. Amongst these conditions is dust accumulation, which has a significant adversative impact on the solar cells' performance, especially in hot and arid regions. This study provides a comprehensive review of 278 articles focused on the impact of dust on PV panels' performance along with other associated environmental factors, such as temperature, humidity, and wind speed. The review highlights the importance of modelling dust accumulation along with other ecological factors due to their interactive nature, and the differences between cleaning techniques and schedules effectiveness. Moreover, the study provides a review of statistical and artificial intelligence models used to predict PV performance and its prediction accuracies in terms of data size and complexity. Finally, the study draws attention to several research gaps that warrant further investigation. Among these gaps is the need for proper dynamic optimisation models for cleaning schedules and a more advanced machine and deep learning models to predict dust accumulation while considering environmental and ageing factors. [ABSTRACT FROM AUTHOR]

Drylands are vast and face threats from climate change and human activities. Traditional reviews cannot capture interdisciplinary knowledge, but bibliometric analysis provides valuable insights. Our study conducted bibliometric research of scientific production on climate change and land degradation in drylands using remote sensing. We examined 1527 Scopus-indexed publications to identify geographic and thematic hotspots, extracting leading authors, journals, and institutions. China leads in publications, followed by the US, Germany, and Australia. The US has the highest citation count. Collaboration networks involve the US, China, and European countries. There has been an exponential increase in remote sensing of land degradation in drylands (RSLDD) publications since 2011. Key journals include "International Journal of Remote Sensing" and "Remote Sensing of Environment". The analysis highlights the growing interest in the field, driven by Australia, the US, and China. Key areas of study are vegetation dynamics and land use change. Future perspectives for this scientific field involve promoting collaboration and exploring emerging technologies for comprehensive land degradation and desertification research. [ABSTRACT FROM AUTHOR]

This document discusses the challenges faced by plants in arid and semi-arid regions due to harsh environmental conditions such as limited rainfall, high temperatures, and poor soil nutrition. The document highlights the importance of understanding plant adaptation strategies to extreme environments in order to protect and manage local vegetation and ecosystems. The document presents research papers that cover various aspects of plant adaptation in arid regions, including water uptake mechanisms, physiological and biochemical adaptations, plant-soil microbial interactions, and ecosystem services. The research findings provide insights into how plants in arid regions adapt to environmental changes and maintain ecological balance. However, further research is needed to fully understand the processes and mechanisms of plant adaptation in extreme environments. [Extracted from the article]

Climatic events and other natural-related disasters experienced in the arid and semi-arid lands of northern Kenya negatively affect the pastoral livelihoods of the communities. Addressing vulnerability to climate shocks among pastoral communities of Kenya's Arid and Semi-lands presents a persistent challenge. Cash transfer programmes have increasingly grown as one mode of building household resilience. Understanding the role of cash transfer interventions on household resilience to climate shocks is key to policy programming. This paper aimed at determining the effects of cash transfers on household resilience to climate shocks. The paper evaluated the Hunger Safety Net Program, which is one of the largest unconditional cash transfer programs in Kenya. The Hunger Safety Net Program targeted poor people in northern Kenya including the counties of Turkana, Wajir, Marsabit, and Mandera. To establish the impact the paper compares households which received cash transfers with those that did not receive transfers. The panel fixed effects model was used to determine the effects of cash transfers on household resilience. The results indicate that cash transfers have positive significant effects on household resilience to climate shocks. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciencias Agroveterinarias is the property of Revista de Ciencias Agroveterinarias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Arid zone grassland is a crucial component of terrestrial ecosystems and plays a significant role in ecosystem protection and soil erosion prevention. However, accurately mapping grassland spatial information in arid zones presents a great challenge. The accuracy of remote sensing grassland mapping in arid zones is affected by spectral variability caused by the highly diverse landscapes. In this study, we explored the potential of a rectangular tile classification model, constructed using the random forest algorithm and integrated images from Sentinel-1A (synthetic aperture radar imagery) and Sentinel-2 (optical imagery), to enhance the accuracy of grassland mapping in the semiarid to arid regions of Ordos, China. Monthly Sentinel-1A median value images were synthesised, and four MODIS vegetation index mean value curves (NDVI, MSAVI, NDWI and NDBI) were used to determine the optimal synthesis time window for Sentinel-2 images. Seven experimental groups, including 14 experimental schemes based on the rectangular tile classification model and the traditional global classification model, were designed. By applying the rectangular tile classification model and Sentinel-integrated images, we successfully identified and extracted grasslands. The results showed the integration of vegetation index features and texture features improved the accuracy of grassland mapping. The overall accuracy of the Sentinel-integrated images from EXP7-2 was 88.23%, which was higher than the accuracy of the single sensor Sentinel-1A (53.52%) in EXP2-2 and Sentinel-2 (86.53%) in EXP5-2. In all seven experimental groups, the rectangular tile classification model was found to improve overall accuracy (OA) by 1.20% to 13.99% compared to the traditional global classification model. This paper presents novel perspectives and guidance for improving the accuracy of remote sensing mapping for land cover classification in arid zones with highly diverse landscapes. The study presents a flexible and scalable model within the Google Earth Engine framework, which can be readily customized and implemented in various geographical locations and time periods. [ABSTRACT FROM AUTHOR]

As arid lands expand across the globe, scholars increasingly turn to the archaeological record for examples of sustainable farming in extreme environments. The arid north coast of Peru was the setting of early and intensive irrigation-based farming; it is also periodically impacted by sudden, heavy rainfall related to the El Niño Southern Oscillation (ENSO) phenomenon. While the sociopolitical effects, technologies, and engineering expertise of these irrigation systems have been thoroughly examined and theorized, little is known about how farmers managed periods of water stress. The aim of this study is to test whether arid zone farming was supported by hybrid, intermittent flood and perennial water source systems in the prehispanic past. An arroyo in the Chicama Valley was selected for preliminary data collection, and these data are presented here: (1) drone photography of the arroyo capturing the aftermath of a recent (2023) rain event; and (2) potassium (K) soil test kit results from samples collected near suspected prehispanic check dam features in the same area. The paper combines these data with comparative examples from the literature to suggest that the prehispanic features functioned as water-harvesting infrastructure. The paper concludes that sustainable, arid zone farming can be supported by hybrid, intermittent flood and perennial water source systems. [ABSTRACT FROM AUTHOR]

Water scarcity is a global problem that particularly affects islands located in arid regions or regions with limited water resources. This issue has prompted the development of non-conventional water sources such as fossil fuel-powered desalination systems. Concern about the high energy and environmental costs associated with this type of facility has created the ideal framework for the proliferation of desalination projects powered by renewable energies, especially wind energy due to the multiple advantages it offers. This article provides a bibliometric analysis to identify the advances made in wind-powered desalination on islands. While many studies explore wind-powered desalination, none compile references specific to islands. This paper analyses islands' desalination needs and showcases wind-powered systems, exploring their types and uses. Firstly, the most relevant international scientific journals are identified to allow the subsequent selection and quantitative and qualitative analysis of articles directly dealing with wind-powered desalination systems. A total of 2344 articles obtained from the Scopus database were analyzed, of which 144 including 181 case studies were selected. Among the results of this study, an increasing year-on-year trend is observed in the number of published studies tackling wind-powered desalination. Finally, this paper presents a series of maps showing the most relevant facilities, projects, and data in this field, and provides an overview of the lessons learned in the decarbonization of desalination. [ABSTRACT FROM AUTHOR]

In environmentally sensitive areas, especially the arid and semi-arid regions, the greening stability process and its influencing factors can directly affect the sustainable development of the ecological environment. In this study, multi-source remote sensing data such as land use/cover data, MODIS NDVI, and soil moisture, methods such as stability index, vegetation quantitative remote sensing, and Geodetector were employed to analyze the sustainability of the greening process in the Mu Us Sandy in 2000–2020, which were viewed from three aspects: changes in stability of land use types and function, soil moisture change and influencing factors on greening stability. The results showed that, (1) From the stability of land use types, continuous stable ecological land accounted for more than 50%, showing that decreased from northwest toward southeast. (2) From the functional stability, NDVI showed a fluctuated growth (0.035/a), with an increasing distribution pattern from northwest to southeast. Additionally, Vegetation changes were unstable and concentrated in the western part of the study area (OtogBanner and Otog Front Banner), while the eastern part was stable, in which vegetation improvement took the main position. Moreover, mobile dunes almost disappeared, and semi-fixed dunes decreased and gradually shrank to the west of the sandy area, while fixed dunes soared and were concentrated in the middle of the sandy land. (3) From the soil moisture change, soil moisture at different underground depths showed an overall increasing trend, but the deep soil moisture was higher than the shallow, and spatial distribution varied greatly. (4) From the influencing factors, natural factors significantly influence greening stability, among which precipitation had a particularly profound impact, and interactions with other natural and social factors were higher explanatory. The paper aims to explore whether the ecological environment is developing in a good and orderly direction in the Mu Us Sandy Land, and the potential factors that cause its changes, to provide a theoretical basis for scientific governance in the Mu Us Sandy Land and other arid and semi-arid areas in the future. [ABSTRACT FROM AUTHOR]

This paper investigates how seasonal hyperspectral reflectance data (between 350 and 1800 nm) can be used to infer ecosystem properties for a semi-arid savanna ecosystem in West Africa using a unique in situ based dataset. Relationships between seasonal dynamics in hyperspectral reflectance, and ecosystem properties (biomass, gross primary productivity (GPP), light use efficiency (LUE), and fraction of photosynthetically active radiation absorbed by vegetation (FAPAR)) were analysed. Reflectance data (ρ) were used to study the relationship between normalised difference spectral indices (NDSI) and the measured ecosystem properties. Finally, also the effects of variable sun sensor viewing geometry on different NDSI wavelength combinations were analysed. The wavelengths with the strongest correlation to seasonal dynamics in ecosystem properties were shortwave infrared (biomass), the peak absorption band for chlorophyll a and b (at 682 nm) (GPP), the oxygen A-band at 761nm used for estimating chlorophyll fluorescence (GPP, and LUE), and blue wavelengths (FAPAR). The NDSI with the strongest correlation to: (i) biomass combined red edge reflectance (ρ705) with green reflectance (ρ587), (ii) GPP combined wavelengths at the peak of green reflection (ρ518, ρ556), (iii) the LUE combined red (ρ688) with blue reflectance (ρ436), and (iv) FAPAR combined blue (ρ399) and near infrared (ρ1295) wavelengths. NDSI combining near infrared and shortwave infrared were strongly affected by solar zenith angles and sensor viewing geometry, as were many combinations of visible wavelengths. This study provides analyses based upon novel multi-angular hyperspectral data for validation of Earth Observation based properties of semi-arid ecosystems, as well as insights for designing spectral characteristics of future sensors for ecosystem monitoring. [ABSTRACT FROM AUTHOR]

Simple Summary: Acute hepatitis, which is a rising public health issue globally, is mostly caused by the hepatitis E virus (HEV). There is a potential risk of camel-borne zoonotic HEV infection in the desert regions of the Middle East and Africa, where camels frequently interact with human populations and camel-derived food products constitute a component of the food chain. To better understand the current state of this subject, the current work's objective is to provide a scientific review of the detection of HEV genotypes seven and eight in camels around the world. Until today, no review paper has been published compiling and discussing the reports available on HEV in camels. More studies are required to ascertain the prevalence of HEV infection in camels worldwide. Additionally, because camels are utilized as a form of transportation in many countries and because HEV in these animals may pose a threat to public health, there is a possibility of foodborne transmission through contaminated camel products. Hepatitis E virus (HEV) represents a major cause of acute hepatitis and is considered an emerging public health problem around the world. In the Middle East's and Africa's arid regions, where camels frequently interact with human populations and camel-derived food products are a component of the food chain, camel-borne zoonotic HEV infection is a potential threat. To date, no review paper has been published on HEV in camels. As such, the purpose of the current work is to provide a scientific review of the identification of HEV genotypes seven and eight in camels worldwide to have a better understanding of the current status of this topic and to identify gaps in the current knowledge. Searches were carried out in the electronic databases PubMed, Mendeley, Web of Science, and Scopus, including studies published until 31 December 2022 (n = 435). Once the databases were checked for duplicate papers (n = 307), the exclusion criteria were applied to remove any research that was not relevant (n = 118). As a result, only 10 papers were found to be eligible for the study. Additionally, in eight of the ten studies, the rates of HEV infection were found to be between 0.6% and 2.2% in both stool and serum samples. Furthermore, four studies detected HEV genotype seven in dromedary camels, and two studies have shown HEV genotype eight in Bactrian camels. Interestingly, these genotypes were recently reported in camels from the Middle East and China, where one human infection with HEV genotype seven has been associated with the consumption of contaminated camel meat and milk. In conclusion, more research will be needed to determine the prevalence of HEV infection in camels around the world as well as the risk of foodborne transmission of contaminated camel products. As camels are utility animals in several countries, HEV in these animals may pose a potential risk to public health. [ABSTRACT FROM AUTHOR]

We quantified the temporal trend and climatic sensitivity of vegetation phenology in dryland ecosystems in the US Great Basin during 1982-2011. Our results indicated that vegetation greenness in the Great Basin increased significantly during the study period, and this positive trend occurred in autumn but not spring and summer. Spatially, increases in vegetation greenness were more apparent in the northwestern, southeastern, and eastern Great Basin but less apparent in the central and southwestern Great Basin. In addition, the start of growing season (SOS) was not advanced while the end of growing season (EOS) was delayed significantly at a rate of 3.0 days per decade during the study period. The significant delay in EOS and lack of earlier leaf onset caused growing season length (GSL) to increase at a rate of 3.0 days per decade during 1982-2011. Interestingly, we found that the variation of mean vegetation greenness in the period of March to November (SSA) was not significantly correlated with its mean surface air temperature but was strongly correlated with its total precipitation. Seasonally, the variation of mean vegetation greenness in spring, summer, and autumn was mainly attributable to changes in pre-season precipitation in winter and spring. Nevertheless, climate warming played a strong role in extending GSL that in turn resulted in the upward trend in mean vegetation greenness during 1982-2011. Overall, our results suggested that changes in wintertime and springtime precipitation played a stronger role than temperature in affecting the interannual variability of vegetation greenness while climate warming was mainly responsible for the 30-year upward trend in the magnitudes of mean vegetation greenness in the dryland ecosystems during 1982-2011. [ABSTRACT FROM AUTHOR]

Accurate estimation of surface evapotranspiration (ET) in the Heihe River Basin using remote sensing data is crucial for understanding water dynamics in arid regions. In this paper, by coupling physical constraints and machine learning for hybrid modeling, we develop a hybrid model based on surface conductance optimization. A hybrid modeling algorithm, two physical process-based ET algorithms (Penman–Monteith-based and Priestley–Taylor-based ET algorithms), and three pure machine learning algorithms (Random Forest, Extreme Gradient Boosting, and K Nearest Neighbors) are comparatively analyzed for estimating the ET. The results showed that, in general, the machine learning model optimized by parameters was able to better predict the surface conductance of the hybrid model. Driver analyses showed that radiation, normalized difference vegetation index (NDVI), and air temperature had high correlations with ET. The hybrid model had a better prediction performance for ET than the other five models, and it improved the R2 of the two physical process-based algorithms to 0.9, reduced the root mean square error (RMSE) to 0.5 mm/day, reduced the BIAS to 0.2 mm/day, and improved the Kling–Gupta efficiency (KGE) to 0.9. The hybrid model outperformed the others across different time scales, displaying lower BIAS, RMSE, and higher KGE. Spatially, its ET patterns aligned with regional vegetation changes, with superior accuracy in annual ET estimation compared to the other models. Comparison with other ET products shows that the estimation results based on the hybrid model have better performance. This approach not only improves the accuracy of ET estimation but also improves the understanding of the physical mechanism of ET estimation by pure machine learning models. This study can provide important support for understanding ET and hydrological processes under different climatic and biotic vegetation in other arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

Copyright of Pixo: Revista de Arquitetura Cidade e Contemporaneidade is the property of Pixo Revista de Arquitetura Cidade e Contemporaneidade and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The combination of seasonal shutdowns, water conveyance, cold, and drought can easily lead to the deterioration of the anti-seepage system and loess foundation of the canal, which contributes to the destruction of the slope. To reveal the failure mechanism of the collapsible loess canal slope, this paper is based on the results of laboratory tests and adopts numerical simulations to analyze the stability of the canal slope under different conditions. The results show that the shear strength indexes and elastic modulus E of loess decrease following an exponential pattern with the increase in wetting-drying and freezing-thawing (WD-FT) cycles. The height of the seepage overflow point yields little effect on the water level behind the impermeable membrane, whereas the height of the water level has a significant effect. In the operation period, the slope under any working conditions is in a relatively stable state. However, the slope with a water level of 4.5 m behind the impermeable membrane tends to be unstable after three WD-FT cycles during the shutdown period. By replacing the surface-degraded loess with sand gravel and picking a depth of 0.9–1.2 m, the slope will maintain a long-term stable state. [ABSTRACT FROM AUTHOR]

The study of ancient irrigation is crucial in the archaeological research of arid regions. It covers a wide range of topics, with the Near East being the focus for decades. However, political instability and limited data have posed challenges to these studies. The primary objective is to establish a standardised method applicable to different arid environments using the Google Earth Engine platform, considering local relief of terrain and seasonal differences in vegetation. This study integrates multispectral data from LANDSAT 5, Sentinel-2, SAR imagery from Sentinel 1, and TanDEM-X (12 m and 30 m) DSMs. Using these datasets, calculations of selected vegetation indices such as the SMTVI and NDVSI, spectral decomposition methods such as TCT and PCA, and topography-based methods such as the MSRM contribute to a comprehensive understanding of landscape irrigation. This paper investigates the influence of modern environmental conditions on the visibility of features like levees and palaeo-channels by testing different methods and parameters. This study aims to identify the most effective approach for each case study and explore the possibility of applying a consistent method across all areas. Optimal results are achieved by combining several methods, adjusting seasonal parameters, and conducting a comparative analysis of visible features. [ABSTRACT FROM AUTHOR]

The seasonal characteristics of fluorescence components in CDOM for lakes in the semi-arid region of Northeast China were examined by excitation-emission matrices fluorescence and parallel factor analysis (EEM-PARAFAC). Two humic-like peaks C1 (Ex/Em = 230, 300/425 nm) and C2 (Ex/Em = 255, 350/460 nm) and two protein-like B (Ex/Em = 220, 275/320 nm) and T (Ex/Em = 225, 290/360 nm) peaks were identified using PARAFAC. The average fluorescence intensity of the four components differed with seasonal variation from June and August 2013 to February and April 2014. The total fluorescence intensity significantly varied from 2.54 ± 0.68 nm-1 in June to the mean value 1.93 ± 0.70 nm-1 in August 2013, and then increased to 2.34 ± 0.92 nm-1 in February and reduced to the lowest 1.57 ± 0.55 nm-1 in April 2014. In general, the fluorescence intensity was dominated by peak C1, indicating that most part of CDOM for inland waters being investigated in this study was originated from phytoplankton degradation. The lowest C2 represents only a small portion of CDOM from terrestrial imported organic matter to water bodies through rainwash and soil leaching. The two protein-like intensities (B and T) formed in situ through microbial activity have almost the same intensity. Especially, in August 2013 and February 2014, the two protein-like peaks showed obviously difference from other seasons and the highest C1 (1.02 nm-1) was present in February 2014. Components 1 and 2 exhibited strong linear correlation (R² = 0.633). There were significantly positive linear relationships between CDOM absorption coefficients a(254) (R² = 0.72, 0.46, p < 0.01), a(280) (R² = 0.77, 0.47, p < 0.01), a(350) (R² = 0.76, 0.78, p < 0.01) and Fmax for two humic-like components (C1 and C2), respectively. A close relationship (R² = 0.931) was found between salinity and DOC. However, almost no obvious correlation was found between salinity and EEM-PARAFAC extracted components except for C3 (R² = 0.469). Results from this investigation demonstrate that the EEM-PARAFAC technique can be used to evaluate the seasonal dynamics of CDOM fluorescence components for inland waters in semiarid regions of Northeast China. [ABSTRACT FROM AUTHOR]

Knowledge of all the mechanisms and processes involved in soil CO2 emissions is essential to close the global carbon cycle. Apart from molecular diffusion, the main physical component of such CO2 exchange is soil ventilation. Advective CO2 transport, through soil or snow, has been correlated with the wind speed, friction velocity or pressure (p). Here we examine variations in subterranean CO2 molar fractions (Χc) over two years within a vertical profile (1.5 m) in a semiarid ecosystem, as influenced by short-timescale p changes. Analyses to determine the factors involved in the variations in subterranean Χc were differentiated between the growing period and the dry period. In both periods it was found that variations in deep Χc (0.5-1.5 m) were due predominantly to static p variations and not to wind or biological influences. Within a few hours, the deep Χc can vary by fourfold showing a pattern with two cycles per day, due to p oscillations caused by atmospheric tides. By contrast, shallow Χc (0.15 m) generally has one cycle per day as influenced by biological factors like soil water content and temperature in both periods, while the wind was an important factor in shallow Χc variations only during the dry period. Evidence of emissions was registered in the atmospheric boundary layer by eddy covariance during synoptic pressure changes when subterranean CO2 was released; days with rising barometric pressure -- when air accumulated belowground, including soil-respired CO2 -- showed greater ecosystem uptake than days with falling pressure. Future assessments of the net ecosystem carbon balance should not rely exclusively on Fick's law to calculate soil CO2 effluxes from profile data. [ABSTRACT FROM AUTHOR]

A method for detailed evaluation of a new satellite-derived global 28-yr cloud and radiation climatology (Climate Monitoring SAF Cloud, Albedo and Radiation dataset from AVHRR data, named CLARA-A1) from polar orbiting NOAA and Metop satellites is presented. The method combines 1 km and 5 km resolution cloud datasets from the CALIPSO-CALIOP cloud lidar for estimating cloud detection limitations and the accuracy of cloud top height estimations. Cloud detection is shown to work efficiently for clouds with optical thicknesses above 0.30 except for at twilight conditions when this value increases to 0.45. Some misclassifications generating erroneous clouds over land surfaces in semi-arid regions in the sub-tropical and tropical regions are revealed. In addition, a substantial fraction of all clouds remains undetected in the Polar regions during the polar winter season due to the lack of or an inverted temperature contrast between Earth surfaces and clouds. Subsequent cloud top height evaluation took into account the derived information about the cloud detection limits. It was shown that this has fundamental importance for the achieved results. An overall bias of -274m was achieved compared to a bias of -2762m if no measures were taken to compensate for cloud detection limitations. Despite this improvement it was concluded that high-level clouds still suffer from substantial height underestimations while the opposite is true for low-level (boundary layer) clouds. The validation method and the specifically collected satellite dataset with optimal matching in time and space are suggested for a wider use in the future for evaluation of other cloud retrieval methods based on passive satellite imagery. [ABSTRACT FROM AUTHOR]

We conducted high frequency measurements of the δ18 O value of atmospheric CO2 from a juniper (Juniperus monosperma) woodland in New Mexico, USA, over a four- year period to investigate climatic and physiological regulation of the δ18O value of ecosystem respiration (δR). Rain pulses reset δR with the dominant water source isotope composition, followed by progressive enrichment of δR. Transpiration (ET) was significantly related to post-pulse δR enrichment because leaf water δ18O value showed strong enrichment with increasing vapor pressure deficit that occurs following rain. Post-pulse δR enrichment was correlated with both ET and the ratio of ET to soil evaporation (ET/ES). In contrast, soil water δ18O value was relatively stable and δR enrichment was not correlated with ES. Model simulations captured the large post-pulse δR enrichments only when the offset between xylem and leaf water δ18O value was modeled explicitly and when a gross flux model for CO2 retro-diffusion was included. Drought impacts δR through the balance between evaporative demand, which enriches δR, and low soil moisture availability, which attenuates δR enrichment through reduced ET. The net result, observed throughout all four years of our study, was a negative correlation of post-precipitation δR enrichment with increasing drought. [ABSTRACT FROM AUTHOR]

We studied the relationships between crust microstructure, infiltration and water holding capacity under arid and temperate conditions (Factor A: Climate) on biological soil crusts (BSCs) sampled along a catena on mobile sand dunes (Factor B: Catena). The arid study site was located near Nizzana, Israel (precipitation: 86mma-1, PET: ~2500mma-1) and the temperate site near Lieberose, Germany (precipitation: 569mma-1, PET: ~780mma-1). BSCs were sampled near the dune crest, at the centre of the dune slope and at the dune base at each site. Scanning electron microscopy (SEM) was used to characterize BSC morphology and microstructure. Infiltration was determined using microinfiltrometry under controlled moisture conditions in the lab. Water holding capacities were determined after water saturation of the dry BSCs. Wettability of the crusts was characterized using a "repellency index", which was calculated from water and ethanol sorptivities. Irrespective of the climate, an accumulation of fine particles in the BSCs was found, increasing along the catena from dune crest to dune base. Texture was finer and water holding capacities of the underlying substrate were higher at the arid site, whereas surface wettability was reduced at the temperate site. At both sites, BSCs caused extra water holding capacity compared to the substrate. Infiltration rates decreased along the catena and were generally lower at the dune slope and base of the arid site. A mechanism of crust stabilization is proposed where BSCs benefit from increased texture and biomass mediated water supply, and where the water supply to higher plants was limited due to alteration of physico-chemical surface properties under temperate conditions. [ABSTRACT FROM AUTHOR]

The management of agroecosystems plays a crucial role in the global carbon cycle with soil tillage leading to known organic carbon redistributions within soils and changes in soil CO2 emissions. Yet, discrepancies exist on the impact of tillage on soil CO2 emissions and on the main soil and environmental controls. A meta-analysis was conducted using 46 peer-reviewed publications totaling 174 paired observations comparing CO2 emissions over entire seasons or years from tilled and untilled soils across different climates, crop types and soil conditions with the objective of quantifying tillage impact on CO2 emissions and assessing the main controls. On average, tilled soils emitted 21% more CO2 than untilled soils, which corresponded to a significant difference at P < 0.05. The difference increased to 29% in sandy soils from arid climates with low soil organic carbon content (SOCC < 1%) and low soil moisture, but tillage had no impact on CO2 fluxes in clayey soils with high background SOCC (> 3%). Finally, nitrogen fertilization and crop residue management had little effect on the CO2 responses of soils to no-tillage. These results suggest no-tillage is an effective mitigation measure of carbon dioxide losses from dry land soils. They emphasize the importance of including information on soil factors such as texture, aggregate stability and organic carbon content in global models of the carbon cycle. [ABSTRACT FROM AUTHOR]

Lanzhou City is located in the semi-arid region of northwest China, which experiences serious desertification. Moreover, the high intensity of land development, with the accelerated industrialization and urbanization, causes increasingly aggravated conflict between humans and the environment. Exploring the response of the ecological environment quality to the natural environment and anthropogenic activities is important to protect the sustainable development of urban economic construction and the environment. Based on the Google Earth Engine (GEE) platform, this paper constructed a modified Remote Sensing Ecological Index (MRSEI) model which could reflect the ecological environment quality by integrating the desertification index (DI) into the Remote Sensing Ecological index (RSEI) model. This paper explores the spatiotemporal variation in the environmental quality from 2000 to 2020 in Lanzhou, China, and analyzes the natural and anthropogenic factors affecting the environment quality in terms of temperature, precipitation, gross domestic product (GDP), land use, night lighting, and population. The results showed that the mean value of MRSEI ranged from 0.254 to 0.400. The area undergoing fast growth in ecological quality was in the northwestern part of Lanzhou, and the area of decrease was in the central part. Various factors have different degrees of influence on the ecosystem, with temperature, precipitation, and land use having a greater impact, and GDP and population having a limited impact. Precipitation and temperature showed a strong impact when interacting with other factors, demonstrating that precipitation and temperature were also key factors affecting MRSEI. Overall, climate change and the implementation of ecological restoration projects have led to an improvement in the quality of the ecological environment in Lanzhou. This study provides a reference for understanding the spatiotemporal changes in the ecological environment in semi-arid Lanzhou and is conducive to formulating proper protection strategies. [ABSTRACT FROM AUTHOR]

Atriplex canescens is widely cultivated as drought and salt-tolerant fodder in arid regions of Northwest China, which is used for photoremediation of degraded land and soil and water conservation. To explore the growth performance of A. canescens when exposed to drought and salt stress, seedlings were treated with a range of drought stress (WC1: 75 ± 3.6%, WC2: 49 ± 2.9% and WC3: 27 ± 2.5% of soil water content) and the corresponding drought stress with additional sodium salt supplementation (NaCl:Na2SO4 = 1:1 with the total concentration of Na+ set to 150 mM). The findings of this paper indicated that moderate sodium salt could stimulate the growth of A. canescens and effectively alleviate the deleterious impact of drought stress by increasing the turgor potential (ψt) and relative water content (RWC) and decreasing the leaf water osmotic potential (ψs). Furthermore, the photosynthetic capacity was improved and the negative effects of drought stress on photosystem II (PSII) were mitigated. The extra 150 mM sodium salt also markedly increased the contribution of Na+ to ψs and the contribution of betaine to ψs. In summary, these results indicate that A. canescens can adapt to drought stress by accumulating enough Na+ for osmotic adjustment (OA). Additionally, this paper is aimed to provide a fundamental basis for the utilization and cultivation of A. canescens as a favored pasture crop in the Qaidam basin, thus increasing the ecological and environmental benefits for arid regions worldwide. [ABSTRACT FROM AUTHOR]

The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant "warming and wetting" since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO. [ABSTRACT FROM AUTHOR]

This paper examines a feature-level fusion framework for detecting and mapping land degradation (LD) and enabling sustainable land management (SLM) in semi-arid areas using optical sensors and Synthetic Aperture Radar (SAR) satellite data. The objectives of this review were to (i) determine the trends and geographical location of land degradation mapping publications, (ii) to identify and report current challenges pertaining to mapping LD using multiscale remote sensing data, (iii) to recommend a way forward for monitoring LD using multiscale remote sensing data. The study reviewed 78 peer-reviewed research articles published over the past 24 years (1998–2022). Image fusion has the potential to be more useful in various remote sensing applications than individual sensor image data, making it more informative and valuable in the interpretation process. In addition, this review discusses the importance of SAR and optical image fusion, pixel-level techniques, applications, and major classes of quality metrics for objectively assessing fusion performance. The literature review alluded that the SAR and optical image fusion in the detection and mapping of land degradation and enabling sustainable land management has not been fully explored. Advanced techniques such as the fusion of SAR and optical satellite imageries need to be incorporated for the detection and mapping of LD, as well as the promotion of SLM in halting LD in South African drylands and around the world. We conclude that there is scope for further research on the fusion of SAR and optical images, as new micro-wave and optical sensors with higher resolution are introduced on a regular basis. The results of this review contribute to a better understanding of the applications of SAR and optical image fusion in future research in the severely degraded drylands of southern Africa. The fusion of SAR and optical data still remains an open challenge. The future of different remote sensing applications lies in this kind of fusion. Land degradation is one of the greatest challenges amongst the environmental problems in South Africa, causing a reduction in the capacity of the land to perform ecosystem functions and services that support society and development. Yet, in South Africa, there are no studies that have widely investigated the potential for a fusion of SAR and optical data to detect and map land degradation and SLM practices. This paper established a baseline for understanding the application of a fusion of SAR and optical data as rapid tools for mapping, monitoring, and evaluating LD, as well as the impacts of SLM practices in South Africa's degraded drylands. [ABSTRACT FROM AUTHOR]

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The article presents various titles of research papers related to geography by the Association of American Geographers. Some of papers included are "The General Magnetic Survey of the Earth," by L.A. Bauer, "Land Sculpturing in Arid Lands with Observations from Northeastern Africa," by W.H. Hobbs, "The Platforms of Barrier Coral Reefs," by T. Wayland Vaughan, "Botanical Phenomena and the Problem of Coastal Subsidence," by D.W. Johnson, "Characteristics of the Mississippi Delta in the Light of Comparative Studies of Some Old-World Deltas," by E.W. Shaw.

As an important component of ecosystem carbon budgets, soil carbon dioxide (CO2) flux is determined by a combination of a series of biotic and abiotic processes. Although there is evidence that the abiotic component can be important in total soil CO2 flux, its relative importance has never been systematically assessed. In this study, the total soil CO2 flux (Rtotal) was partitioned into biotic (Rbiotic) and abiotic (Rabiotic) components over eight typical landscapes in a desert-oasis ecotone, including cotton field, hops field, halophyte garden, reservoir edge, native saline desert, alkaline soil, dune crest and interdune lowland in the Gurbantunggut Desert, and the relative importance of these two components was analyzed. Results showed that Rabiotic always contributed to Rtotal for the eight landscapes, but the degree of contribution varied greatly. In the cotton and hops fields, the ratio of Rabiotic to Rtotal was extremely low (< 10%); whereas Rabiotic was dominant in the alkaline soil and dune crest. Statistically, Rabiotic=Rtotal decreased logarithmically with rising Rbiotic, suggesting that Rabiotic strongly affected Rtotal when Rbiotic was low. This pattern confirms that soil CO2 flux is predominantly biological in most ecosystems, but Rabiotic can dominate when biological processes are weak. On a diurnal basis, Rabiotic resulted in no net gain or loss of carbon but its effect on instantaneous CO2 flux was significant. Temperature dependence of Rtotal varied among the eight landscapes, determined by the predominant components of CO2 flux: with Rbiotic driven by soil temperature and Rabiotic regulated by the rate of change in temperature. Namely, declining temperature resulted in negative Rabiotic (CO2 went into soil), while rising temperature resulted in a positive Rabiotic (CO2 released from soil). Furthermore, without recognition of Rabiotic, Rbiotic would have been either overestimated (for daytime) or underestimated (for nighttime). Thus, recognition that abiotic component in total soil CO2 flux is ubiquitous in soils has widespread consequences for the understanding of carbon cycling. While the abiotic flux will not change net daily soil CO2 exchange and not likely directly constitute a carbon sink, it can alter transient soil CO2 flux significantly, either in magnitude or in its temperature dependency. [ABSTRACT FROM AUTHOR]

Reservoirs on rivers can disrupt organic carbon (OC) transport and transformation, but less is known how downstream river reaches directly below dams contribute to OC processing than reservoirs alone. We compared how reservoirs and their associated tailwaters affected OC quantity and quality by calculating particulate (P) OC and dissolved (D) OC fluxes, and measuring composition and bioavailability of DOC. We sampled the Yampa River near Maybell, Colorado, USA and the Green River above and below Fontenelle and Flaming Gorge reservoirs, and their respective tailwaters from early snowmelt to base flow hydrological conditions. In unregulated reaches (Yampa River, Green River above Fontenelle reservoir), DOC and POC concentrations increased with snowmelt discharge. POC and DOC concentrations also increased with stream discharge below Fontenelle reservoir, but there was no relationship between DOC and stream flow below Flaming Gorge reservoir. The annual load of POC was 3-fold lower below Fontenelle Reservoir and nearly 7-fold lower below Flaming Gorge reservoir, compared to their respective upstream sampling sites. DOC exported to downstream reaches from both reservoirs was less bioavailable, as measured with bioassays, than DOC upriver of the reservoirs. Lastly, tailwater reaches below the reservoirs generated OC, exporting 1.6-2.2 g Cm-2 d-1 of OC to downstream ecosystems. Changes in total fluxes from upstream to downstream of reservoirs and their tailwaters do not represent the simultaneous transformation and production of OC, which may lead to the underestimation of the quantity of OC mineralized, transformed, or retained in coupled river-reservoir-tailwater ecosystems. [ABSTRACT FROM AUTHOR]

Bioclimatic architecture is a sustainable design approach that aims to create buildings that put local climate characteristics into consideration and utilize the natural environment to achieve thermal comfort and reduce energy consumption. Among the various strategies used in bioclimatic architecture, natural ventilation stands out as a cost-effective and eco-friendly method that allows for the flow of air through buildings to provide cooling and improve indoor air quality without relying on mechanical systems. With the growing concerns surrounding climate change and sustainable development, the use of natural ventilation techniques is becoming increasingly vital in buildings design. This paper investigates the importance of natural ventilation as one of the bioclimatic architecture strategies for sustainable building design in hot-arid regions characterized by extreme weather conditions, by providing an overview of the various natural ventilation strategies, including singlesided, double-sided, wind-induced, and stack ventilation and identifies the key factors affecting air movement to enhance thermal comfort and indoor air quality inside spaces. The research findings reveal a set of design guidelines that can be implemented to optimize natural ventilation in hot-arid regions. These guidelines cover building orientation, form, vegetation, and the design of openings and natural ventilation strategies that are most suitable for this climate. [ABSTRACT FROM AUTHOR]

The Forest Fire Danger Index (FFDI) is the main measure used in Australia for estimating fire risk. Recent work by the authors showed that the FFDI forms stable state regimes, nominated as fire climate regimes. These regimes shifted to greater intensity in southern and eastern Australia around the year 2000 and, a decade later, further north. Reductions in atmospheric moisture were the primary contributor. These changes have not been fully incorporated into future projections. This paper compares the recent regime shifts with the most recent national projections of FFDI, published in 2015. They show that for most states and regions, the 2030 upper limit is approached or exceeded by the recent shift, except for two states with large arid zones, South Australia and Western Australia. Methods for attributing past changes, constructing projections, and the inability of climate models to reproduce the recent decreases in atmospheric moisture, all contribute to these underestimates. To address these shortcomings, we make some suggestions to modify efforts aiming to develop seamless predictions and projections of future fire risk. [ABSTRACT FROM AUTHOR]

Open water transposition channels in hot and arid regions, like those in the São Francisco River Integration Project (PISF) in Brazil, suffer significant water losses through evaporation. This paper proposes covering these channels with photovoltaic (PV) panels to reduce evaporation while simultaneously generating clean energy. The research aims to quantify water savings and energy generation potential across all channel lengths and assess whether the generated solar power can substitute grid electricity for powering the transposition pumps during peak hours, thereby enhancing energy efficiency. This study analyzed the state-of-the-art of PV generation and calculated their solar potential. Identified the specific characteristics of PISF channels and watercourses considering the regional geography, meteorology, irradiation, and social peculiarities. And, finally, assessed the feasibility of covering the watercourses with solar panels. The results reveal that covering all current PISF channels with PV panels could save up to 25,000 cubic meters of water per day, significantly contributing to water security and improving the quality of life for the local population. Additionally, the project could generate 1200 gigawatt-hours of electricity annually, meeting the energy demands of the transposition pumps during peak hours and promoting energy efficiency within the project. This research paves the way for utilizing PV technology to address water scarcity challenges and enhance the sustainability of water infrastructure projects in arid regions worldwide. [ABSTRACT FROM AUTHOR]

This study aims to quantify meteorological–hydrological drought propagations and examine the potential impacts by climatic variability, LULC change (LULC), and human regulations. An integrated observation-modeling framework quantifies drought propagation intervals and assesses mechanisms influencing hydrological droughts. Meteorological droughts are characterized using the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts are assessed through the Standardized Streamflow Index (SSI) across diverse climatic zones. Cross-correlation analysis between SPEI and SSI time series identifies the lag time associated with the highest correlation as the drought propagation interval. Mechanisms are investigated via a coupled empirical-process modeling framework incorporating the Soil and Water Assessment Tool (SWAT). Discrepancies between simulated and observed SSI time series help quantify the extent of human regulation impacts on hydrological drought characteristics and propagation. The Yellow River Basin (YRB), divided into six subzones based on climate characteristics, is selected as the case study. Key findings include: (1) Meteorological droughts were extremely severe across most YRB during the 1990s, while the 2000s showed some mitigation primarily due to precipitation increases. (2) Hydrological droughts and propagation times from meteorology to hydrology demonstrated substantial spatiotemporal variability. In general, summer propagation times were shorter than other seasons. (3) Propagation times were shorter in arid regions with cropland or built-up land cover versus grassland and woodland, while the reverse held for humid regions. (4) Human regulations prolonged propagation times, likely due to reservoir regulations designed to overcome water deficits. While the YRB is the focus of this paper, the methodologies and findings are applicable to other regions worldwide to enhance drought forecasting and water resource management. In various hydrological and climatic contexts worldwide. [ABSTRACT FROM AUTHOR]

Simple Summary: This work aims to analyze flocks' management practices and sheep breeders' perceptions of the impact of climate change to enhance the resilience of the sheep production systems in the Tunisian semi-arid region. The results revealed three main sheep production systems: the agro-pastoral rain-fed system (AGPRF), the agro-pastoral irrigated system (AGPI), and the agro-sylvo-pastoral system (AGSP). Each production system is characterized by specific management and productive parameters that are used by farmers to build resilience actions. However, farmers' climate change perceptions are mostly the same across the three sheep production systems: a decrease in precipitation and an increase in temperatures and extreme events, which negatively influence feedstuff availability and costs. Global climate change inflicts unambiguous risks on agricultural systems and food security. Small ruminants are known for their ability to adapt to changing environmental conditions. This paper aims to characterize sheep production systems in a vulnerable agricultural zone and the breeders' perceptions of climate change to apprehend challenges that they are confronting, and formulate resilience actions. The data analysis is based on 94 semi-structured surveys of sheep farmers carried out in the Tunisian semi-arid region. The PCA analysis results revealed three main sheep production systems. The agro-pastoral rain-fed system (AGPRF) is dominant (55%), with large farms and common pastures integrating cereals and fodder. The agro-pastoral irrigated system (AGPI: 20%) is characterized by small-area and forage irrigation (1.8 ha) and a smaller number of ewes but a greater use of animal feed supplementation. The agro-sylvo-pastoral system (AGSP: 25%) is a system where grazing is based on common lands and using tree sub-products, while the agricultural area is exclusively used to cultivate cereal crops. Sheep breeders' climate perceptions are summarized as unpredictable climate events, a decrease in precipitation, and an increase in temperature. Resilience actions principally consist of reducing flocks' numbers, using alternative local feed, fodder, and water resources, and building more shelters and planting more trees in the grazing areas. Nevertheless, cost-effectiveness should be considered in such vulnerable zones to insure the sheep production systems' sustainability. [ABSTRACT FROM AUTHOR]

Floods destroy crop production; nevertheless, the extent of their impact on farmers' livelihoods in developing countries has been poorly investigated. This paper contributes to the growing evidence-based assessment of the impacts of shocks on communities. It assessed the post-disaster livelihood of farmers affected by the 2012 flooding in the semi-arid zone of Benin. To this end, a survey was conducted on 228 farmers in two municipalities of the flood-prone part of the semi-arid zone of Benin (Malanville, Karimama). Information on the well-being of households was collected using semi-structured interviews. Data were analyzed using income and consumption approaches focusing on poverty and on subjective assessment using happiness approach. Additionally, a probit model was used for a poverty assessment. The survey revealed that flooded farmers were amongst the poorest in the study system. Seven variables determined poverty in this study: household size, location, the percentage of the farm size that was flooded, fishing, the farmer's gender, farm size, and "holding a secondary activity". Regarding happiness, 99% of the flooded farmers were unhappier after the flood in 2012. The results clearly show that being subjected to floods increases the incidence of poverty. The capacity of flood risk management and governance should be strengthened in the study system. [ABSTRACT FROM AUTHOR]

Irrigation activities are important for sustaining food production and account for 70 % of total global water withdrawals. In addition, due to increased evapotranspiration (ET) and changes in the leaf area index (LAI), these activities have an impact on hydrology and climate. In this paper, we present a new irrigation scheme within the land surface model ORCHIDEE (ORganising Carbon and Hydrology in Dynamic EcosystEms)). It restrains actual irrigation according to available freshwater by including a simple environmental limit and using allocation rules that depend on local infrastructure. We perform a simple sensitivity analysis and parameter tuning to set the parameter values and match the observed irrigation amounts against reported values, assuming uniform parameter values over land. Our scheme matches irrigation withdrawals amounts at global scale, but we identify some areas in India, China, and the USA (some of the most intensively irrigated regions worldwide), where irrigation is underestimated. In all irrigated areas, the scheme reduces the negative bias of ET. It also exacerbates the positive bias of the leaf area index (LAI), except for the very intensively irrigated areas, where irrigation reduces a negative LAI bias. The increase in the ET decreases river discharge values, in some cases significantly, although this does not necessarily lead to a better representation of discharge dynamics. Irrigation, however, does not have a large impact on the simulated total water storage anomalies (TWSAs) and its trends. This may be partly explained by the absence of nonrenewable groundwater use, and its inclusion could increase irrigation estimates in arid and semiarid regions by increasing the supply. Correlation of irrigation biases with landscape descriptors suggests that the inclusion of irrigated rice and dam management could improve the irrigation estimates as well. Regardless of this complexity, our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, which is important to explore the joint evolution of climate, water resources, and irrigation activities. [ABSTRACT FROM AUTHOR]

The Ebinur Lake Basin is an ecologically sensitive area in an arid region. Investigating its land use and land cover (LULC) change and assessing and predicting its ecosystem service value (ESV) are of great importance for the stability of the basin's socioeconomic development and sustainable development of its ecological environment. Based on LULC data from 1990, 2000, 2010, and 2020, we assessed the ESV of the Ebinur Lake Basin and coupled the grey multi-objective optimization model with the patch generation land use simulation model to predict ESV changes in 2035 under four scenarios: business-as-usual (BAU) development, rapid economic development (RED), ecological protection (ELP), and ecological–economic balance (EEB). The results show that from 1990 to 2020, the basin was dominated by grassland (51.23%) and unused land (27.6%), with a continuous decrease in unused land and an increase in cultivated land. In thirty years, the total ESV of the study area increased from 18.62 billion to 67.28 billion yuan, with regulation and support services being the dominant functions. By 2035, cultivated land increased while unused land decreased in all four scenarios compared with that in 2020. The total ESV in 2035 under the BAU, RED, ELP, and EEB scenarios was 68.83 billion, 64.47 billion, 67.99 billion, and 66.79 billion yuan, respectively. In the RED and EEB scenarios, ESV decreased by 2.81 billion and 0.49 billion yuan, respectively. In the BAU scenario, provisioning and regulation services increased by 6.05% and 2.93%, respectively. The ELP scenario, focusing on ecological and environmental protection, saw an increase in ESV for all services. This paper can assist policymakers in optimizing land use allocation and provide scientific support for the formulation of land use strategies and sustainable ecological and environmental development in the inland river basins of arid regions. [ABSTRACT FROM AUTHOR]

Snowmelt floods are highly hazardous meteorological disasters that can potentially threaten human lives and property. Hence, snowmelt susceptibility mapping (SSM) plays an important role in flood prevention systems and aids emergency responders and flood risk managers. In this paper, a method of identifying snowmelt flood hazards is proposed, and a large‐scale snowmelt flood hazard zonation scheme based on historical recordings and multisource remote sensing data is established. To assess the quality of our approach, the proposed model was tested in the cold and arid region of Xinjiang, China. Overall, 140 historical snowmelt flood events and 27 explanatory factors were selected to construct a geospatial dataset for SSM of the contemporary period. GridSearchCV was used to comprehensively search the candidate parameters from the grid of given parameters obtained with the random forest (RF) algorithm. Then, the geospatial dataset was divided into two subsets: 70% for training and 30% for testing. Next, SSM results were obtained with the RF algorithm using optimized parameters. The results indicate that our optimized RF classifier performs well for the task of SSM, with a high AUC value (0.975) for the test dataset. The validation and analysis suggest that the proposed method can efficiently identify snowmelt flood hazards in undersampled arid areas at a regional scale. [ABSTRACT FROM AUTHOR]

Tecoma stans is a widely distributed tall ornamental shrub in the plains of Indian subcontinent and is considered an invasive species across Argentina, Australia, South Africa, Pacific Islands and tropical regions of Asia. Besides having an ornamental significance, T. stans has been extensively investigated for its pharmaceutical applications as a source of bioactive compounds. In addition, the shrub is cultivated commercially as a potted flowering plant. We believe that T. stans, being a hardy, invasive and aggressively growing species, holds a considerable potential and a promising solution for re-greening waste and degraded lands outside its invasive range, due to its wider adaptability and drought tolerant characteristics. The shrub is an excellent source of pollen and nectar, that attracts diverse insect-pollinators and several species of birds. The prudent plantation of this shrub has the potential to restore the ecology of barren landscapes, that can change its perspective of 'being invasive' to 'being ecologically healthy' across the tropical, semi-arid and subtropical regions worldwide. This paper reviews the current updates on ecology, life cycle including morphology, plant growth characteristics, flowering phenology, reproductive biology, breeding system and fruiting of T. stans. In addition, details on insect-pollinator diversity and natural regeneration potential have also been discussed, besides highlighting its therapeutic and landscape use. [ABSTRACT FROM AUTHOR]

In the process of agricultural development in arid and semi-arid areas, the carbon fixation capacity of vegetation can be affected to different degrees, but research on its driving factors is lacking. Consequently, this paper focuses on the Weiku Oasis in Xinjiang as its research area, in which the carbon fixation capacity of vegetation is estimated with the chemical equation of a photochemical reaction, using methods such as linear system models and Geodetector to analyze the relationship between cropland expansion characteristics and the carbon fixation capacity of vegetation from 1990 to 2020. The influence of land-use changes on the space differentiation of carbon fixation was elucidated through a time series relationship, and the synergistic effects of nine influencing factors on the carbon fixation capacity during the process of vegetation changes were discussed. The results were as follows: (1) In the process of agricultural development, the proportions of cultivated land area and spatial agglomeration had significant negative correlations with carbon sequestration, and the significance was rising, but the effect of cultivated land area proportion was more significant. (2) Through temporal sequential cooperativity analysis, when other land-use types were converted into cultivated land, the carbon fixation capacity of vegetation suddenly and significantly decreased in the initial year of the transformation, but the effect of cultivated land reclamation on the carbon fixation capacity of vegetation did not have a significant time lag. Moreover, after a certain period of time, cultivated land can gradually recover part of its lost carbon fixation capacity. (3) Among the nine driving factors, potential evapotranspiration is the most prominent in explaining the carbon fixation capacity of vegetation. This single-factor pairwise interaction presents the relationship between bivariate enhancement and nonlinear enhancement. When terrain factors interact with other factors, the enhancement effect of the influence on the carbon fixation capacity of vegetation has an obvious promotion effect. However, the change in the carbon fixation capacity of vegetation is more significantly influenced by potential evapotranspiration and the interaction between the normalized difference vegetation index (NDVI) and other factors. This research is helpful to understanding the basic theories related to the change in the carbon fixation capacity of vegetation during the process of agricultural development in arid and semi-arid areas, as well as providing theoretical reference for ecological environment construction and sustainable development. [ABSTRACT FROM AUTHOR]

Rehabilitation of post-mining sites in semi-arid/subtropical environments of eastern Australia have a general objective to establish specific types of native vegetation communities as defined in mine closure plans and in relation to the specific biotic and abiotic requirements of such communities. Critical for the success of rehabilitation is the availability of water and hence the climatic characteristic of this geographical region which is defined by a number of weather-bound factors (e.g. potentially erratic rainfall and periods of drought and flooding). However, specific estimates of climate suitability are seldom incorporated into current mined land rehabilitation design. To address this, our analysis combined various broad-scale climatic parameters (i.e. primarily relating to rainfall) to assess bioregional suitability-susceptibility within the context of plant early-establishment in the objective of informing rehabilitation schemes as to the inherent environmental challenges influencing both short- and long-term ecological development. Following our survey of available climate data, we derived site suitability-susceptibility indexes (that are otherwise currently not available within rehabilitation schemes) and compared the performance of 9 mine site locations in which our Centre has been engaged in environmental monitoring (Weipa, Mt. Isa, Ernest Henry, Eromanga, Kidston, Curragh, Tarong, North Stradbroke Island, and Newnes Plateau). More specifically, the sites were ranked from most-to-least suitable and compared with natural vegetation patterns (as estimated by the mean NDVI). Overall, it was determined that regular rainfall and relatively short periods of water-deficit are key characteristics of climate suitability (as found among the relatively more temperate coastal-hinterland sites), whereas high rainfall variability and (or) prolonged seasonal drought are primary characteristics of unsuitability (as found among the arid central-inland sites). Conceptual and practical considerations are provided which could inform rehabilitation schemes as to the inherent environmental challenges influencing both short- and long-term ecological development. [ABSTRACT FROM AUTHOR]

Changes in land use across the semiarid grasslands of Northern Mexico have driven a decline of plant cover and alteration of plant species composition. A number of different plant communities have resulted from these changes, however, their implications on the carbon cycle and regional carbon balance are still poorly understood. Here, we examined the effects of plant cover loss and changes in species composition on net ecosystem CO2 exchange (NEE) and their biotic and abiotic controls. Five typical plant community types were examined in the semiarid grassland by encasing the entire above-ground ecosystem using the geodesic dome method. Sites included an oat crop (crop), a moderately grazed grassland (moderate grazing), a 28 yr-old grazing exclosure (exclosure), an overgrazed site with low perennial grass cover (overgrazed), and an overgrazed site presenting shrub encroachment (shrub encroachment). For natural vegetation, rates of daytime NEE for sites with a high plant cover (exclosure and moderate grazing) were similar (P > 0.05) as compared to sites with low plant cover (overgrazed and shrub encroachment). However, night time NEE (carbon loss) was more than double (P < 0.05) for sites with high plant cover compared to sites with low cover, resulting into slight C sinks for the low plant cover sites and neutral or sources for the high plant cover sites on an annual basis. Differences in plant cover and its associated biomass defined the sensitivity to environmental controls. Thus, daytime NEE in low plant cover sites reached light compensation points at lower PPFD values than those from high plant cover sites. Differences in species composition did not influence NEE rates even though there were transient or permanent changes in C3 vs. C4 functional groups. [ABSTRACT FROM AUTHOR]

The article focuses on a study which compares satellite microwave backscattering (ASCAT) and visible/near-infrared reflectances (PARASOL) to estimate the aeolian aerodynamic roughness length in arid and semi-arid regions. It derives a global map of the aeolian aerodynamic roughness length at 6 kilometer resolution. It discusses the ASCAT scatterometer satellite measurements.

Numerical solution of the one‐dimensional Richards equation (RE) accurately partitions precipitation into infiltration and runoff in capillary dominated soils. However, its application sometimes requires significant computational effort and presents reliability challenges. The Green and Ampt (G&A) approach represents a conservative and efficient method to calculate one‐dimensional infiltration but is limited to deep, well drained, uniform, non‐layered soils for a single rainfall event. The original G&A model and subsequent advancements represent wetting fronts as discrete objects, rather than discretizing the model domain in space, yielding a computationally simpler model than the RE. This paper describes an extension of the G&A method into layered soils on a continuous basis that we call Layered Green and Ampt with Redistribution (LGAR). Assumptions employed in the derivation include: uniform soil hydraulic properties within layers, single‐valued capillary head at the interface between soil layers, and no influence of groundwater table on soil moisture. Wetting fronts advance due to the combined effects of gravity and wetting front capillary drive in a layered soil profile. Results of multi‐month continuous LGAR simulations of infiltration using forcing and soil hydraulic data from USDA SCAN sites are compared against infiltration calculated using the HYDRUS‐1D RE solver using standard metrics. The assumptions employed in deriving the LGAR method limit its application to situations where cumulative potential evapotranspiration is greater than cumulative precipitation, typical of arid or semi‐arid conditions. LGAR is a mass‐conservative, computationally efficient, reliable and reasonably accurate method for simulating infiltration over extended time periods compared to the numerical solution of the RE in layered soils in arid and semi‐arid regions. Plain Language Summary: In arid and semi‐arid regions the groundwater table is typically far below the land surface, and the process of infiltration divides rainfall into soil moisture and surface runoff. Previous extensions of the Green and Ampt (1911, https://doi.org/10.1017/s0021859600001441) infiltration method allow accurate calculation of infiltration into a layered soil for short time periods. This paper shows a novel extension that calculates infiltration in layered soils on a continuous basis using a Green and Ampt like method. This development represents an advance because it provides an accurate, mass‐conserving, computationally efficient and reliable method to calculate infiltration in arid and semi‐arid landscapes where stormflow generation is often dominated by layered soil properties. Key Points: The Richards equation (RE) is widely used to simulate infiltration but often presents computational challengesWe developed a Layered Green and Ampt with Redistribution (LGAR) approach that compares well against RE infiltration predictionsThe LGAR method is unconditionally stable with guaranteed mass conservation and is designed for semi‐arid and arid areas [ABSTRACT FROM AUTHOR]

The net primary productivity (NPP) of vegetation is an important indicator reflecting the vegetation dynamics and carbon sequestration capacity in a region. In recent years, China has implemented policies to carry out ecological protection. To understand the changes in the distribution of vegetation NPP in China and the influence of climate factors, the Carnegie–Ames–Stanford approach (CASA) model was used to estimate the NPP from 2001 to 2020. In this paper, several sets of measurement datasets and products were collected to evaluate the effectiveness of the model and suggestions were provided for the modification of the CASA model based on the evaluation results. In addition to the correlation analysis, this paper presents a statistical method for analyzing the quantitative effects in individual climatic factors on NPP changes in large regions. The comparison found that the model has a better estimation effect on grassland and needleleaf forest. The estimation error for the evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF) decreases with the warming of the climatic zone, while the evergreen broadleaf forest (EBF) and deciduous needleleaf forest (DNF) do the opposite. The changes in total CASA NPP were consistent with the trends of other products, showing a dynamic increasing trend. In terms of the degree of correlation between the NPP changes and climatic factors, the NPP changes were significantly correlated with temperature in about 10.39% of the vegetation cover area and with precipitation in about 26.92% of the vegetation cover area. It was found that the NPP variation had a negative response to the temperature variation in Inner Mongolia grasslands, while it had a positive but small effect (±10 g C) in the Qinghai–Tibet Plateau grasslands. Precipitation had a facilitative effect on the grassland NPP variation, while an increase in the annual precipitation of more than 200 mm had an inhibitory effect in arid and semi-arid regions. This study can provide data and methodological reference for the ecological assessment of large-scale regional and climate anomalous environments. [ABSTRACT FROM AUTHOR]

With the warming and humidification process in the Northwest Arid Zone over the past 30 years, the runoff of a vast majority of rivers has been affected to different degrees. In this paper, the runoff from the Weigan River, a typical inland river in the arid zone of Northwest China, is taken as an example, and seven types of CMIP6 data are selected with the help of a SWAT model to predict the runoff volume of the Weigan River in the next 30 years under climate change. The results show that (1) the SWAT model can simulate the runoff from the Weigan River well and has good applicability in this study area. (2) With an increase in radiative forcing, the temperature, precipitation and runoff in the study area show an increasing trend. (3) Under the four radiative forcing scenarios in 2030 and 2050, the runoff from the Weigan River out of the mountain is predicted to be maintained at 25.68 to 30.89 × 108 m3, which is an increase of 1.35% to 21.91% compared with the current runoff, of which the contribution to the increase in future runoff caused by the changes in temperature and precipitation is 68.71% and 27.24%, respectively. It is important to explore the impact of climate change on the runoff from the Weigan River to understand the impact of climate change on the Northwest Arid Region scientifically and rationally, and to provide a scientific basis for evaluating the risk of climate change and formulating policies to deal with it. [ABSTRACT FROM AUTHOR]

The global climate has undergone great changes in recent decades, which has a significant impact on the vegetation system, especially in arid and semi-arid areas. Based on a dynamic model, this paper studied the response of vegetation pattern to climate change in Qinghai Lake, a typical semiarid region. The conditions for Turing instability of the equilibrium were obtained by mathematical analysis. The numerical experiments showed the influence of different climitic factors (carbon dioxide concentrations [CO2], temperature and precipitation) on vegetation pattern. The results showed that the robustness of the vegetation system was enhanced as precipitation or [CO2] increased. Furthermore, we presented evolution of vegetation system under different climate scenarios to forecast the future growth of vegetation. We compared the various climate scenarios with representative concentration pathways (RCP2.6, RCP4.5, RCP8.5). The results revealed that RCP2.6 scenario was a desired climate scenario for Qinghai Lake. Our study also highlighted the measures to avoid desertification by the method of optimal control. We expect that this study will provide theoretical basis for vegetation protection. [ABSTRACT FROM AUTHOR]