Taklimakan Research Articles

Moisture sources for the unprecedented precipitation event in the heart of Taklimakan desert

Moisture sources for the unprecedented precipitation event in the heart of Taklimakan desert

Synergistic windbreak efficiency of desert vegetation and oasis shelter forests.

This study investigates the novel approach of synergizing desert vegetation with shelter forests to enhance windbreak efficiency in a transitional zone between the Korla oasis and the Taklimakan Desert, northwest China. Through an extensive field survey and experimental setup, we evaluated the impact of different shelterbelt configurations on wind speed reduction. Three types of shelter forests were examined: multi-row Poplar (Populus alba), single-row Jujube (Ziziphus jujube), and a mixed-species layout combining one row of Jujube and two rows of Poplar trees. Wind speed measurements were recorded at multiple heights across three zones-open field, between desert vegetation and shelterbelt, and leeward of the shelterbelt-over a three-month period (April to June, 2023). The findings reveal a significant reduction in wind speed, particularly on the leeward side, with multi-row and mixed-species configurations proving the most effective. The highest synergistic efficiency, observed in the mixed-species shelter forest, showed a windbreak efficiency improvement of over 20% compared to desert vegetation alone. This study provides new insights into the combined effectiveness of desert vegetation and shelter forests, offering a strategic framework for designing shelterbelts in arid environments. These results underscore the critical role of diverse, structured vegetation arrangements in combating wind erosion and contribute to the development of sustainable ecological management practices for desert regions worldwide.

Precipitation Controls on Carbon Sinks in an Artificial Green Space in the Taklimakan Desert

Precipitation Controls on Carbon Sinks in an Artificial Green Space in the Taklimakan Desert

Effects of different surface water flow frequencies on water use characteristics of Tamarix ramosissima in the hinterland of the Taklamakan Desert

Tamarix ramosissima is a dominant species in desert ecosystems and an ecological barrier species in arid areas, playing a crucial role in stabilizing dunes and preventing desertification. In this study, river water, groundwater, soil water, and T. ramosissima individual samples were collected from three sites in July and October 2023 at the Daliyaboyi Oasis located at the tail of the Kriya River in the hinterland of the Taklamakan Desert. The three sites are referred to as the center (SE), west (SW), and north (SN) sites within the Daliyaboyi Oasis, and each experienced different flood frequencies. The SE site experienced flooding in July and October, the SW site experienced flooding only in July, and the SN site experienced no flooding in July or October. The spatial and temporal variation in hydrogen and oxygen stable isotopes and line-conditional excess (lc-excess) in water and plant samples were analyzed, and the potential changes in water use of T. ramosissima were analyzed by the hydrogen and oxygen stable isotope and MixSIAR model. The findings indicated that the slope of SWL at the SE, SW, and SN sites was higher in July (6.77, 6.42, and 3.05, respectively) than in October (7.37, 3.30, and 2.14, respectively). The lc-excess value of the SE site did not exhibit seasonal changes; only the lc-excess values of soil water in SW and SN sites showed seasonal changes. MixSIAR results indicated frequent flood events at the SE site, with relatively constant proportions of water source utilization by T. ramosissima in July and October. In addition, shallow soil water (0–60 cm) and deeper soil water (60–80 cm) were the main water sources of T. ramosissima at SE. The SN site was slightly influenced by surface water, resulting in statistically non-significant changes in the water source utilization by T. ramosissima. Indeed, deep soil water (60–200 cm) and groundwater were the sources of water for T. ramosissima at this site. In contrast with October, the SW site experienced flood events in July, resulting in the utilization of water by T. ramosissima from the shallow soil (0–60 cm) and deep soil (60–280 cm) in July and October, respectively. Different surface water flow patterns led to different water use characteristics of T. ramosissima, which further demonstrated that T. ramosissima has high resilience and ecological plasticity. This work provides a useful reference for the implementation of effective ecological water transport measures in the Daliyaboyi Oasis and similar arid habitats.

A chromosome-level genome assembly for the desert scorpion Mesobuthus przewalskii from Asian drylands.

Scorpions are an ancient and charismatic group of arthropods with medical importance, but a high-quality reference genome for this group is still lacking. Here we perform whole-genome sequencing of Mesobuthus przewalskii, a desert scorpion endemic to the Taklimakan Desert. We combine PacBio HiFi sequencing and Hi-C chromosome conformation capturing to generate chromosomal-level, haplotype-resolved, and fully annotated genome assembly for this medically important scorpion. The assembly consists of two haplotypes (1052.01 Mbp and 1055.19 Mbp, respectively) reaching chromosome-level contiguity and >98% BUSCO completeness. Sequences were anchored in 13 chromosomes with a contig N50 of 34.44 Mbp and scaffold N50 of 81.43 Mbp. Several key genome features and the mitochondrial genome assembly were also provided. This genome represents the fifth but the most complete assembly for the order Scorpiones.

Evaluating the Prediction Performance of the WRF-CUACE Model in Xinjiang, China

Dust and air pollution events are increasingly occurring around the Taklimakan Desert in southern Xinjiang and in the urban areas of northern Xinjiang. Predicting such events is crucial for the advancement, growth, and prosperity of communities. This study evaluated a dust and air pollution forecasting system based on the Weather Research and Forecasting model coupled with the China Meteorological Administration Chemistry Environment (WRF-CUACE) model using ground and satellite observations. The results showed that the forecasting system accurately predicted the formation, development, and termination of dust events. It demonstrated good capability for predicting the evolution and spatial distribution of dust storms, although it overestimated dust intensity. Specifically, the correlation coefficient (R) between simulated and observed PM10 was up to 0.85 with a mean absolute error (MAE) of 721.36 µg·m−3 during dust storm periods. During air pollution events, the forecasting system displayed notable variations in predictive accuracy across various urban areas. The simulated trends of PM2.5 and the Air Quality Index (AQI) closely aligned with the actual observations in Ürümqi. The R for simulated and observed PM2.5 concentrations at 24 and 48 h intervals were 0.60 and 0.54, respectively, with MAEs of 28.92 µg·m−3 and 29.10 µg·m−3, respectively. The correlation coefficients for simulated and observed AQIs at 24 and 48 h intervals were 0.79 and 0.70, respectively, with MAEs of 24.21 and 27.56, respectively. The evolution of the simulated PM10 was consistent with observations despite relatively high concentrations. The simulated PM2.5 concentrations in Changji and Shihezi were notably lower than those observed, resulting in a lower AQI. For PM10, the simulation–observation error was relatively small; however, the trends were inconsistent. Future research should focus on optimizing model parameterization schemes and emission source data.

Microbial Community Structure in the Taklimakan Desert: The Importance of Nutrient Levels in Medium and Culture Methods.

Although the Taklimakan Desert lacks the necessary nutrients and conditions to support an extensive ecosystem, it is a treasure trove of extremophile resources with special structures and functions. We analyzed the bacterial communities using oligotrophic medium and velvet cloth replicate combined with an extended culture duration. We isolated numerous uncultured microorganisms and rare microorganisms belonging to genera not often isolated or recently described, such as Aliihoeflea, Halodurantibacterium, and Indioceanicola. A total of 669 strains were isolated from the soil of the Taklimakan Desert, which were classified into 5 phyla, 7 classes, 25 orders, 42 families, 83 genera, and 379 species. Among them, 148 strains were potential new species. Our data show that even when working with samples from extreme environments, simple approaches are still useful for cultivating stubborn microbes. Through comparing the isolation effects of different nutrient levels on microbial diversity and abundance, the results show that reducing the nutrient level of the medium was more conducive to improving the culturability of microorganisms in low-nutrient environments, while the high-nutrient medium was more suitable for the isolation of dominant fast-growing strains. This study helps to better reflect the diversity of microbial resources and lays a foundation for the further research and utilization of soil microbial resources in the Taklimakan Desert.

The First Validation of Aerosol Optical Parameters Retrieved from the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS) and Its Application

In August 2022, China successfully launched the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS). The primary payload of this satellite is an onboard multi-beam lidar system, which is capable of observing aerosol optical parameters on a global scale. This pioneering study used the Fernald forward integration method to retrieve aerosol optical parameters based on the Level 2 data of the TECIS, including the aerosol depolarization ratio, aerosol backscatter coefficient, aerosol extinction coefficient, and aerosol optical depth (AOD). The validation of the TECIS-retrieved aerosol optical parameters was conducted using CALIPSO Level 1 and Level 2 data, with relative errors within 30%. A comparison of the AOD retrieved from the TECIS with the AERONET and MODIS AOD products yielded correlation coefficients greater than 0.7 and 0.6, respectively. The relative error of aerosol optical parameter profiles compared with ground-based measurements for CALIPSO was within 40%. Additionally, the correlation coefficients R2 with MODIS and AERONET AOD were approximately between 0.5 and 0.7, indicating the high accuracy of TECIS retrievals. Utilizing the TECIS retrieval results, combined with ground air quality monitoring data and HYSPLIT outcomes, a typical dust transport event was analyzed from 2 to 7 April 2023. The results indicate that dust was transported from the Taklamakan Desert in Xinjiang, China, to Henan and Anhui provinces, with a gradual decrease in the aerosol depolarization ratio and backscatter coefficient during the transport process, causing varying degrees of pollution in the downstream regions. This research verifies the accuracy of the retrieval algorithm through multi-source data comparison and demonstrates the potential application of the TECIS in the field of aerosol science for the first time. It enables the fine-scale regional monitoring of atmospheric aerosols and provides reliable data support for the three-dimensional distribution of global aerosols and related scientific applications.

Aerosol Components Derived from Global AERONET Measurements by GRASP: A New Value-Added Aerosol Component Global Dataset and Its Application

Abstract Aerosols affect Earth’s climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, southern Africa, sub-Sahel, Gobi Desert, Middle East, Sahara Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60–0.85 for BC; R = 0.75–0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing.

The source, transport, deposition and direct radiative effect of mineral dust over western China: A modeling study of July 2022 with focus on the Tibetan Plateau

A Regional Air Quality Model System (RAQMS) driven by WRF was applied to explore the emission, transport, deposition, and direct radiative effect of mineral dust over western China in July 2022, with focus on the Tibetan Plateau (TP). Model validation against ground and satellite observations demonstrated the model reproduced meteorological variables, PM10 concentration, aerosol optical depth (AOD), and extinction coefficients in the vertical reasonably well. There was a dust event during 3–7 July 2022, which was originated from the Taklimakan Desert (TKD) and affected eastern and central TP under anticyclonic flows, resulting in the maximum hourly PM10 concentration exceeding 50 μg m−3 in Lhasa. Shortwave radiation was reduced considerably by dust aerosols over eastern TP, with the maximum decrease in daytime mean shortwave radiation reaching 30 W m−2 around Nyingchi on 5 July. Anthropogenic aerosols dominated PM10 mass in the capital cities of western China (54–67 %), while dust aerosols were dominant in the cities near the deserts. During this dust event, dust aerosols from TKD and Qaidam Desert (QDD) significantly influenced eastern TP, with dust contributions to PM10 mass concentration of 52 %, 76 % and 69 %, respectively, in Chamdo, Lhasa and Nyingzhi, respectively. The total dust emission in western China was about 10.6 Tg in July 2022, with the largest contribution from TKD (63.5 %), followed by Gobi Desert (GB) (26 %). The total deposition of dust was estimated to be 6.2 Tg, in which TKD and GB contributed 66 % and 22 %, respectively. During the study period, about 418 Gg dust aerosols were deposited on TP, 49 % of which was from TKD and 25 % from QDD. Foreign dust sources contributed approximately 7 % and 9 % to dust concentration and total deposition over TP, respectively. Over southern TP, the source contribution to dust deposition was estimated to be 42 %, 24 % and 21 % from TKD, foreign sources and QDD, respectively, suggesting potentially important impact of long-range transboundary dust transport on deposition, surface albedo and climate over TP.

Population structure and selective signature of Kirghiz sheep by Illumina Ovine SNP50 BeadChip.

By assessing the genetic diversity and associated selective traits of Kirghiz sheep (KIR), we aim to uncover the mechanisms that contribute to sheep's adaptability to the Pamir Plateau environment. This study utilized Illumina Ovine SNP50 BeadChip data from KIR residing in the Pamir Plateau, Qira Black sheep (QBS) inhabiting the Taklamakan Desert, and commonly introduced breeds including Dorper sheep (DOR), Suffolk sheep (SUF), and Hu sheep (HU). The data was analyzed using principal component analysis, phylogenetic analysis, population admixture analysis, kinship matrix analysis, linkage disequilibrium analysis, and selective signature analysis. We employed four methods for selective signature analysis: fixation index (Fst), cross-population extended homozygosity (XP-EHH), integrated haplotype score (iHS), and nucleotide diversity (Pi). These methods aim to uncover the genetic mechanisms underlying the germplasm resources of Kirghiz sheep, enhance their production traits, and explore their adaptation to challenging environmental conditions. The test results unveiled potential selective signals associated with adaptive traits and growth characteristics in sheep under harsh environmental conditions, and annotated the corresponding genes accordingly. These genes encompass various functionalities such as adaptations associated with plateau, cold, and arid environment (ETAA1, UBE3D, TLE4, NXPH1, MAT2B, PPARGC1A, VEGFA, TBX15 and PLXNA4), wool traits (LMO3, TRPS1, EPHA5), body size traits (PLXNA2, EFNA5), reproductive traits (PPP3CA, PDHA2, NTRK2), and immunity (GATA3). Our study identified candidate genes associated with the production traits and adaptation to the harsh environment of the Pamir Plateau in Kirghiz sheep. These findings provide valuable resources for local sheep breeding programs. The objective of this study is to offer valuable insights for the sustainable development of the Kirghiz sheep industry.

Impact of anthropogenic and natural constituents on particulate matter in oasis cities on the southern margin of the Taklimakan Desert based on MERRA-2 and multi-site ground observation

Dust storms are associated with large amounts of particulate matter (PM) that can have adverse effects on health and the environment. The contribution of natural dust to atmospheric PM levels represents a scientific challenge, especially in areas with close proximity to dust sources. To improve our knowledge in this area, we collected 300 PM filter-samples across five oasis cities on the southern edge of the Taklimakan Desert in 2016, and applied the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) data to quantify the contribution of natural dust to PM on sand dust and non-sand dust days. Research has shown that the particle size distribution of mineral dust in Taklimakan dust aerosols was relatively uniform. On sand dust days, CaSO4 and Na2SO4 were directly emitted from the surface, leading to higher sulfate concentrations in PM. While the increase in the proportions of organic carbon - OC1 and OC2 was attributed to the mixed anthropogenic emissions. On non-sand dust days, SO42− concentration was significantly affected by emissions from anthropogenic sources. The automotive composite emissions and coal combustion were the main sources of elemental carbon - EC1. Based on the results of MERRA-2 reanalysis data, natural dust constituted 53 % and 70 % of the total PM2.5 and PM10, respectively. In this study, we have quantified the contribution of natural dust under different weather conditions and identifying potential sources of PM in oasis cities. This study provides support for the assessment of natural dust and PM prevention in oasis cities.

Trends analysis of Evapotranspiration and responses to soil moisture and wind speed over the Taklimakan Desert, China

The Tarim Basin is a typical hyper-arid area, 57% of which is occupied by the Taklimakan desert. Because evapotranspiration (ET) is a key factor in determining water demand, accurate estimation of ET is critical for efficient water management in arid regions. In this study, the spatiotemporal dynamics of ET across the Tarim Basin from 2001 to 2020 were simulated based on a revised Surface Energy Balance System (SEBS) algorithm, and the impacts of driving factors on ET trends in the Taklimakan desert were quantified. The findings indicated that the mean annual ET in the entire basin was slightly greater than that in the desert (302 mm vs. 295 mm), although the decreasing rate of annual ET across the entire basin was slower than that in the desert (−0.27 mm/year vs. −0.50 mm/year). Strong increasing trends were found in croplands, whereas decreasing trends, which accounted for 56.5% of the basin, were primarily concentrated in the central and southern parts of the desert. Correlation analysis revealed that wind speed (WS) and soil moisture (SM) were the dominant factors, with a negative contribution of more than 35% and a positive contribution of more than 45%, respectively, to ET trends. Compared with the ERA5-Land and complementary relationship ET using the extended triple collocation method, SEBS ET provided detailed information and a lower random error standard deviation. Our findings contribute to the understanding of how dominant factors impact ET in hyper-arid regions and provide a reference for water management.

Desert oasis vegetation information extraction by PLANET and unmanned aerial vehicle image fusion

Sparse vegetation is a key factor in maintaining the health and sustainability of oasis ecosystems under extreme drought conditions. Combining the advantages of both satellites and drones, using image processing and machine learning technology, it can efficiently and accurately extract information on the vegetation of desert oases, providing a scientific basis for ecological monitoring and management. Therefore, in this study, the Dariyabui natural oasis in the hinterland of the Taklamakan Desert, China, was used as the study area to fuse PLANET and UAV images to screen 19 feature factors from different data sources. The machine learning binary classification model was evaluated based on the overall accuracy (OA, %), kappa, balanced accuracy (BA, %), F1_score (F1, %), and Area Under Curve (AUC) values. The results were validated using aerial imaging data from different months. The results show that (1) the primary feature factors for extracting sparse ground vegetation information in a desert oasis include the soil-adjusted vegetation index (SAVI); modified soil-adjusted vegetation index (MSAVI); optimized soil-adjusted vegetation index (OSAVI); and the mean, entropy, contrast, homogeneity, and digital surface models (DSM). (2) The evaluation indices of the fused images in the vegetation information extraction were better than those of the original satellite images; the difference in the extraction effect with the original UAV images was not significant. (3) The random forest (RF) algorithm achieved the best classification accuracy in extracting sparse vegetation information (Kappa = 0.87, OA = 94.12 %, BA = 93.53 %, F1 = 92.13 %, and AUC = 0.967).

Where Dust Comes From: Global Assessment of Dust Source Attributions With AeroCom Models

AbstractThe source of dust in the global atmosphere is an important factor to better understand the role of dust aerosols in the climate system. However, it is a difficult task to attribute the airborne dust over the remote land and ocean regions to their origins since dust from various sources are mixed during long‐range transport. Recently, a multi‐model experiment, namely the AeroCom‐III Dust Source Attribution (DUSA), has been conducted to estimate the relative contribution of dust in various locations from different sources with tagged simulations from seven participating global models. The BASE run and a series of runs with nine tagged regions were made to estimate the contribution of dust emitted in East‐ and West‐Africa, Middle East, Central‐ and East‐Asia, North America, the Southern Hemisphere, and the prominent dust hot spots of the Bodélé and Taklimakan Deserts. The models generally agree in large scale mean dust distributions, however models show large diversity in dust source attribution. The inter‐model differences are significant with the global model dust diversity in 30%–50%, but the differences in regional and seasonal scales are even larger. The multi‐model analysis estimates that North Africa contributes 60% of global atmospheric dust loading, followed by Middle East and Central Asia sources (24%). Southern hemispheric sources account for 10% of global dust loading, however it contributes more than 70% of dust over the Southern Hemisphere. The study provides quantitative estimates of the impact of dust emitted from different source regions on the globe and various receptor regions including remote land, ocean, and the polar regions synthesized from the seven models.

Study on Daytime Atmospheric Mixing Layer Height Based on 2-Year Coherent Doppler Wind Lidar Observations at the Southern Edge of the Taklimakan Desert

Study on Daytime Atmospheric Mixing Layer Height Based on 2-Year Coherent Doppler Wind Lidar Observations at the Southern Edge of the Taklimakan Desert

Temporal and spatial distribution of PM2.5 in the Xinjiang region based on AOD fusion data and the GTWR model

ABSTRACT By integrating MODIS aerosol optical depth data and combining it with ground-based PM2.5 measurements and meteorological data, a geographically and temporally weighted regression (GTWR) model was used to estimate the spatiotemporal distribution of PM2.5 in Xinjiang in 2022. Findings include the following: (1) The GTWR model effectively represents PM2.5 distributions, with a correlation coefficient of 0.92, surpassing the geographically weighted regression model by 5.7% and the land use regression model by 9.5%. (2) Monthly PM2.5 levels in Xinjiang exhibit a pattern of initial decline followed by an increase. Elevated coal-fired heating in February and high air humidity in July contribute to higher atmospheric particulate concentrations. The peak monthly average concentration reaches 79.05 µg m−3 in February, and the lowest concentration drops to 33.86 µg m−3 in July. (3) Influenced by dust-prone conditions and atmospheric diffusion in the Taklimakan Desert region, PM2.5 levels in Xinjiang show a notable southwest-to-northeast gradient.

Long-range transport impact of a severe dust storm over the Yangtze River Basin region and its modeling sensitivity to dust emission scheme

Dust storms frequently occur in the spring over East Asia, affecting southern Mongolia and northeast China. An exceptionally powerful dust storm occurred in East Asia from March 14th to March 18th, 2021. To investigate the ability of climate models to simulate severe dust storms, we employed the Weather Research Forecast model coupled with chemistry (WRF-Chem) with Goddard Chemistry Aerosol Radiation and Transport (GOCART), SHAO and KOK dust emission schemes to simulate the evolution of this event and to characterize dust aerosols long-range transport. Results showed that this storm was caused by a Mongolian cyclone depicted at 850 hPa with a cold front, which swept dust aerosols southeastward across southern Mongolia to northeast China. Model evaluation with satellite-retrieved Aerosol Optical Depth (AOD) and observational PM10 concentrations revealed that the SHAO dust emission scheme performed better in simulating spatial and temporal distribution of AOD over the Gobi Desert (GD) but overestimated them over Taklimakan Desert (TD). In contrast, the GOCART dust emission scheme underestimated AOD over most areas except the Taklimakan Desert; the KOK dust emission scheme overestimated them over both TD and GD. Overall, the SHAO dust emission scheme had good performance in simulating the surface PM10 concentrations over the Yangtze River Basin (YRB) and depicted an increase in PM10 concentrations, which denoted the transport of dust aerosols over YRB. As a better description of the physical process of dust emission flux over the eastern region of the Gobi Desert, the SHAO dust emission scheme depicted well the spatial and temporal evolution of dust plume episodes, especially over northeast China and YRB. The significant differences in dust emission fluxes between the three dust emission schemes were attributed to the sensitivity of threshold friction velocity and erodibility factor. Thereunto, the SHAO dust emission scheme incorporated well soil particle size distribution and threshold velocity to produce the dust emission flux, which allowed higher dust emission flux over the eastern GD and under strong southwesterly transported dust aerosols to East Central China's region of North China Plain (NCP) and YRB. This study will help further the simulation of extreme dust events more accurately and the exploration of climate change's effect on dust events over East Asia.

Depth-dependent responses of soil bacterial communities to salinity in an arid region

Soil salinization adversely affects soil fertility and plant growth in arid region worldwide. However, as the drivers of nutrient cycling, the response of microbial communities to soil salinization is poorly understood. This study characterized bacterial communities in different soil layers along a natural salinity gradient in the Karayulgun River Basin, located northwest of the Taklimakan desert in China, using the 16S rRNA Miseq-sequencing technique. The results revealed a significant filtering effect of salinity on the bacterial community in the topsoil. Only the α-diversity (Shannon index) in the topsoil (0–10 cm) significantly decreased with increasing salinity levels, and community dissimilarity in the topsoil was enhanced with increasing salinity, while there was no significant relationship in the subsoil. BugBase predictions revealed that aerobic, facultatively anaerobic, gram-positive, and stress-tolerant bacterial phenotypes in the topsoil was negatively related to salinity. The average degree and number of modules of the bacterial co-occurrence network in the topsoil were lower under higher salinity levels, which contrasted with the trends in the subsoil, suggesting an unstable bacterial network in the topsoil caused by higher salinity. The average path length among bacterial species increased in both soil layers under high salinity conditions. Plant diversity and available nitrogen were the main drivers affecting community composition in the topsoil, while available potassium largely shaped community composition in the subsoil. This study provides solid evidence that bacterial communities adapt to salinity through the adjustment of microbial composition based on soil depth. This information will contribute to the sustainable management of drylands and improved predictions and responses to changes in ecosystems caused by climate change.

Regional differences in the grain size characteristics of surface sediments from typical barchan dunes in arid zones

The grain size characteristics of aeolian sediments are the combined result of sand sources, regional airflow regimes, dune morphology, etc., and are essential for understanding the formation and evolution of barchan dunes. Based on field investigations and laboratory experimental data, in this paper, we explored differences in the grain size characteristics of the surface sediments of barchan dunes at the southeastern edge of the Taklimakan Desert (TKLM-SE), the western (QB-W) and southern parts of the Qaidam Basin Desert (QB-S), the sand belt connecting the Badain Jaran Desert and the Tengger Desert (BT-B), and their responses to sand sources, dune morphology, and wind regimes. The main results were as follows: (i) The mean grian size distribution patterns of the windward slope toe to the leeward slope toe through the dune crest/ridge varied with different transects of the barchan dunes and different deserts, showing four types including gradually fining (GF), gradually coarsening (GC), coarsening followed by fining (CF), and fining followed by coarsening (FC). The patterns were GF and CF in the TKLM-SE; GF, GC, and FC in the BT-B; GF, GC, and CF in the QB-W; and GF in the QB-S. (ii) The interdune sediments provided the source material for the formation and development of barchan dunes and their grain size varied in different deserts. The interdune sediments were composed of gravel and very fine sand in the TKLM-SE, while they were composed of medium and fine sand in the QB-W, QB-S, and BT-B. (iii) The windward side of the barchans varied with different wind directions, and dune height affected dune surface airflow velocity and direction, changing the pattern of grain size distribution on the dune surface. The wind regime over a ten-day or half-month scale could explain the variance in the grain size distribution patterns better than that on an annual scale. (iv) Grain size characteristics of dune surface sands changed with dune shape due to changes in the surface airflow velocity and direction and the sediment-carrying capacity of the airflow. With an increasing ratio of dune height to dune width, the grain size of the dune crest sands became coarser. These results help advance our understanding of the grain size characteristics of barchan dunes and regional variabilities in their patterns.