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In the context of global warming, the strength and frequency of drought events are projected to grow in the future, and the onset of drought can have dramatic effects on vegetation growth in terrestrial ecosystems. Central Asia is the largest non-territorial drought area in the world, and the response of vegetation to drought events is extremely sensitive in the area. However, few studies have quantified and compared the vegetation gross primary productivity (GPP) response to the lagged and cumulative effects of drought. In this research, the solar-induced chlorophyll fluorescence GPP and Standardized Precipitation Evaporation Index (SPEI) were used to analyze the time and space patterns of vegetation GPP and the SPEI in Central Asia and to quantify and compare the lagged and cumulative effects of drought on the GPP of various vegetation types. During the period from 2000 to 2018, the general trends of vegetation GPP showed a slight increase in Central Asia, with the ratio of variation being 1.35 g C m−2 y−1 and a spatially decreasing distribution from north to south. SPEI showed a trend of decreasing and then increasing over a period of 19 years, with a slight decreasing (drying) trend and a rate of change of −0.02 y−1, and the overall spatial pattern was drying out from north to south. In 13 months, 72.44% of regional droughts had lagged impacts on vegetation. The maximum correlation coefficients of vegetation and the lagged effectiveness of drought were concentrated in the range of 0.15–0.35, and the high correlation was distributed in southern and northwestern Kazakhstan, which are prairie regions. Of the regions in Central Asia, 75.86% showed cumulative drought effects concentrated at 9–12 months. The maximum correlation coefficients were concentrated in the range of 0.20–0.50, and the high correlation regions were primarily situated in south Kazakhstan and east Uzbekistan. Comparing the correlation coefficients of the lagged effect of vegetation GPP and SPEI with the cumulative effect shows that the cumulative rather than lagged impacts of drought on vegetation cover were found in 86.75% of the regions in Central Asia. This research enhances our comprehension of the influence of drought events on ecosystems in arid regions and has a certain reference value for helping arid region ecosystems to cope with global climate change. [ABSTRACT FROM AUTHOR]

The accurate inversion of actual evapotranspiration (ETa) at a regional scale is crucial for understanding water circulation, climate change, and drought monitoring. In this study, we produced a 1 km monthly ETa dataset for Turpan and Hami, two typical arid cities in northwest China, using multi-source remote sensing data, reanalysis information, and the ETMonitor model from 1980 to 2021. We analyzed the spatiotemporal variation of ETa using various statistical approaches and discussed the impact of climate and land use and cover changes (LUCC) on ETa. The results show the following: (1) the estimation results correlate well with ETa products on monthly scales (coefficient of determination (R2) > 0.85, root mean square error (RMSE) < 15 mm/month) with high reliability. (2) The ETa values were spatially distributed similarly to precipitation and LUCC, with the multi-year (1980–2021) average of 66.31 mm and a slightly fluctuating downward trend (−0.19 mm/a). (3) During the 42-year period, 63.16% of the study area exhibited an insignificant decrease in ETa, while 86.85% experienced pronounced fluctuations (coefficient of variation (CV) > 0.20), and 78.83% will show an upward trend in the future. (4) ETa was significantly positively correlated with precipitation (94.17%) and insignificantly positively correlated with temperature (55.81%). The impact of human activities showed an insignificant decreasing trend (85.41%). Additionally, the intensity of ETa varied considerably among land types, with the largest for cropland (424.12 mm/a). The results of the study have implications for promoting the rational allocation of regional water resources and improving water use efficiency in arid zones. [ABSTRACT FROM AUTHOR]

Various climatic factors and their interactions affect China's snow depth alterations. However, a measure of the relative importance of climatic factors regarding the variance in snow depth is lacking. Here, we use a heretofore largest dataset, quality‐controlled daily observations from 1,665 meteorological stations, and statistical analyses to identify proxy drivers and their contributions regarding regional variability and trends in China's snow depth and snow depth‐climate relationships from 1951 to 2019. Results show that seasonal snow depth alterations are substantial in China and caused by various climatic drivers. In winter, observed positive trends in the northwest and northeast of China mainly respond to augmentation in solid precipitation and snow accumulation in fall. For the Tibetan Plateau, the negative snow depth anomaly seems to respond to the rising air temperature below the freezing point along with some secular changes in solid precipitation and shallower fall snowpacks. All these trends in winter snow depth over the northwest, northeast, and Tibetan Plateau of China account approximately for 30% of the total interannual variance in spring snow depth in these regions. In the milder central north and south of China, snow accumulation is not evident. Besides solid precipitation and rising air temperature below the freezing point, atmospheric humidity is also notable for its effect on the interannual variance in winter snow depth in these regions. In spring and fall, however, the negative effect of warming climate on snow depth becomes remarkably more important. It seems that about 13–33% (12–50%) of the total interannual variance in the widespread decrease (insignificant perturbation), except for some weak increases in the northeast region (decreases in the Tibetan Plateau), of China's spring (fall) snow depth are caused by the rising air temperature below the freezing point. [ABSTRACT FROM AUTHOR]

Achieving land degradation neutrality (LDN) is considered critical to achieving sustainable development goals. However, further research and an improved large-scale desertification assessment framework are needed. We constructed a comprehensive land desertification status index (LDSI) to assess desertification and its driving mechanisms in Central Asia from 2001 to 2020. Our spatial distance models and principal component analysis were verified by combined field data. The results indicate that desertification levels in Central Asia fluctuated, decreasing from south to north and increasing from west to east. The extent of increased desertification (45.75%) and recovery (45.65%) were nearly equivalent. According to optimal parameters-based geographical detectors, climate factors are the main contributors to desertification, the most significant being reference evapotranspiration. We also found regional differences in the driving mechanisms of desertification. Based on Theil–Sen, Mann–Kendall, and Hurst tests, future desertification intensification of 9.69% is possible, with hotspots mainly in northwestern Central Asia, while 9.73% restoration may occur in other areas. The findings have relevance for achieving LDN. Policymakers should monitor the impact of global climate change and develop recovery measures based on comprehensive consideration of local climate, soil, and terrain conditions. [ABSTRACT FROM AUTHOR]

Soil is the largest carbon reservoir in terrestrial ecosystems, and thus minor changes in it can dramatically affect atmospheric CO2 concentrations. In the northwestern arid zone of China, the prediction of soil organic carbon (SOC) changes is often limited by the scarcity of soil samples and the scale and depth of research, which limit the understanding of carbon cycling processes in arid zone terrestrial ecosystems. Therefore, this study produced digital soil maps of SOC stocks (SOCS) for two periods (1980‐1990 and 2010‐2020) at a 90‐m resolution based on historical soil profile data and a random forest model. The results showed that the prediction accuracy for SOCS in the topsoil (0–30 cm) was superior to that of the subsoil (30–100 cm). Among them, the mean annual evapotranspiration, normalized difference vegetation index during the growing season, multi‐year mean temperature, and clay content were the main environmental factors affecting the spatial distribution of SOCS. In the past 30 years, the SOCS of the northwestern arid zone has decreased by 585.50 Tg, with a mean decline of 19.52 Tg C yr−1. The changes in SOCS caused by land‐use conversion and reductions in SOCS were further shown to be attributable to grassland desertification and agricultural reclamation. These findings are valuable for exploring the carbon cycle in terrestrial ecosystems in the context of global climate change and for achieving China's goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

• The SOC in two depths were mapped at a resolution of 1 km and five-year interval during 1980–2100. • Three climate scenarios of SSP 1–1.9, SSP2-4.5 and SSP5-8.5 in CMIP6 were considered. • The top 20 cm and 100 cm SOC of China both acted as carbon sinks during 1980–2020. • The SOC will fluctuate significantly in the future under different climate scenarios. • Under the SSP2-4.5 scenario, SOC presented a larger likelihood of being a carbon source in most region. Revealing historical changes in soil organic carbon (SOC) and exploring its future status are important for safeguarding soil health and food security, giving full play to the service function of soil ecosystems, and coping with climate change. However, there is still a gap in our understanding of the SOC stocks in China and their spatial patterns in response to future climate change. Therefore, we attempted to fill this knowledge gap using a large amount of soil observation data, digital soil mapping technology, and global circulation models from Coupled Model Inter-comparison Project phase 6 (CMIP6). In this study, a random forest model was selected to construct the spatial relationship between SOC in the top 0–20 cm (SOC020) and 0–100 cm (SOC0100) of the soil and 21 environmental factors. Spatiotemporal changes in SOC from 1980 to 2100 were revealed at a resolution of 1 km and five-year interval for three climate scenarios in CMIP6. The cross-validation results indicated acceptable predictions for both depths of SOC; however, relatively large prediction uncertainties were observed for SOC0100 in the Tibetan Plateau and northeastern China. The mean values of SOC020 and SOC0100 over the last four decades were 35.77 and 84.62 Tg, respectively, and showed carbon sinks at the national scale, with accumulation rates of 0.05 Pg yr-1 and 0.036 Pg y-1 for the two depths. Compared with historical values (1980–2020), SOC will fluctuate significantly in the future under different climate scenarios. Among them, SOC showed a slow increasing trend at both depths under the SSP1-1.9 low emission scenario, while SOC presented a decreasing trend under the SSP2-4.5 and SSP5-8.5 medium–high emission scenarios. In particular, in most of China under the SSP2-4.5 scenario, SOC0100 presented a larger likelihood of being a carbon source. This study provides a reference for exploring the response of soil carbon pools to climate change and evaluating the effectiveness of land management and ecological protection. [ABSTRACT FROM AUTHOR]

• The potential of Google Earth Engine (GEE) to detect long-term wetland change series is explored. • Comparing the response of different types of lake wetlands in the arid area to climate. • Evapotranspiration is the primary factor influencing wetland shrinkage in drylands. Climate change has caused inland wetlands shrinkage and exacerbated problems, such as sustainable development and ecological security, for years. These issues are mainly pronounced in the inland arid area. The ecological environment's deterioration is especially severe in the drylands of the interior. However, dryland wetland changes and their response to climate are poorly understood. This study uses the K-means algorithm in Google Earth Engine (GEE) to classify two typical dryland wetlands (Ebinur and Bosten Lakes) for rapidly and accurately detecting dryland wetland changes. Moreover, it explores the long-term spatial–temporal variation in wetland distribution. In addition, it investigates the response of various lakes to climate change in northern and southern Xinjiang using wavelet analysis. The study's results showed that K-means clustering in the GEE platform has a high classification accuracy (Kappa > 0.8) in wetland classification, making it a feasible approach. The terminal lake wetland types, represented by the Ebinur Lake, changed significantly between 2001 and 2021. In contrast, the inflow-outflow lake wetland types, represented by the Bosten Lake, perform more consistently. Significant spatial–temporal variation is observed at Ebinur Lake, with the lake gradually shrinking and transforming into a marsh, where the largest marsh proportion degrades into non-wetland during the year. Bosten Lake experienced frequent conversions between marsh and non-wetland throughout the year. Furthermore, the responses of various dryland lakes to climate change are consistent, and a low precedes precipitation and follows evapotranspiration. However, their sensitivity to climate response varies, with the terminal lake being most affected by climate change. Mastering the dynamic changes and climate response of dryland wetlands achieves the sustainable development goals of drylands, including carbon neutrality and peak carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Aerosols significantly contribute to global and regional climate change by altering the surface solar radiation, thereby affecting plant productivity. Central Asia is a primary source of global dust aerosols. However, the mechanisms of how aerosols affect terrestrial gross primary productivity (GPP), especially in Central Asia, are not clearly understood. In this study, we investigated the spatial variation in aerosol optical depth (AOD) and GPP and the relationship between them during the growing season (April–October) from 2001 to 2018 using remote sensing data from several sources. We created a GWR-SEM model consisting of a geographically weighted model (GWR) coupled with a structural equation model (SEM) to quantify and analyze the effects of AOD on GPP. The results show that AOD decreased slightly at a rate of −0.0002 y−1 during the study period and that there was a tendency towards spatial aggregation. The extent of AOD pollution in the northwest region (around the Aral Sea) was slightly greater than that in the southeast. GPP increased significantly at a rate of 7.2965 g C m−2 y−2, especially in the northern region. There were some differences in the effects of AOD on GPP between different vegetation types; the highest AOD–GPP correlation was found in shrublands and croplands. Analysis of the GWR-SEM model suggested that AOD and two forms of radiation (surface net radiation, SNR, and photosynthetically active radiation, PAR) explained 72.4% (63.4% for 2001, 66.8% for 2018) of the spatial variation in GPP. SNR had the greatest effect on GPP, followed by AOD. Diffuse PAR had the greatest indirect effect on GPP. The findings of this study highlight the importance of aerosol pollution on spatial variation in gross primary productivity, and they provide a methodological framework for investigating the relationship between AOD and GPP in arid areas. [Display omitted] • Spatial and temporal variations of AOD and GPP over Central Asia are evaluated against MODIS products. • The correlation between AOD and GPP over Central Asia are revealed. • A GWR-SEM model is used to quantitatively evaluate aerosol effects on GPP. • The major drivers of GPP change with time and vegetation types. [ABSTRACT FROM AUTHOR]

Desertification is among the most severe global environmental and the socio-economic problems in the world. This paper is a first attempt to link scientific research to national policymaking on desertification in China. We aim to trace scientific research findings in the national policies and strategies of desertification prevention in China. One example is the large-scale plantation programme in the dust source region threatening Beijing and Tianjin since 1998. It has been suggested that the recent increased forest cover due to plantations in North China has helped reduce dust storm emissions and contributed to mitigating dust storm weather in Beijing and Tianjin. Reforestation/afforestation policy remains in the Chinese national environmental strategies for the new national forestation programme (2011-2020). Overgrazing during recent decades has been blamed for land degradation and desertification in Northwest China by many scholars. Small field experiments prove that vegetation in desertified/degraded land could recover if isolated from human activities. Since 1998, natural recovery has become one powerful national force to prevent land desertification and recover natural vegetation. One example is selected at Cele County, Xinjiang Uygur Autonomous Region to showcase how vegetation could thrive at large scale in natural arid and semi-arid climate if isolated from human intervention. The plantation project has pushed the stakeholders to better understand their negative impact on the environment, especially the overgrazing behaviour. After that, the household income and living level have also been significantly enhanced; however, it is not clear whether the project induced labour migration. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Changes in atmospheric particulate matter content directly affect the Earth-atmosphere system balance and climate change and indirectly affect the environment and ecology. Therefore, this matter is receiving increasing attention. A typical arid area with a fragile ecological environment and frequent dust activities, Xinjiang, China, was investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) daily aerosol optical thickness and Ångström wavelength exponent data to obtain the temporal and spatial distribution characteristics of long-term dust aerosols over 20 years. The frequency of occurrence was calculated to accurately identify anthropogenic and natural sources, and data, such as wind speed, were superimposed to quantitatively estimate dust aerosol emissions. The factors that influenced dust aerosol emissions are discussed. The results show that the distribution of dust aerosols in South and North Xinjiang is obviously different, and the average dust aerosol optical depth (DOD) in spring is higher than that in other seasons. The sources of natural dust have little variation and are primarily located in Lop Nur, on the edges of the Taklamakan and Gurbantunggut deserts, in the central Tuha Basin, and in dried-up lakes. The sources of anthropogenic dust are mainly distributed in the farmland areas of the oasis plain and the impact fan plain. Natural dust aerosols are dominant in Xinjiang, with high natural dust emissions in spring. Changes in anthropogenic dust aerosols are caused by production activities, and the annual average anthropogenic dust emissions account for 8% of the total dust emissions. Precipitation can promote a reduction in natural dust emissions. Topography has an obvious effect on the formation and transportation of dust aerosols, which manifests as the frequent occurrence of dust in the basin. The population density data and Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data reveal, that the intensity of human activities has a great impact on anthropogenic dust aerosols. This study provides support for research on how aerosols affect climate and environmental changes in Xinjiang. · Daily dust aerosol optical depth (DOD) data was obtained from 2003 to 2019 · Anthropogenic and natural dust sources of Xinjiang, China, were identified · Dust aerosols emissions in dust sources were quantitatively estimated · The influences of precipitation, topography, and human on dust aerosols were analyzed [ABSTRACT FROM AUTHOR]

In the past 50 years, the Kaidu–Kongqi River Basin (KKRB) in the arid region of northwest China (ARNC) has experienced drastic climate variability. Meanwhile, from 2000 to 2013, the growths of population and socioeconomic development in the area were drastic, along with much more intensive water management activities. These factors may have caused considerable land use/cover change (LUCC) in the area. Based on the land use/cover classification data derived from the Landsat TM imageries in 1990, 2000, and 2010, as well as the governmental socioeconomic statistics and field observation data, this study investigated the LUCC in the KKRB during 1990–2010. The findings include: (1) The LUCC in the Kaidu–Kongqi River Basin was considerable during the study period, and this change was largely limited to the grassland and cultivated land. The natural grassland in the area decreased with a rate of 118.1 km 2 /y, whereas the cultivated land increased with a rate of 79.2 km 2 /y. The rapid expansion of cultivated land was mainly sourced from reclamations of wasteland and natural grassland. (2) The LUCC has been resulted from the interaction of natural environmental changes and human activities. The changing runoff affected by climate change has played a fundamental role in land use conversion. The human activity intensity index value rose from 0.75 for 1990–2000 to 0.88 for 2000–2010. [ABSTRACT FROM AUTHOR]