Extreme precipitation (EP) is a major external agent driving various natural hazards in the Loess Plateau (LP), China. However, the characteristics of the spatiotemporal EP responsible for such hazardous situations remain poorly understood. We integrate universal multifractals with a segmentation algorithm to characterize a physically meaningful threshold for EP (EPT). Using daily data from 1961 to 2015, we investigate the spatiotemporal variation of EP over the LP. Our results indicate that (with precipitation increasing) EPTs range from 17.3 to 50.3 mm d⁻¹, while the mean annual EP increases from 35 to 138 mm from the northwestern to the southeastern LP. Further, historically, the EP frequency (EPF) has spatially varied from 54 to 116 d, with the highest EPF occurring in the mid-southern and southeastern LP where precipitation is much more abundant. However, EP intensities tend to be strongest in the central LP, where precipitation also tends to be scarce, and get progressively weaker as we move towards the margins (similarly to EP severity). An examination of atmospheric circulation patterns indicates that the central LP is the inland boundary with respect to the reach and impact of tropical cyclones in China, resulting in the highest EP intensities and EP severities being observed in this area. Under the control of the East Asian monsoon, precipitation from June to September accounts for 72 % of the total amount, and 91 % of the total EP events are concentrated between June and August. Further, EP events occur, on average, 11 d earlier than the wettest part of the season. These phenomena are responsible for the most serious natural hazards in the LP, especially in the central LP region. Spatiotemporally, 91.4 % of the LP has experienced a downward trend in precipitation, whereas 62.1 % of the area has experienced upward trends in the EP indices, indicating the potential risk of more serious hazardous situations. The universal multifractal approach considers the physical processes and probability distribution of precipitation, thereby providing a formal framework for spatiotemporal EP assessment at the regional scale.

With the background of climate change and intensified human activities, environmental problems are becoming increasingly prominent on the Qinghai-Tibet Plateau (QTP). For the development of efficient environmental policies and protection measures, quick and accurate assessments of the spatiotemporal patterns in ecological vulnerability are crucial. Based on the Google Earth Engine (GEE) platform, we used Moderate Resolution Imaging Spectroradiometer (MODIS), Shuttle Radar Topography Mission (SRTM), and human footprint (HFP) datasets to analyze the spatiotemporal distributions and main driving factors of the remote sensing ecological vulnerability index (RSEVI) for the QTP. Moreover, spatial autocorrelation analysis and the standard deviational ellipse (SDE) were used to analyze the spatiotemporal characteristics. Our results showed that the RSEVI gradually increased from the southeast to the northwest of the QTP. From 2000 to 2018, the potential vulnerability area increased by 6.59 × 10⁴ km², while the extreme vulnerability area decreased by 1.84 × 10⁴ km². Moran’s I value of the RSEVI was greater than 0 and increased, indicating that the aggregation degree was increasing. The gravity center was located in Nagqu, Tibet, and shifted to the northwest from 2000 to 2015 and to the southeast from 2015 to 2018. The SDE rotated in a counterclockwise direction. The three most important driving factors of ecological vulnerability were wetness, land surface temperature (LST), and the normalized difference vegetation index (NDVI), indicating that climate and vegetation were the dominant factors. Moreover, this study developed a promising method for the ecological vulnerability assessment of large-scale and long time series datasets, and it provides theoretical support for the ecological conservation and sustainable development of the QTP under global change.

Forests are critical ecosystems for environmental regulation and ecological security maintenance, especially at high altitudes that exhibit sensitivity to climate change and human activities. The Qinghai-Tibet Plateau—the world’s largest water tower region—has been breeding many large rivers in Asia where forests play important roles in water regulation and water quality improvement. However, the vulnerability of these forest ecosystems at the regional scale is still largely unknown. Therefore, the aim of this research is to quantitatively assess the temporal–spatial variability of forest vulnerability on the Qinghai-Tibet Plateau to illustrate the capacity of forests to withstand disturbances. Geographic information system (GIS) and the spatial principal component analysis (SPCA) were used to develop a forest vulnerable index (FVI) to assess the vulnerability of forest ecosystems. This research incorporates 15 factors covering the natural context, environmental disturbances, and socioeconomic impact. Results indicate that the measure of vulnerability was unevenly distributed spatially across the study area, and the whole trend has intensified since 2000. The three factors that contribute the most to the vulnerability of natural contexts, environmental disturbances, and human impacts are slope aspect, landslides, and the distance to the farmland, respectively. The vulnerability is higher in forest areas with lower altitudes, steeper slopes, and southerly directions. These evaluation results can be helpful for forest management in high altitude water tower regions in the forms of forest conservation or restoration planning and implementation towards sustainable development goals.

Climate change and anthropogenic activities are reshaping dryland ecosystems globally at an unprecedented pace, jeopardizing their stability. The stability of these ecosystems is crucial for maintaining ecological balance and supporting local communities. Yet, the mechanisms governing their stability are poorly understood, largely due to the scarcity of comprehensive field data. Here we show the patterns of community temporal stability and its determinants across an aridity spectrum by integrating a transect survey across China's drylands with remote sensing. Our results revealed a U-shaped relationship between community temporal stability and aridity, with a pivotal shift occurring around an aridity level of 0.88. In less arid areas (aridity level below 0.88), enhanced precipitation and biodiversity were associated with increased community productivity and stability. Conversely, in more arid zones (aridity level above 0.88), elevated soil organic carbon and biodiversity were linked to greater fluctuations in community productivity and reduced stability. Our study identi fies a critical aridity threshold that precipitates signi ficant changes in community stability in China's drylands, underscoring the importance of distinct mechanisms driving ecosystem stability in varying aridity contexts. These insights are pivotal for developing informed ecosystem management and policy strategies tailored to the unique challenges of dryland conservation. (c) 2024 The Authors. Published by Elsevier B.V. on behalf of Chinese Society for Environmental Sciences, Harbin Institute of Technology, Chinese Research Academy of Environmental Sciences. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).