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Rotated object detection is a crucial task in aerial image analysis. To address challenges such as multi-directional object rotation, complex backgrounds with occlusions, and the trade-off between speed and accuracy in remote sensing images, this paper introduces a lightweight progressive fusion calibration network for rotated object detection (LPFC-RDet). The network comprises three main modules: the Retentive Meet Transformers (RMT) feature extraction block, the Progressive Fusion Calibration module (PFC), and the Shared Group Convolution Lightweight detection head (SGCL). The RMT feature extraction block integrates a retentive mechanism with global context modeling to learn rotation-insensitive features. The PFC module employs pixel-level, local-level, and global-level weights to calibrate features, enhancing feature extraction from occluded objects while suppressing background interference. The SGCL detection head uses decoupled detection tasks and shared group convolution layers to achieve parameter sharing and feature interaction, improving accuracy while maintaining a lightweight structure. Experimental results demonstrate that our method surpasses state-of-the-art detectors on three widely used remote sensing object datasets: HRSC2016, UCAS_AOD, and DOTA. [ABSTRACT FROM AUTHOR]

Wind erosion climatic erosivity is a measure of climatic conditions that affect wind erosion. Projecting wind erosion climatic erosivity is curcial for predicting future wind erosion risk. In this study, we employed dynamic downscaling outputs from the MPI-ESM1-2-HR model to project changes in wind erosion climatic erosivity over High Mountain Asia (HMA) from 2041 to 2060 under a middle-emission scenario (an additional radiative forcing of 4.5 W/m2 by 2100). From 1995 to 2014, wind erosion climatic erosivity in HMA was high in the southwest, on the Qiangtang Plateau, and in the Qaidam Basin, exceeding 1 kg·m−1 s−1. Compared to the period 1995–2014, wind erosion climatic erosivity is projected to decrease by 0.5 kg·m−1 s−1 over the east of the Qiangtang Plateau and increase by approximately 1 kg·m−1 s−1 in the southwest of the HMA during 2041–2060 under the middle emission scenario. This increase in wind erosion climatic erosivity in the southwest of HMA is attributed to a projected rise in high-wind frequency for 2041–2060 compared to 1995–2014. Conversely, the decrease in wind erosion climatic erosivity in the east of the Qiangtang Plateau results from increased precipitation during 2041–2060, which mitigates the effects of increased high-wind frequencies. Given the growing risk of wind erosion in the southwest of the HMA, it's essential to implement appropriate mitigation policies for the future. [ABSTRACT FROM AUTHOR]

Diversified molecular information‐processing methods have significant implications for nanoscale manipulation and control, monitoring and disease diagnosis of organisms, and direct intervention in biological activities. However, as an effective approach for implementing multifunctional molecular information processing, DNA reaction networks (DRNs) with numerous functionally specialized molecular structures have challenged them on scale design, leading to increased network complexity, further causing problems such as signal leakage, attenuation, and cross‐talk in network reactions. Our study developed a strategy for performing various signal‐processing tasks through engineering modular DRNs. This strategy is based on a universal core unit with signal selection capability, and a time‐adjustable signal self‐resetting module is achieved by combing the core unit and self‐resetting unit, which improves the time controllability of modular DRNs. In addition, multi‐input and ‐output signal cross‐catalytic and continuously adjustable signal delay modules were realized by combining core and threshold units, providing a flexible, precise method for modular DRNs to process the signal. The strategy simplifies the design of DRNs, helps generate design ideas for large‐scale integrated DRNs with multiple functions, and provides prospects in biocomputing, gene regulation, and biosensing. [ABSTRACT FROM AUTHOR]

The Jishishan Ms 6.2 earthquake occurred at 23:59 on December 18, 2023 in Gansu Province, China. We conducted a field survey to assess the hazards and damages caused by the earthquake and its associated geo-activities. Subsequently, we organized a seminar to discuss the possible causes of the destruction of a prehistoric site—Lajia Settlement—dated back to four thousand years B.P. and located only several kilometers away from the epicenter of the Jishishan earthquake. The Jishishan earthquake was unique for its hazard and disaster process, which featured ground shaking and a series of complex geological and geomorphological activities: sediment and soil spray piles, liquefaction, collapse, landslide, and mudflow along water channels. We define this phenomenon as the Jishishan earthquake ripple hazard (JERH). The most recent evidence from the JERH suggests that a prehistoric earthquake similar to the JERH, instead of riverine floods or earthquake-induced landslide dam outburst flood, as previously hypothesized, destroyed the Lajia Settlement. [ABSTRACT FROM AUTHOR]

Although the World Health Organization has declared that the COVID‐19 pandemic no longer qualifies as a global public health emergency, it still needs to explore the response of society to the COVID‐19 pandemic. Socio‐economic status (SES) was proven to be linearly associated with the COVID‐19 pandemic, although this relationship may be more complex due to regional differences. In the study, we analyzed and revealed the effects and mechanisms of SES on infections among low, lower‐middle, upper‐middle and high SES group (LSG, LMSG, UMSG, and HSG, respectively). The results showed that the relationship between SES and infections was inverted U‐shaped, especially in the first three phases. In Phase I, UMSG had the highest number of infections, with an average of 238.31/1M people (95%CI: 135.47–341.15/1M people). In Phases II and III, infections decreased insignificantly with increasing SES (r = −0.01, p = 0.92; r = −0.11, p = 0.22) and the highest number of infections were found in the LMSG. In Phase IV, SES was positively related to the number of infections (r = 0.54, p < 0.001). Furthermore, the nonlinear impact of multiple factors related to SES on the infections explains the complex relationships between SES and infections. SES affected infections mainly through medical resources, demographics and vaccination, and differed across the SES groups. Particularly, demographics could exert an impact on population mobility, subsequently influencing infections in LMSG, with an indirect effect of 0.01 (p < 0.05) in Phase II. This study argues for greater attention to countries with middle SES and the need for future targeted measures to cope with infectious diseases. Plain Language Summary: As the virulence of SARS‐CoV‐2 diminishes and vaccination coverage rises, countries around the world are gradually returning to normal development like the pre‐COVID‐19 period. However, the COVID‐19 pandemic crisis of the past three years calls for thoughtful reflection, presenting us with experiences and lessons to learn from. Previous studies suggested that the infections were linearly associated with socio‐economic status (SES). Nevertheless, SES was related with multiple factors (such as vaccination), leading to the complex relationship between infections and SES. Therefore, it still needs to analyze the impacts and mechanisms of SES on infections. Empirical results show the relationship between SES and infections was an inverted U‐shape in the progress of the COVID‐19 pandemic, and the infections in lower‐middle and upper‐middle SES countries was the highest in the first three phases. SES affected infections through multiple factors and the mechanisms differed across SES groups. This work emphasizes the need to be attentive to the further prevalence of infectious diseases in middle‐SES countries and implementing the target measures in different SES countries in the future. Key Points: The response of society to the COVID‐19 pandemic was exploredSocio‐economic status had an inverted U‐shaped relationship with infections during the COVID‐19 pandemicSES affected infections mainly through action time, demographics, medical resources and vaccination [ABSTRACT FROM AUTHOR]

Compound dry and hot extremes are proved to be the most damaging climatic stressor to wheat thereby with grave implications for food security, thus it is critical to systematically reveal their changes under unabated global warming. In this study, we comprehensively investigate the global change in compound dry and hot days (CDHD) within dynamic wheat growing seasons during 2015–2100 under 4 socio-economic scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) based on the latest downscaled Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Our results demonstrate a notable increase in CDHD’s frequency ( CDHD f ) and severity ( CDHD s ) worldwide under all SSPs, such increase is sharper over southern Asia in winter wheat growing season, and southern Canada, northern America, Ukraine, Turkey and northern Kazakhstan in spring wheat growing season. As the top 10 wheat producer, India and America will suffer much more detrimental CDHD in their wheat growing season. Adopting a low forcing pathway will mitigate CDHD risks in up to 93.3% of wheat areas. Positive dependence between droughts and heats in wheat growing season is found over more than 74.2% of wheat areas, which will effectively promote the frequency and severity of CDHD. Global warming will dominate the increase of CDHD directly by increasing hot days and indirectly by enhancing potential evapotranspiration thereby aggravating droughts. This study helps to optimize adaptation strategies for mitigating CDHD risks on wheat production, and provides new insights and analysis paradigm for investigating future variations in compound extremes occurring within dynamic crops growing seasons. [ABSTRACT FROM AUTHOR]

The United Nations' Sustainable Development Goal (SDG) 3.9 calls for a substantial reduction in deaths attributable to PM2.5 pollution (DAPP). However, DAPP projections vary greatly and the likelihood of meeting SDG3.9 depends on complex interactions among environmental, socio-economic, and healthcare parameters. We project potential future trends in global DAPP considering the joint effects of each driver (PM2.5 concentration, death rate of diseases, population size, and age structure) and assess the likelihood of achieving SDG3.9 under the Shared Socioeconomic Pathways (SSPs) as quantified by the Scenario Model Intercomparison Project (ScenarioMIP) framework with simulated PM2.5 concentrations from 11 models. We find that a substantial reduction in DAPP would not be achieved under all but the most optimistic scenario settings. Even the development aligned with the Sustainability scenario (SSP1-2.6), in which DAPP was reduced by 19%, still falls just short of achieving a substantial (≥20%) reduction by 2030. Meeting SDG3.9 calls for additional efforts in air pollution control and healthcare to more aggressively reduce DAPP. Reducing PM2.5 air pollution from biomass burning, transport, energy, and manufacturing, in combination with improvements in healthcare, especially in emerging economies like India and China, will be crucial to meeting SDG3.9 [ABSTRACT FROM AUTHOR]

The extreme precipitation in China is greatly influenced by the East Asian summer monsoon, which can be divided into two components: the southeast monsoon (SEM) and the southwest monsoon (SWM). The Hanjiang River basin (HJB), a representative monsoon‐influenced basin in China, is alternately influenced by the southwest monsoon and southeast monsoon throughout the year. However, the specific relationship between rainstorms and monsoons, and the relative contribution of different monsoons, remains unclear in the HJB. Using multiple datasets, this study analysed the variability of various rainstorm types in the HJB during 1985–2020, investigated their relationships with different monsoon indicators and assessed the contribution of monsoons on the rainstorm variance. The results reveal a nonsignificant increasing trend in rainstorms within the basin, the severe convective rainstorm days accounted for a high proportion of the total rainstorm days, and the spatiotemporal characteristics of different rainstorm types are different. The rainstorm indicators are significantly correlated with the monsoon within the HJB and are positively correlated with the SWM, particularly its intensity. The SEM exhibits a weak correlation with rainstorms and has limited explanation for the variance in rainstorms. The intensity of SWM within the HJB shows a significant positive correlation with all rainstorm indicators. It is also detected as the most important indicator for explaining the interannual variation in rainstorms, explaining 41.97% and 39.45% of the variance in daily rainstorm frequency and totals, which comprises more than half of the total explanatory portion. The explanation of circulation factors for the variance in daily rainstorms is higher than that for severe convective rainstorms. In addition to monsoons, the Pacific Decadal Oscillation and the Southern Oscillation Index also have a great contribution to the rainstorm variability in the HJB. [ABSTRACT FROM AUTHOR]

A decline in atmospheric oxygen concentration is projected in the 21st century given the background of global warming. The Qinghai-Tibetan Plateau is located at a high altitude, and thus, it faces a hypoxia challenge; however, knowledge of the factors contributing to its atmospheric oxygen concentration is still lacking. Here, we conducted joint observations of ecosystem oxygen production and carbon sinks and near-surface atmospheric oxygen concentrations on the Qinghai-Tibetan Plateau and meteorological elements at Beijing Fangshan Station. Using seasonal differences and statistical methods, we calculated the relative contribution rates of vegetation to changes in atmospheric oxygen concentration. Our results indicate that solar radiation, atmospheric humidity, and ecosystem oxygen consumption and production have a significant impact on the atmospheric oxygen concentration, and the impact shows temporal and spatial differences. Vegetation significantly impacts the oxygen concentration, with a contribution rate of 16.7%–24.5%, which is underestimated in existing research. Our findings provide important insights into the factors that influence atmospheric oxygen concentration and highlight the contribution of vegetation. To better understand the oxygen dynamics of the Qinghai-Tibetan Plateau, we recommend further field observations of soil respiration and vegetation photosynthesis to clarify the contributions of carbon storage, carbon sinks and other factors to the near-surface atmospheric oxygen concentration. [ABSTRACT FROM AUTHOR]

Investigating the response of landslide activity to climate change is crucial for understanding the disastrous effects of climate change on high mountains. However, the lack of long-term, spatial-temporal consistent measurement of landslide activity prohibits the study of this relationship. In this work, we used two methods to derive the time series of a landslide's deformation and study its relationship with precipitation in the northeastern Tibetan Plateau. The small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) method with Sentinel-1A images is first applied to derive time series of the landslide's deformation from 2020 to 2021. A recently developed method to derive cumulative deformations of optical images was used with Landsat 5 and Sentinel-2 images to derive the long-term deformation time series from 1986 to 2023. Centimeter-scale deformations detected by using the InSAR method are mainly located in the upper and eastern parts of the landslide, whereas meter-scale deformations detected by using the optical method are in the middle of the landslide. Time-series results from both methods show that intra-annual initiations of the landslide's deformation occurred in rainy months (from July to October). Although there seems to be no direct relations between inter-annual deformations and precipitation, significant displacements since 2020 occurred after exceptionally wet years from 2018 (with a record-breaking precipitation year in 2020). With optical images, we found that the maximum cumulative deformation of the landslide has been >35 m since 1986 with major deformations (>20 m) found after 2020, which may indicate an imminent risk to the Lijie town near the toe of the landslide. With climate change, increased precipitation is expected in future, which may trigger more similar landslides in the vicinity of this region. This work demonstrates an executable framework to assess landslide hazard risk under climate change. [ABSTRACT FROM AUTHOR]

For the ecologically vulnerable Qinghai-Tibet Plateau (QTP), hypoxia is increasingly becoming an extremely important environmental risk factor that significantly affects the health of both humans and livestock in the plateau region, as well as hindering high-quality development. To focus on the problem of hypoxia, it is especially urgent to study the surface oxygen concentration (i.e., oxygen concentration). However, the existing research is not sufficient, and there is a lack of oxygen concentration data collected on the QTP. In this study, through the Second Tibetan Plateau Scientific Expedition and Research and field measurements, the oxygen concentration data and corresponding geographic environmental data were collected at 807 measurement points on the QTP from 2017 to 2022, and the spatiotemporal oxygen concentration patterns were estimated. This work filled the gaps in the measurement and research of oxygen concentrations on the QTP while providing data support for analyses of the influencing factors and spatiotemporal characteristics of oxygen concentrations, which is of great significance for promoting the construction of ecological civilization in the QTP region. Measurement(s) Surface oxygen concentration Technology Type(s) Field measurement, model estimation Factor Type(s) Geographic location, raster Sample Characteristic - Environment Land cover Sample Characteristic - Location Qinghai-Tibet Plateau [ABSTRACT FROM AUTHOR]

On 6 February 2023, two 7.8 magnitude earthquakes consecutively hit south-central Türkiye, causing great concern from all governments, the United Nations, academia, and all sectors of society. Analyses indicate that there is also a high possibility of strong earthquakes with a magnitude of 7.8 or above occurring in the western region of China in the coming years. China is a country that is highly susceptible to catastrophic disasters such as earthquakes, floods, and other natural calamities, which can cause significant damages to both human life and property, as well as widespread impacts on the society. Currently, China's capacity for disaster prevention and control is still limited. In order to effectively reduce the impact of catastrophic disasters, ensure the safety of people's lives and property to the greatest extent possible, maintain social stability in high-risk areas, and ensure high-quality and sustainable regional development, it is urgent to improve the seismic resistance level of houses and critical infrastructure in high earthquake risk zones and increase the earthquake-resistant design level of houses in high-risk fault areas with frequent seismic activities; significantly enhance the ability to defend against extreme weather and ocean disasters in economically developed areas along the southeastern coast, as well as the level of fortification in response to extreme meteorological and hydrological disasters of coastal towns/cities and key infrastructure; vigorously enhance the emergency response capacity and disaster risk prevention level in western and ethnic minority regions; comprehensively improve the defense level of residential areas and major infrastructure in high geological hazard risk zones with flash floods, landslides, and mudslides; systematically promote national disaster prevention and mitigation education; and greatly enhance the societal disaster risk reduction ability, including catastrophic insurance. [ABSTRACT FROM AUTHOR]

Landslides cause huge human and economic losses globally. Detecting landslide precursors is crucial for disaster prevention. The small baseline subset interferometric synthetic-aperture radar (SBAS-InSAR) has been a popular method for detecting landslide precursors. However, non-monotonic displacements in SBAS-InSAR results are pervasive, making it challenging to single out true landslide signals. By exploiting time series displacements derived by SBAS-InSAR, we proposed a method to identify moving landslides. The method calculates two indices (global/local change index) to rank monotonicity of the time series from the derived displacements. Using two thresholds of the proposed indices, more than 96% of background noises in displacement results can be removed. We also found that landslides on the east and west slopes are easier to detect than other slope aspects for the Sentinel-1 images. By repressing background noises, this method can serve as a convenient tool to detect landslide precursors in mountainous areas. [ABSTRACT FROM AUTHOR]

Plant water source partitioning suffers from multiple uncertainty sources including tracers, depleted xylem water deuterium, and mixing models, but the uncertainties have rarely been systematically evaluated. Taking apple trees of different ages as example, we combined four tracers of different characteristics (2H, 3H, 17O, and 18O), two xylem water deuterium bias correction methods (soil water excess and stem relative water content), and four mixing models (IsoSource, SIAR, MixSIR, and MixSIAR) to quantify the total uncertainty and the uncertainty of each component. For the total uncertainty, the contributions of the mixing models were the largest (37%), followed by those of tracers (28%) and interaction of tracers and models (27%), while the contributions of other sources were the smallest (8%). In particular, the xylem water deuterium bias correction methods had an uncertainty of 2%, implying its minor role in deviating plant water source partitioning. After evaluating the performance of the three components with four target functions, we recommend tracer combination of 2H18O with MixSIAR as the best framework for water source partitioning of apple trees on the Loess Plateau. The decomposed uncertainties and recommended methods provide technical support and promote understanding of variable results in plant water source partitioning. Plain Language Summary: Plants may absorb water from multiple sources, including precipitation, soil water of different layers, streamwater, and groundwater. Identifying the plant water source is important for management of plant productivity and water resources. In this context, the isotope‐based methods have been widely applied to partition plant water sources. However, uncertainties have been detected from tracers, depleted xylem water deuterium, and mixing models. Despite that the above uncertainty sources have been separately explored by different studies, and the contribution of each uncertainty component to the total uncertainty has rarely been investigated. To explore this knowledge gap, we employ four isotopes, two xylem water deuterium correction methods, and four mixing models to generate the possible isotope‐correction method‐mixing model combinations. We compare the uncertainty of each component in these combinations to determine the steps that should be paid more attention in plant water source partitioning. Further, we recommend the best isotope‐correction method‐mixing model combination for plant water source partitioning. Although the recommended method may be limited to the regions with climate and vegetation similar to this study, this study presents a valuable technical insight into the evaluation and selection of methods for plant water source partitioning. Key Points: We decompose the uncertainties in isotope‐based plant water source partitioning, and analyze dominance of each uncertainty componentMixing models and tracers have dominant but deuterium bias correction has negligible effect on partitioned plant water sourcesWe propose a framework on evaluating and selecting the most suitable methods for plant water source partitioning [ABSTRACT FROM AUTHOR]

Global warming has caused changes in the area and thickness of permafrost on the Qinghai-Tibet Plateau and prompted the transition from permafrost to seasonally frozen soil, which has affected the soil moisture, soil temperature, and distribution of plant roots. This, in turn, affects grassland vegetation productivity and aboveground/belowground biomass. In this study, we took Qinghai Province in the northeastern Qinghai-Tibet Plateau as the research area to model the spatial pattern of grassland biomass and then evaluated the potential influence of frozen soil type information on aboveground and belowground biomass. Our research shows that there are significantly more biomass observations in seasonally frozen soil regions than in permafrost regions. However, when we ignore the type of frozen soil, the model does not show more accurate simulation in seasonally frozen soil regions, mainly because the stronger correlation between permafrost biomass and environmental factors, such as precipitation, compensates for the lack of observational data. In addition, we found that the biomass estimation error can be reduced significantly by building different models for each type of frozen soil, which implies that the type of frozen soil has an important impact on grassland biomass. Therefore, in considering the effects of future climate warming, more attention should be given to the impact of changes in frozen soil type on regional vegetation productivity. In addition, our investigation contributes a benchmark dataset of above- and belowground vegetation carbon storage in different frozen soil types, which provides the research community with useful information for optimizing process-based carbon cycle models. [ABSTRACT FROM AUTHOR]

Regional modeling of landslide hazards is an essential tool for the assessment and management of risk in mountain environments. Previous studies that have focused on modeling earthquake-triggered landslides report high prediction accuracies. However, it is common to use a validation strategy with an equal number of landslide and non-landslide samples, scattered homogeneously across the study area. Consequently, there are overestimations in the epicenter area, and the spatial pattern of modeled locations does not agree well with real events. In order to improve landslide hazard mapping, we proposed a spatially heterogeneous non-landslide sampling strategy by considering local ratios of landslide to non-landslide area. Coseismic landslides triggered by the 2008 Wenchuan Earthquake on the eastern Tibetan Plateau were used as an example. To assess the performance of the new strategy, we trained two random forest models that shared the same hyperparameters. The first was trained using samples from the new heterogeneous strategy, and the second used the traditional approach. In each case the spatial match between modeled and measured (interpreted) landslides was examined by scatterplot, with a 2 km-by-2 km fishnet. Although the traditional approach achieved higher AUCROC (0.95) accuracy than the proposed one (0.85), the coefficient of determination (R2) for the new strategy (0.88) was much higher than for the traditional strategy (0.55). Our results indicate that the proposed strategy outperforms the traditional one when comparing against landslide inventory data. Our work demonstrates that higher prediction accuracies in landslide hazard modeling may be deceptive, and validation of the modeled spatial pattern should be prioritized. The proposed method may also be used to improve the mapping of precipitation-induced landslides. Application of the proposed strategy could benefit precise assessment of landslide risks in mountain environments. [ABSTRACT FROM AUTHOR]

A dry valley is a special landscape type that is formed by the combined effect of climate and topography. Accurately defining the scope of a dry valley and knowledge of its spatial distribution characteristics can provide data support for relevant studies in the region. Starting from natural ontological characteristics and formation mechanisms, we constructed a geographical ontological model of dry valleys through an analysis of concepts related to the dry valley and combined GIS technology and methods to accurately define the scope and analyze the spatial characteristics of the dry valleys in the Three Parallel Rivers Region (DVT). Our results show that: (1) The geographically and ontologically oriented method developed to define the scope of the dry valley has a high accuracy, with an overall accuracy of 92.3% and a kappa coefficient of 0.84, therefore it can provide a better mechanism for defining the scope of a dry valley on a large scale. (2) The total area and total length of the DVT are 6147.1 km2 and 2125.3 km, respectively. The dry valleys in this region are mainly located in the Tibet Autonomous Region and in the Sichuan and Yunnan provinces in China. (3) The terrain in the DVT is precipitous, and areas with slopes greater than 25° account for 70% of the total area of the dry valleys. The DVT area of sunny aspects (north, northeast, and northwest aspects) is larger than that of shady aspects (south, southeast, and southwest aspects), and the land cover is mainly grassland with a desert substrate. The result of our study can provide data support for further in-depth research in related fields of dry valleys. [ABSTRACT FROM AUTHOR]

Based on historical land use for eight periods from 1980 to 2020 and the projected land use under seven Shared Socioeconomic Pathways (SSPs: SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5) from 2021 to 2100, we conducted a study on past and future land use changes in the Qinghai-Tibet Plateau (QTP). This work aims to reveal the land use changes during the carbon peak (2021–2040) and carbon neutrality (2051–2070) periods and at the end of the 21st century (2081–2100). The results show that: (1) in the historical period (1980–2020), the land use types in the QTP were grassland (1475×103 km2, 58.2%), barren land (685×103 km2, 27.0%), forest land (243×103 km2, 9.6%), water (114×103 km2, 4.5%), cropland (18.6×103 km2, 0.7%) and urban land (0.3×103 km2, 0.01%). (2) Relative to the baseline period (1995–2014), the area of grassland is projected to decrease by 0.7% (SSP4-6.0)–5.4% (SSP2-4.5) (0.5–3.9% of the total area of the QTP), 2.8% (SSP4-6.0)–12.5% (SSP3-7.0) (2.1–9.4% of the total area of the QTP) and 6.1% (SSP4-6.0)–21.7% (SSP4-3.4) (4.6–16.4% of the total area of the QTP) in the future three periods. In contrast, the forest land area is projected to increase, by approximately 2.5% (SSP4-6.0) to 30.1% (SSP3-7.0) (0.3–4.3% of the total area of the QTP), 9.2% (SSP4-6.0) to 56.5% (SSP2-4.5) (1.3–8.0% of the total area of the QTP), and 21.2% (SSP4-6.0) to 72.8% (SSP2-4.5) (3.0–10.2% of the total area of the QTP) in the future three periods, respectively. (3) Approximately 0.4 (SSP4-6.0) to 6.9% (SSP5-8.5), 0.9 (SSP4-6.0) to 2.7% (SSP4-3.4), and 0.04 (SSP5-8.5) to 3.5% (SSP1-1.9) of land is expected to convert from grassland to forest land in the future three periods, respectively. The shift from grassland to forest land area is likely to enhance the carbon sink potential of the QTP in the future period. [ABSTRACT FROM AUTHOR]

The construction of DNA reaction networks with complex functions using various methods has been an important research topic in recent years. Whether the DNA reaction network can perform complex tasks and be recycled directly affects the performance of the reaction network. Therefore, it is very important to design and implement a DNA reaction network capable of multiple tasks and reversible regulation. In this paper, the hairpin allosteric method was used to complete the assembly task of different functional nucleic acids. In addition, information conversion of the network was realized. In this network, multiple hairpins were assembled into nucleic acid structures with different functions to achieve different output information through the cyclic use of trigger strands. A method of single-input dual-output information conversion was proposed. Finally, the network with signal amplification and reversible regulation was constructed. In this study, the reversible regulation of different functional nucleic acids in the same network was realized, which shows the potential of this network in terms of programmability and provides new ideas for constructing complex and multifunctional DNA reaction networks. [ABSTRACT FROM AUTHOR]

Living organisms can produce corresponding functions by responding to external and internal stimuli, and this irritability plays a pivotal role in nature. Inspired by such natural temporal responses, the development and design of nanodevices with the ability to process time-related information could facilitate the development of molecular information processing systems. Here, we proposed a DNA finite-state machine that can dynamically respond to sequential stimuli signals. To build this state machine, a programmable allosteric strategy of DNAzyme was developed. This strategy performs the programmable control of DNAzyme conformation using a reconfigurable DNA hairpin. Based on this strategy, we first implemented a finite-state machine with two states. Through the modular design of the strategy, we further realized the finite-state machine with five states. The DNA finite-state machine endows molecular information systems with the ability of reversible logic control and order detection, which can be extended to more complex DNA computing and nanomachines to promote the development of dynamic nanotechnology. [ABSTRACT FROM AUTHOR]

As a crucial component of the climate system, snow cover plays an important role on surface energy budgets, hydrological cycles and socioeconomic development. This paper investigated the spatiotemporal patterns of snow depth across the Qinghai Plateau (QP) during 1980–2018 based on passive microwave (PMW) satellite observation and reanalysis products. The study identified the relationships between the changes in PMW snow depth and topographic features and revealed the impact of climatic variables (air temperature, precipitation and wind speed) and large‐scale atmospheric circulations on observed snow depth variability. The results show that the spatial pattern of snow depth climatology is similar in all datasets, except in terms of magnitude, with high values in the southern and southeastern parts of the QP and low values in the eastern and northwestern parts. Average snow depth correlates positively with precipitation, elevation and slope, and negatively with air temperature and wind speed. The long‐term trends in snow depth vary with the season and the datasets. The PMW snow depth across the QP shows a significant annual (−0.125 cm·decades−1, p <.10) and spring (−0.184 cm·decades−1, p <.05) negative trend, while snow depth for ERA5 and MERRA2 does not present significant trends. Air temperature dominates total snow depth variation over the QP, explaining 43.85, 24.88 and 47.28% of annual, winter and spring PMW snow depth variations, which significantly affects snow depth variations in most parts of the QP, yet the effects of precipitation and wind speed on snow depth variation exhibit significant regional differences, and atmospheric circulations (e.g., AMO) also have a remarkable controlling effect on some localized areas. [ABSTRACT FROM AUTHOR]

The Qinghai-Tibet Plateau and its adjacent mountainous areas are characterized by significant climate differences, diverse geomorphology, active glaciers, and strong crustal uplift and river incision. The first part - changes in cryosphere-related disasters driven by the warming climate - provides latest insights on the changes related to snow avalanches and thaw slumps of permafrost on the plateau, driven by climate change. Li et al. used debris flow data, historical meteorological data, and future climate projection data to assess the debris flow risk of the Karakoram Highway region. [Extracted from the article]

Land subsidence is impacting large populations in coastal Asia via relative sea-level rise (RSLR). Here we assesses these risks and possible response strategies for China, including estimates of present rates of RSLR, flood exposure and risk to 2050. In 2015, each Chinese coastal resident experienced on average RSLR of 11 to 20 mm/yr. This is 3 to 5 times higher than climate-induced SLR, reflecting that people are concentrated in subsiding locations. In 2050, assuming these subsidence rates continue, land area, population and assets exposed to the 100-year coastal flood event is 20%-39%, 17%-37% and 18%-39% higher than assuming climate change alone, respectively. Realistic subsidence control measures can avoid up to two thirds of this additional growth in exposure, with adaptation required to address the residual. This analysis emphasizes subsidence as a RSLR hazard in China that requires a broad-scale policy response, utilizing subsidence control combined with coastal adaptation. Chinese coastal populations are concentrated in subsiding locations, and also subject to sea-level rise. Here the authors find that more areas, population and assets are exposed to coastal flooding by 2050 but realistic subsidence control measures can avoid additional risks. [ABSTRACT FROM AUTHOR]

It is generally believed that global warming drives an increase in heatwaves, but these changes vary regionally. Projected trends of heatwaves and comparisons between observed and projected heatwave trends are poorly understood. We selected multiple characteristics of global heatwave events, including indicators on heat‐related health impacts under historical and future scenarios from the NASA Earth Exchange/Global Daily Downscaled Projections (NEX‐GDDP) dataset. We quantified the trends in the frequency, intensity, duration and peak temperature of heatwave events and identified heatwave hotspots that respond dramatically to radiative forcing. Future simulations suggest a four‐fold increase in the duration of heatwaves by 2050s, spatially concentrated in central Africa, northern South America and Southeast Asia, and the maximum duration of single heatwave event will be up to 44 days under a high emission scenario. Accelerated increasing trends are also detected in intensity, total duration and temperature of heatwaves with up to 2‐fold, 8‐fold and 9‐fold larger than the trends of the baseline period under the high emission scenario. Considering socioeconomic exposure to extreme heatwaves, we identified some hotspot areas in western Europe, eastern North America and northern China that will face greater potential risks in the coming future and therefore need to urgently strengthen their adaptation capacity. [ABSTRACT FROM AUTHOR]

Wind regime is one of the main natural factors controlling the evolution and distribution of aeolian sand landforms, and sand drift potential (DP) is usually used to study the capacity of aeolian sand transport. The Badain Jaran Desert (BJD) is located where polar cold air frequently enters China. Based on wind data of eight nearby meteorological stations, this research is intended to explore the temporal variation and spatial distribution features of wind speed and DP using linear regression and cumulative anomaly method, and reveal the relationship between atmospheric circulation and wind speed with correlation analysis. We found that the wind speed and frequency of sand-blowing wind in the BJD decreased significantly during 1971–2016, and the wind speed obviously mutated in 1987. The regional wind speed change was affected by the Asian polar vortex, the northern hemisphere polar vortex and the Tibet Plateau circulation. The wind rose of the annual sand-blowing wind in this region was the "acute bimodal" type. Most of the annual wind directions clustered into the W-NW, and the prevailing wind direction was WNW. During 1971–2016, the annual DP, the resultant drift potential (RDP) and the directional variability (PDP/DP) in the desert showed an obvious downtrend, with a "cliff-like" decline in the 1980s and relative stable fluctuation thereafter. The BJD was under a low-energy wind environment with the acute bimodal wind regime. Wind speed, sand-blowing wind frequency and DP were high in the northeast and low in the southwest. [ABSTRACT FROM AUTHOR]

As the largest component of carbon export from terrestrial ecosystems, ecosystem respiration (RECO), together with vegetation productivity, determines the carbon stock changes in terrestrial ecosystems, so it is crucial to reveal the response of RECO to climate change. However, the simulation of RECO is usually inaccurate due to the neglect of the lagged response of respiration to changes in water conditions. In this study, we integrated meteorological data, remote sensing data, and soil data, and introduced the indicators of the previous water conditions into the deep learning model to simulate RECO. The conclusions are as follows: (a) There is a 1–2 years' lagged response of RECO to changes in water conditions. (b) It is necessary to consider the influence of previous water conditions when simulate RECO. It not only improved the simulation accuracy of RECO, but also reflected its inter‐annual fluctuations and change trends more accurately, avoiding the underestimation of RECO inter‐annual fluctuations. (c) There is an inconsistency in carbon input and carbon output change trends which impacts the carbon sink pattern and potential of terrestrial ecosystems. The growth trend of Gross Primary Production (GPP) in global terrestrial ecosystems is greater than that of RECO, with a trend of increasing carbon sinks, especially in the northern extra‐tropics; while the carbon sink capacity of tropical regions has gradually saturated, showing that the change trend of RECO is close to that of GPP, which poses a potential risk to the sustainable carbon sink capacity of global ecosystems in the future. Plain Language Summary: Ecosystem respiration (RECO) is the largest component of carbon export from terrestrial ecosystems and determines the carbon sink potential of terrestrial ecosystems. Consider from the perspective of carbon cycle mechanism, it is reasonable to believe that RECO has the lagged response to changes in water conditions. However, most studies usually consider the water conditions in growing season only, which caused the inaccurate RECO simulations and underestimation of RECO's interannual variation. In this study, we introduced the multi‐time scale standardized precipitation evapotranspiration indexes‐which can reflect the current and previous water conditions‐into deep learning models to construct an optimal model for simulating global‐scale RECO. We revealed the optimal time scales of the lagged effect that need to be considered in RECO simulations and analyzed the global pattern of RECO tendencies and its implications on terrestrial carbon sink potential. We believe this paper to be of particular interest to the readers of your journal as our method is novel that could well reveal the spatial pattern and the interannual variations of RECO at global scale and our results have important implications for the assessment of terrestrial ecosystem carbon sink. In addition, it revealed some new rules that are interesting for the academic community. Key Points: There is a 1–2 years' lagged response of ecosystem respiration (RECO) to changes in water conditionsConsidering the previous water conditions can improve the simulation accuracy of RECO and its inter‐annual fluctuationsThere is an inconsistency in carbon input and carbon output change trends which impacts the carbon sink potential of terrestrial ecosystems [ABSTRACT FROM AUTHOR]

Heat stroke is a serious heat‐related health outcome that can eventually lead to death. Due to the poor accessibility of heat stroke data, the large‐scale relationship between heat stroke and meteorological factors is still unclear. This work aims to clarify the potential relationship between meteorological variables and heat stroke, and quantify the meteorological threshold that affected the severity of heat stroke. We collected daily heat stroke search index (HSSI) and meteorological data for the period 2013–2020 in 333 Chinese cities to analyze the relationship between meteorological variables and HSSI using correlation analysis and Random forest (RF) model. Temperature and relative humidity (RH) accounted for 62% and 9% of the changes of HSSI, respectively. In China, cases of heat stroke may start to occur when temperature exceeds 36°C and RH exceeds 58%. This threshold was 34.5°C and 79% in the north of China, and 36°C and 48% in the south of China. Compared to RH, the threshold of temperature showed a more evident difference affected by altitude and distance from the ocean, which was 35.5°C in inland cities and 36.5°C in coastal cities; 35.5°C in high‐altitude cities and 36°C in low‐altitude cities. Our findings provide a possible way to analyze the interaction effect of meteorological variables on heat‐related illnesses, and emphasizes the effects of geographical environment. The meteorological threshold quantified in this research can also support policymaker to establish a better meteorological warning system for public health. Plain Language Summary: The impact of extreme heat events on population has become of urgent public health concern. In China, the real mortality and morbidity data are not publicly available and data of some diseases are not enough recorded. Thus, it is difficult to build a solid relationship between heat strokes and meteorological variables in large spatial scale. Internet search data, highly correlated with real heat stoke cases, was adopted as a new data set in our research instead of the heat‐related morbidity data to investigate the relationship between heat strokes and multiple meteorological variables. According to Random forest model, temperature and relative humidity (RH) were identified as the most important factor, which mainly affected the severity of heat strokes. We quantified the meteorological threshold that affected the severity of heat strokes as well. Heat strokes may start to occur when temperature exceeds 36°C and RH exceeds 58% in China. The temperature of this threshold is higher in the south or low‐latitude region or coastal region of China. This work provides new insights for health research and help to timely alert the public in adverse weather conditions. Key Points: Internet search data could help to evaluate the health impact in large scale to address the data shortageIncreasing temperature and relative humidity (RH) led to sharply increased heat stroke, particularly when maximum temperature exceeds 36°C and RH exceeds 58%Meteorological threshold was affected by geographical factors like altitude, latitude and distance from ocean [ABSTRACT FROM AUTHOR]

Droughts and heatwaves are the most detrimental climatic threats to global wheat production, their spatiotemporal coexistence (compound drought and heatwave events [CDHEs]) can cause synergistic and amplified impacts on wheat yield, which call for an improved understating of their characteristics and variations that related to wheat growth. Past decade has witnessed a surge in the study of CDHEs in terms of their causative mechanisms, variabilities and impacts; however, changes in CDHEs occurring within crops' growing seasons are barely discussed, especially on global scale. In this study, we proposed a novel approach to identify and summarize CDHEs by taking "crop growing season" as accumulated period, and investigated the spatiotemporal changes of CDHEs occurring within wheat growing seasons over global wheat‐producing areas during 1981–2020, including their spatial extent, frequency and duration. Results show that the spatial extent of CDHEs experienced rapid expansion during wheat growing seasons of 1981–2020, meanwhile, droughts and heatwaves increasingly tended to occur simultaneously. More than 92% of wheat‐producing areas experienced at least one CDHE in each wheat growing season, the frequency of CDHEs increased significantly in 28.2% of wheat‐producing areas, and the total duration of CDHEs increased significantly in 33.2% of wheat‐producing areas. Europe, eastern China, western US and northern Argentina are the hotspot regions with the biggest contradiction between fast‐increasing CDHEs and wheat production, pointing to the urgency of marking spatially targeted adaptation measures for disaster reduction and risk management. [ABSTRACT FROM AUTHOR]

Polygonal salt crust patches (PSCPs) in modern playas have critical hydrologic implications for arid areas, but the morphology and origin of these polygonal features are under debate. This study investigated the structure and morphological characteristics of crustal landforms in a modern playa located in the West Juyan Lake, western Inner Mongolia of China, through an integrated analysis of high-resolution remote sensing images obtained from Google Earth, pedestrian field surveys, and unmanned aerial vehicle photography. The study area covers approximately 2,650 ha and the number of salt crust patches was 3,491. Across this area, the coverage and number of salt crust patches varied with elevation and sedimentary environment. The results show that the polygonal patch pattern of the salt crust landforms was fractal, and similar polygonal patch perimeter to area ratios and landscape index values prevail in the study area. The wind erosion of material on the surface of the Gobi Desert, a mountain torrent alluvial fan, and material carried by seasonal river water probably provided the provenance of the regional salt crust landforms. The structure and morphological characteristics of salt crust in typical playas of the arid and semiarid region are important for better understanding their composition and sedimentary environment. This study can help reveal relevant information regarding environmental change and provide a reference for saline dust emissions from playas in arid areas. [ABSTRACT FROM AUTHOR]

Spatiotemporal patterns of water stress caused by global warming has significantly affected gross primary productivity (GPP). However, its impact is hard to capture as the water stress of different timescales simultaneously influence GPP through the effects of time lag and legacy. As a result, synthetically considering the roles of water stress in the current year and previous years in GPP is very important for accurate modeling of GPP. In this study, we introduced the water stress indicators of standardized precipitation evapotranspiration index (SPEI) at different timescales, GPP observations from global flux network and the remote sensing‐based indexes to models of convolutional neural network (CNN). We built the optimal CNN model which effectively simulated the spatial patterns of GPP and detected their trends in interannual variation. The findings were as follows: (1) The CNN model with introduction of multi‐timescale SPEIs that reflect both current and previous years' water conditions improved the accuracy of modeled GPP. This result indicated that although GPP is most sensitive to current water conditions, it is also clearly affected by previous years' water conditions. (2) The optimal CNN model that considered previous years' water conditions not only aptly simulated the spatial distribution of GPP, but also showed advantages in simulating the interannual fluctuations of GPP and its response to drought. Ignoring the previous water conditions will underestimate the interannual fluctuations of GPP and the impact of drought on GPP. [ABSTRACT FROM AUTHOR]

Background: Quantifying the stock of soil organic carbon (SOC) and evaluating its potential impact factors is important to evaluating global climate change. Human disturbances and past climate are known to influence the rates of carbon fixation, soil physiochemical properties, soil microbial diversity and plant functional traits, which ultimately affect the current SOC storage. However, whether and how the paleoclimate and human disturbances affect the distribution of SOC storage on the high-altitude Tibetan Plateau remain largely unknown. Here, we took the Qinghai Plateau, the main component of the Tibetan Plateau, as our study region and applied three machine learning models (random forest, gradient boosting machine and support vector machine) to estimate the spatial and vertical distributions of the SOC stock and then evaluated the effects of the paleoclimate during the Last Glacial Maximum and the mid-Holocene periods as well as the human footprint on SOC stock at 0 to 200 cm depth by synthesizing 827 soil observations and 71 environmental factors. Results: Our results indicate that the vegetation and modern climate are the determinant factors of SOC stocks, while paleoclimate (i.e., paleotemperature and paleoprecipitation) is more important than modern temperature, modern precipitation and the human footprint in shaping current SOC stock distributions. Specifically, the SOC stock was deeply underestimated in near natural ecosystems and overestimated in the strongly human disturbance ecosystems if the model did not consider the paleoclimate. Overall, the total SOC stock of the Qinghai Plateau was underestimated by 4.69%, 12.25% and 6.67% at depths of 0 to 100 cm, 100 to 200 cm and 0 to 200 cm, respectively. In addition, the human footprint had a weak influence on the distributions of the SOC stock. We finally estimated that the total and mean SOC stock at 200 cm depth by including the paleoclimate effects was 11.36 Pg C and 16.31 kg C m−2, respectively, and nearly 40% SOC was distributed in the top 30 cm. Conclusion: The paleoclimate is relatively important for the accurate modeling of current SOC stocks. Overall, our study provides a benchmark for predicting SOC stock patterns at depth and emphasizes that terrestrial carbon cycle models should incorporate information on how the paleoclimate has influenced SOC stocks. [ABSTRACT FROM AUTHOR]

Land degradation induced by soil erosion is widespread in semiarid regions globally and is common in the agro–pastoral ecotone of northern China. Most researchers identify soil erosion by wind and water as independent processes, and there is a lack of research regarding the relative contributions of wind and water erosion and the interactions between them in what is referred to here as compound soil erosion (CSE). CSE may occur in situations where wind more effectively erodes a surface already subject to water erosion, where rainfall impacts a surface previously exposed by wind erosion, or where material already deposited by wind is subject to water erosion. In this paper, we use the Chinese Soil Loss Equation (CSLE) and the Revised Wind Erosion Equation (RWEQ) to calculate the rate of soil erosion and map the distribution of three types of soil erosion classified as (i) wind (wind-erod), (ii) water (water-erod), and (iii) CSE (CSE-erod) for the study area that spans more than 400,000 km2 of sand- and loess-covered northern China. According to minimum threshold values for mild erosion, we identify water-erod, wind-erod, and CSE-erod land as occurring across 41.41%, 13.39%, and 27.69% of the total area, while mean soil erosion rates for water-erod, wind-erod, and CSE-erod land were calculated as 6877.65 t km−2 yr−1, 1481.47 t km−2 yr−1, and 5989.49 t km−2 yr−1, respectively. Land subject to CSE-erod is predominantly distributed around the margins of those areas that experience wind erosion and water erosion independently. The CSLE and RWEQ do not facilitate a direct assessment of the interactions between wind and water erosion, so we use these equations here only to derive estimates of the relative contributions of wind erosion and water erosion to total soil erosion and the actual mechanisms controlling the interactions between wind and water erosion require further field investigation. It is concluded that CSE is an important but underappreciated process in semiarid regions and needs to be accounted for in land degradation assessments as it has substantial impacts on agricultural productivity and sustainable development in regions with sandy and/or loess-covered surfaces. [ABSTRACT FROM AUTHOR]

Floods are great threats to human life and property. Extensive research has investigated the spatiotemporal variation in flood occurrence, while few have studied the heterogeneity in global flood events of different sizes, which may require different coping strategies and risk reduction policies. In this study, we analysed the spatiotemporal patterns of global flood events with different affected areas (classified in three levels) during 1985–2019 and examined the contribution of different influencing factors to flood-induced mortality using Geodetector. The results show that (1) the increase in global flood frequency was mainly caused by Level II and Level III floods, and the average area affected by flood events has been increasing yearly since 1985. (2) In America and Africa, the frequency of Level III floods has increased monotonically. At the same time, the frequency of Level I floods in Europe and Level II floods in Asia has increased significantly. (3) For Europe and Asia, most of the deaths occurred with Level II floods; while for America and Africa, Level III floods caused the most mortality. (4) The top three factors contributing to the spatial heterogeneity in flood-induced mortality were the affected population, GDP per capita and flood duration. The contribution of each factor varied among the different types of floods. Topographic factors (percentage of mountainous area) magnified flood-induced mortality during extreme events with heavy rainfall, especially for Level III floods. The heterogeneity in flood frequency and flood-induced mortality indicates that flood protection measures should be more targeted. In addition, the increase in large-scale floods (Level III) highlights the need for transregional cooperation in flood risk management. [ABSTRACT FROM AUTHOR]

Within the hazard and disaster risk research field, explicitly treating carbon emissions as a hazard remains rather nascent. Applying hazard and disaster risk research perspectives to seek new insights on integrated mitigation and adaptation approaches and policy measures is equally elusive. Since China's pledge to achieve carbon neutrality by 2060, the "dual carbon" goals of carbon emission peaking and neutrality have stimulated nationwide attention, research, and policies and action plans. How to ensure that the transition pathways are on track and well-contextualized is one of the crucial challenges for policymakers and practitioners. This article examines the "risks" of missing the carbon neutrality goal at a regional scale in China, denoted as Carbon Emission Risk (CER). Carbon emissions (CE) as hazard, combined with the human socioeconomic system as exposure and human living environment, constitute the regional carbon emission environmental risk system. The "risks" of missing (or achieving) the carbon neutrality target for any region at any time, the article argues, is essentially determined by the ratio of CE to carbon absorption (CA, for uptake and removal). These variables are modified by a broadly defined "vulnerability coefficient" (Cv) that embodies both the potential for changes (decreasing CE and increasing CA), and the uncertainties of measuring CE and CA. Thus, the ratio of CE to CA is a measure of reality at any moment of time, whereas Cv indicates the overall propensity or capacity for moving the CE/CA ratio towards 1, that is, realizing carbon neutrality. Based on our calculation, CER at the provincial level in eastern China is higher than in western China. The article also calls for strengthening CER research and summarizes key measures for carbon emission risk governance. [ABSTRACT FROM AUTHOR]

Precise embolism control in immature brains can facilitate mechanistic studies of brain damage and repair after perinatal arterial ischemic stroke (PAIS), but it remains a technical challenge. Microhemorrhagic transformation is observed in one-third of infant patients who have suffered PAIS, but the underlying mechanism remains elusive. Building on an established approach that uses magnetic nanoparticles to induce PAIS, we develop a more advanced approach that utilizes magnetized erythrocytes to precisely manipulate de novo and in situ embolus formation and reperfusion in perinatal rodent brains. This approach grants spatiotemporal control of embolic stroke without any transarterial delivery of pre-formed emboli. Transmission electron microscopy revealed that erythrocytes rather than nanoparticles are the main material obstructing the vessels. Both approaches can induce microbleeds as an age-dependent complication; this complication can be prevented by microglia and macrophage depletion. Thus, this study provides an animal model mimicking perinatal embolic stroke and implies a potential therapeutic strategy for the treatment of perinatal stroke. SIMPLE and SIMPLeR are proposed as models for embolism, the latter reversibly manipulating magnetized red blood cells to occlude cerebral vessels. Both methods induce age-dependent micro-hemorrhage transformation, with microglia/macrophage depletion preventing hemorrhage transformation. [ABSTRACT FROM AUTHOR]

Climate change is often described as the average changes in temperature and precipitation; however, it is the change in climate extremes determines the levels of socioeconomic impacts related to climate change. It is generally believed that global warming drives increase in frequency, intensity and duration of precipitation extremes, but these changes vary regionally. Focusing on the relationships between evolution of extreme events and long‐term climate change, here we propose a novel classification scheme based on Kӧppen's system and changes in mean and variability of precipitation, divide the global climate into 20 different changing types and reveal the regional evolution of precipitation extremes. We find that precipitation extremes ascend significantly in wetting regions, especially in tropical and temperate zones, independent with changed variability. As for drying regions, the evolution of extremes is related to precipitation variability. An increase of extremes can still be detected in fluctuant‐drying areas, while a slight decrease can be seen in stabilized‐drying areas. It is surprising to find increase in both wetness and dryness extremes which implies higher intensity of meteorological hazards in densely populated areas. Based on the current and projected growth of population exposure to precipitation extremes, we identify some hotspots with high potential risk in the future. [ABSTRACT FROM AUTHOR]

Climate change is often described as the average changes in temperature and precipitation; however, it is the change in climate extremes determines the levels of socioeconomic impacts related to climate change. It is generally believed that global warming drives increase in frequency, intensity and duration of precipitation extremes, but these changes vary regionally. Focusing on the relationships between evolution of extreme events and long-term climate change, here we propose a novel classification scheme based on Köppen's system and changes in mean and variability of precipitation, divide the global climate into 20 different changing types and reveal the regional evolution of precipitation extremes. We find that precipitation extremes ascend significantly in wetting regions, especially in tropical and temperate zones, independent with changed variability. As for drying regions, the evolution of extremes is related to precipitation variability. An increase of extremes can still be detected in fluctuant-drying areas, while a slight decrease can be seen in stabilized-drying areas. It is surprising to find increase in both wetness and dryness extremes which implies higher intensity of meteorological hazards in densely populated areas. Based on the current and projected growth of population exposure to precipitation extremes, we identify some hotspots with high potential risk in the future. [ABSTRACT FROM AUTHOR]

Urbanization can be a challenge and an opportunity for earthquake risk mitigation. However, little is known about the changes in exposure (for example, population and urban land) to earthquakes in the context of global urbanization, and their impacts on fatalities in earthquake-prone areas. We present a global analysis of the changes in population size and urban land area in earthquake-prone areas from 1990 to 2015, and their impacts on earthquake-related fatalities. We found that more than two thirds of population growth (or 70% of total population in 2015) and nearly three quarters of earthquake-related deaths (or 307,918 deaths) in global earthquake-prone areas occurred in developing countries with an urbanization ratio (percentage of urban population to total population) between 20 and 60%. Holding other factors constant, population size was significantly and positively associated with earthquake fatalities, while the area of urban land was negatively related. The results suggest that fatalities increase for areas where the urbanization ratio is low, but after a ratio between 40 and 50% occurs, earthquake fatalities decline. This finding suggests that the resistance of building and infrastructure is greater in countries with higher urbanization ratios and highlights the need for further investigation. Our quantitative analysis is extended into the future using Shared Socioeconomic Pathways to reveal that by 2050, more than 50% of the population increase in global earthquake-prone areas will take place in a few developing countries (Pakistan, India, Afghanistan, and Bangladesh) that are particularly vulnerable to earthquakes. To reduce earthquake-induced fatalities, enhanced resilience of buildings and urban infrastructure generally in these few countries should be a priority. [ABSTRACT FROM AUTHOR]

Oxygen (O2) is the most abundant molecule in the atmosphere after nitrogen. Previous studies have documented that oxygen concentration remains nearly constant (20.946%) at all altitudes. Here we show for the first time that oxygen concentration varies significantly from earlier consensus and shows strong spatial and seasonal differences. Field observations on the Qinghai-Tibetan Plateau (QTP) indicate oxygen concentration of 19.94–20.66% (2018, n = 80), 19.98–20.78% (2019, n = 166) and 19.97–20.73% (2020, n = 176), all statistically different from earlier reports (p < 0.001) and are lower than the nearly constant. The mean oxygen concentration in summer (20.47%) is 0.31% higher than that of winter (20.16%) (n = 53) at identical locations in 2019, sampled in the Qilian Mountains, northwest QTP. We used LMG (The Lindeman, Merenda and Gold) method to estimate the relative contributions of altitude, air temperature and vegetation index (Fractional Vegetation Cover, FVC and Leaf Area Index, LAI) to oxygen concentration, which are 47%, 32% and 3% (FVC, R2 = 82%); 45%, 30% and 7% (LAI, R2 = 82%), respectively. These findings provide a new perspective for in-depth understanding on population risk in high altitude regions in the context of global climate change, to ensure the health and safety of residents and tourists in high altitude regions and promoting the stability, prosperity and sustainable development of high-altitude regions worldwide. [ABSTRACT FROM AUTHOR]

More than a year after its appearance and still rampant around the world, the COVID-19 pandemic has highlighted tragically how poorly the world is prepared to handle systemic risks in an increasingly hyper-connected global social-ecological system. The absence or clear inadequacy of global governance arrangements and mechanisms is painfully distinct and obvious. In this short article, we summarize a set of COVID-19 pandemic-related analyses and lessons that are inspired by Chinese practice. First, strong government response is one of the most important methods to control a pandemic. Second, countries should be concerned about human-to-frozen goods-to-human transmission. Third, sharing resources and experiences through cooperation is crucial to ensure an adequate health response. Based on these insights, we stress the critical importance of coordination and cooperation, and call for a global network to enhance integrated human health risk resilience. [ABSTRACT FROM AUTHOR]

A decline in mean near‐surface (10 m) wind speed has been widely reported for many land regions over recent decades, yet the underlying cause(s) remains uncertain. This study investigates changes in near‐surface wind speed over northern China from 1961 to 2016, and analyzes the associated physical mechanisms using station observations, reanalysis products and model simulations from the Community Atmosphere Model version 5.1 (CAM5). The homogenized near‐surface wind speed shows a significantly (p < 0.05) decline trend of −0.103 m s−1 decade−1, which stabilized from the 1990s onwards. Similar negative trends are observed for all seasons, with the strongest trends occurring in the central and eastern parts of northern China. Fast warming has occurred at high‐latitudes (i.e., >50°N) in recent decades, which has weakened the annual and seasonal meridional air temperature gradient (−0.33°C to −0.12°C dec−1, p < 0.05, except autumn) between these regions (50°–60°N, 75°–135°E) and the northern China zone (35°–45°N, 75°–135°E). This caused a significant (p < 0.05) decrease in annual and seasonal pressure gradient (−0.43 to −0.20 hPa dec−1) between the two zones, which contributed to the slowdown of winds. CAM5 simulations demonstrate that spatially uneven air temperature increases and near‐surface wind speed decreases over northern China can be realistically reproduced using the so‐called "all forcing" simulation, while the "natural only forcing" simulation fails to realistically simulate the uneven warming patterns and declines in near‐surface wind speed over most of northern China, except for summer. Key Points: Homogenized wind speed has significantly (p < 0.05) declined over northern China, while it stabilized from the 1990s onwardsUneven warming has weakened meridional air temperature and pressure gradient, which has induced the slowdown of winds over northern China"All radiative" forcing can reproduce uneven warming and wind speed decreases, while they cannot be simulated by "natural‐only" forcing [ABSTRACT FROM AUTHOR]

Extreme sea levels (ESLs) due to typhoon-induced storm surge threaten the societal security of densely populated coastal China. Uncertainty in extreme value analysis (EVA) for ESL estimation has large implications for coastal communities' adaptation to natural hazards. Here we evaluate uncertainties in ESL estimation and relevant driving factors based on hourly observations from 13 tide gauge stations and a complementary dataset derived from a hydrodynamic model. Results indicate significant uncertainties in ESL estimations stemming from using different EVA methods, which then propagate to the inundation assessment. Amplification factors due to sea-level rise (SLR) are highly sensitive to local relative SLR and the shape of the exceedance probability curve, which in turn depends on the selected EVA method. The hydrodynamic model hindcast indicates that high ESLs mainly occurred in eastern coastal China due to typhoon-induced storm surge. Larger uncertainties in the modelled ESLs are found for the coasts of the Yangtze River Delta, and particularly in the river mouth region. Future research and adaptation planning should prioritize these regions given expected future rising sea level, compound flood events, and human-induced factors (e.g. subsidence). This study provides theoretical and practical references for adaptation to ESL-related hazards along coastal China, with implications for coastal regions worldwide. [ABSTRACT FROM AUTHOR]

There has been increasing interest in understanding climate change impacts on crop yield stability, including interannual yield variability and lower yield extremes, in addition to mean yield. In this study, we evaluated these impacts on wheat yield and investigated the contribution of changes in climate mean and variability, and their interaction, on the North China Plain (NCP). Wheat yield simulation experiments with control groups were conducted using the Crop Environment Resource Synthesis (CERES) model, with multiple general circulation model ensembles under two representative concentration pathways (RCPs), namely 4.5 and 8.5. Climate change was projected to reduce mean yield by 15 and 17%, increase yield interannual variability by 5 and 11%, and reduce 10‐year return period lower yield extremes by 31 and 34% under RCPs 4.5 and 8.5, respectively. When analysed, changes in climate mean proved the main cause for changes in mean yield (62–71%), followed by the interactive changes in climate mean and variability (26–33%). As for the impact on yield variability, the interaction of the changes in climate mean and variability proved the main cause (48–54%), followed by changes in climate mean (33–41%). Surprisingly, climate change in variability contributed the least in both cases. Our results pertaining to the decrease in both availability and stability of wheat yield on the NCP presents a greater challenge for building a resilient food system for local areas than before. They also highlighted the importance of separating the impacts of changes in climate mean and variability on crop yield stability in a holistic framework, with particular attention paid to the tangible and interactive effects. [ABSTRACT FROM AUTHOR]