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Strong winds have evident impacts on the environment and the society. It can affect the dispersion of air pollutants, land erosion, and damage buildings, representing a severe hazard to people and properties. However, the changes and variabilities of extreme winds are still largely unknown, especially in global high-elevation regions, e.g., the Tibetan Plateau. This study analyses for the first-time changes in extreme wind speed over the Tibetan Plateau using homogenized near-surface daily maximum wind speed observations for 1973–2020. Results show that the daily maximum wind speed has significantly decreased in most stations during 1973–2020, with the largest decline in magnitude observed in spring. The frequency of daily maximum wind speed exceeding the 95% percentile shows a similar slowdown pattern. The detected decline is linked to large-scale atmospheric circulation, particularly to changes in the patterns of westerly and monsoon, which explain 35%~57% of daily maximum wind speed anomaly variations. Furthermore, this study reveals that changes in (a) geostrophic wind, (b) the instability of atmospheric thermal stratification, (c) vertical wind shear, and (d) Tibetan Plateau low vortex also contributes to the observed decreasing trends of daily maximum wind speed. [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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Our society has entered in an era of Anthropocene, in which people and their activities dominate almost all ecosystems on the planet. In the context of growing uncertainties, landscape sustainability science (LSS), as a place-based, use-inspired science, aims to understand and improve the dynamic relationship between ecosystem services and human well-being. In this editorial, we identify the major theoretical foundations of LSS, discuss recent innovations in research methodology to advance LSS, summarize the extension of LSS through landscape design and geo-design, and examine the application of LSS for addressing sustainability challenges across multiple landscapes. We highlight that long-term regional sustainability can only be achieved by integrating context-based sustainability across agricultural, urban, and natural landscapes so as to minimize the regional ecological footprint and make advancement towards achieving the sustainable development goals. [ABSTRACT FROM AUTHOR]

Crop phenology changes are important indicators of climate change. Climate change impacts on crop phenology are generally investigated through statistical analysis of the relationship between growth period length and growth period mean temperature. However, growth periods may be either earlier or later in a given year; hence, changes in mean temperature indicate both the effects of climate change and those attributable to seasonal temperature differences. Failure to consider temperature change resulting from seasonal shifts can lead to biased estimation of warming trends and their corresponding impact on phenology. We evaluated this potential bias in rice phenology change in 892 phenology series from China by applying time series regression control for phenological dates. The results indicate that the true magnitudes of climate change for early rice, late rice, and single rice are 0.20–0.56, 0.23–0.86, and 0.28–0.38 K/decade, after correction for the effects of seasonal shifts. The effects of seasonal shifts of growth periods led to underestimates of the magnitude of climate change by 0.16–0.22 and 0.05–0.08 K/decade for early rice and single rice, respectively, and an overestimate of the effect for late rice of 0.02–0.06 K/decade. Correspondingly, the net warming impacts on growth period length after correcting for the effects of seasonal shifts were − 2.7 d/K for early rice, − 4.8 d/K for late rice, and − 3.1 d/K for single rice, which were weaker for early and single rice, but stronger for late rice, relative to previous reports. Changes in growth period length were most closely associated with variation in phenological dates, while their relationship with climate change was less pronounced. Our results indicate that earlier phenological dates and prolonged-duration cultivars have been adopted to offset the impact of climate change, providing further evidence of active adaptation of rice cultivation practice to climate change in China. [ABSTRACT FROM AUTHOR]

Despite globalization and the scale of international food trade, access to sufficient food remains a major challenge in Africa. The most effective way to mitigate food insecurity is to increase crop production. To answer the question that whether African countries have the capacity to mitigate food shortages by best cultivating practices observed on current cropland, in this study, we use the local net primary productivity scaling (LNS) method to evaluate the currently attainable potential yield-gap (CAYgap). The CAYgap is initially used to suggest steps towards best regional agricultural practices and provide an indicator of regional divergence of cropland productivity in each homogeneous agro-climatic zone. Results indicate that under current climatic conditions, improving each countries' productivity to the zonal optimal level, around ~ 90% of all African countries have the capacity to mitigate their current energy shortages independently. Thus, to achieve ending hunger, possible efforts are needed which include (1) clarifying what and how socio-economic and institutional factors cause yield divergence across agro-climatic zones and establishing relevant practical policies; (2) strengthening the resilience of food access to make national food availability favors households and individuals; and (3) establishing systematically monitoring platforms on dynamics of crop yields from pixel to regional and from growth phrase to decadal scales. Furthermore, our study demonstrates the feasibility of applying satellite-derived indicators for the maximum yield achieved method to quantify and map the current cropland yield divergence by LNS method, and this method could be applied on different spatial level from regional to global scale with reasonable homogeneous zone scheme. [ABSTRACT FROM AUTHOR]

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (−2.59 to −15.89%). Followed by climatic fluctuations with a range of −2.60 to −4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (−2.11 to −12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable. [ABSTRACT FROM AUTHOR]

Hydrological and statistical models are playing an increasing role in hydrological forecasting, particularly for river basins with data of different temporal scales. In this study, statistical models, e.g. artificial neural networks, adaptive network-based fuzzy inference system, genetic programming, least squares support vector machine, multiple linear regression, were developed, based on parametric optimization methods such as particle swarm optimization (PSO), genetic algorithm (GA), and data-preprocessing techniques such as wavelet decomposition (WD) for river flow modelling using daily streamflow data from four hydrological stations for a period of 1954-2009. These models were used for 1-, 3- and 5-day streamflow forecasting and the better model was used for uncertainty evaluation using bootstrap resampling method. Meanwhile, a simple conceptual hydrological model GR4J was used to evaluate parametric uncertainty based on generalized likelihood uncertainty estimation method. Results indicated that: (1) GA and PSO did not help improve the forecast performance of the model. However, the hybrid model with WD significantly improved the forecast performance; (2) the hybrid model with WD as a data preprocessing procedure can clarify hydrological effects of water reservoirs and can capture peak high/low flow changes; (3) Forecast accuracy of data-driven models is significantly influenced by the availability of streamflow data. More human interferences from the upper to the lower East River basin can help to introduce greater uncertainty in streamflow forecasts; (4) The structure of GR4J may introduce larger parametric uncertainty at the Longchuan station than at the Boluo station in the East river basin. This study provides a theoretical background for data-driven model-based streamflow forecasting and a comprehensive view about data and parametric uncertainty in data-scarce river basins. [ABSTRACT FROM AUTHOR]

Context: During the past three decades, China’s agroecosystem has undergone dramatic alterations because of changes in climatic and management factors, which threatened agricultural sustainability.Objectives: We investigated how climatic and management factors affected agricultural ecosystem services (AES).Methods: We adopted the GIS-based Environmental Policy Integrated Climate (EPIC) model to simulate the five critical AES: food production, soil organic carbon (SOC), nitrate leaching, water erosion, and wind erosion from 1980 to 2010 and used a partial least square regression model to quantify the contributions of the drivers of the variation in the AES on the main grain-producing area (MGPA), climatic zone, and national scales.Results: On the MGPA scale, SOC exhibited no obvious change and food production increased, whereas the negative environmental effects largely increased. The MGPA is important to ensure the safety of China’s food supply. At the climatic zone scale, food production and SOC increased, water erosion in the tropical-subtropical monsoonal zone and water and wind erosion in the temperate monsoonal zone decreased, whereas N leaching, water erosion, and wind erosion increased in other climate zones. At the national scale, food production, SOC, N leaching, and wind erosion increased, whereas water erosion decreased. The crop cultivated area played a major role in the effect on food production and SOC. The dominant factors for N leaching, water erosion, and wind erosion varied with crop type and study scales.Conclusions: Adjustment of agricultural management measures is vital and possible to minimize the tradeoffs, increase the synergies among agro ecosystem services, and promote adaptation to the changing climate. [ABSTRACT FROM AUTHOR]

Analysis of casualties due to landslides from 2000 to 2012 revealed that their spatial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide casualty events in southern China than in northern China. Hotspots of landslide-generated casualties were in the western Sichuan mountainous area and Yunnan-Guizhou Plateau region, southeast hilly area, northern part of the loess hilly area, and Tianshan and Qilian Mountains. However, local distribution patterns indicated that landslide casualty events were also influenced by economic activity factors. To quantitatively analyse the influence of natural environment and human-economic activity factors, the Probability Model for Landslide Casualty Events in China (LCEC) was built based on logistic regression analysis. The results showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density were positively correlated with casualties caused by landslides. Notably, GDP growth rate ranked only second to relative relief as the primary factors in the probability of casualties due to landslides. The occurrence probability of a landslide casualty event increased 2.706 times with a GDP growth rate increase of 2.72%. In contrast, vegetation coverage was negatively correlated with casualties caused by landslides. The LCEC model was then applied to calculate the occurrence probability of landslide casualty events for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events. The 27 counties were divided into three categories: poverty-stricken counties, mineral-rich counties, and real-estate overexploited counties; these are key areas that should be emphasized in reducing landslide risk. [ABSTRACT FROM AUTHOR]

Using daily precipitation data from 25 meteorological stations for a period of 1961-2014, spatiotemporal features of wet spells and droughts and related impacts on agricultural production across Anhui province, China, were investigated with a linear regressive technique, the Standardized Precipitation Evapotranspiration Index (SPEI) and the modified Mann-Kendall trend test method. Results indicated that: (1) ENSO-induced wet spells and droughts accounted for 83 and 68% of the total wet spells and droughts and droughts were closely related to La Nina events of the same and subsequent years. Wet spells, however, were closely related to El Niño events; (2) a larger variability was found in the SPEI, showing larger flood and drought risks during spring and autumn than those during summer and winter seasons. Generally, wet spells in winter were relatively high and the drying tendency was identified in winter during recent years; (3) relations between SPEI and SSTA were shifting during warm and cold phases of ENSO. The warm phase of ENSO tended to have larger impacts on SPEI in southern Anhui province, and the cold phase of ENSO had a greater impact on the SPEI variation in northern Anhui province. Comparatively, SSTA had an increasing impact on wet spells and droughts with increasing lag time; and (4) the reduction of rice and maize production in southern Anhui province was found mainly during 1 year earlier to the ENSO events. The amount of reduction of maize was larger in northern Anhui province and Jianghuai region, years with maize reduction were more often in southern Anhui province. Irrigation in central Anhui province can mitigate the negative effects of wet spells and droughts. [ABSTRACT FROM AUTHOR]