A global transition to flash droughts under climate change

Three-dimensional ecological drought identification and evaluation method considering eco-physiological status of terrestrial ecosystems

Ecological drought is a complex process in terrestrial ecosystems where vegetation's eco-physiological functions are impaired due to water stress. However, there is currently a lack of long-term assessment of ecological drought from an eco-physiological perspective. In this study, the standardized ecological drought index (SESNDI) was developed using actual evaporation, root soil moisture, and kernel normalized difference vegetation index via the Euclidean distance method, reflecting ecosystem physiology, water supply capacity, and vegetation status. Solar-induced chlorophyll fluorescence validated SESNDI by reflecting vegetation photosynthesis. Using China as an example, severely impacted by climate change and ecological restoration, ecological drought's spatio-temporal variation and propagation characteristics was evaluated using clustering algorithms. The results demonstrated that (1) SESNDI showed superior performance over several other drought indices. (2) During 1982-2020, ecological drought was prevalent from 1990 to 2010, especially in the central and northeastern regions. (3) Compared to 1982-2000, the median duration and affected area of ecological drought events during 2001-2020 reduced by four months and 1.51 × 105 km2, respectively, while the median intensity increased by 0.06. (4) Decreased precipitation and increased temperature were the primary factors contributing to the frequent occurrence of ecological drought in China from 1990 to 2010. This study offers a crucial methodology for evaluating ecological drought, serving as a reference for developing effective terrestrial restoration strategies.

Observed flash drought to persist in future over southern Africa

Southern Africa has experienced multiple occurrences of drought episodes, which is projected to persist in the future, considering all climate scenarios. Despite the documented change in a meteorological, agricultural, and hydrological drought situation in the region, few studies are yet to explore the changes in flash drought (hereafter; FD), which is characterized by a rapid reduction in root-zone soil moisture and more substantial intensification in few days to weeks. Here, we analyze the observed FD and related underlying drivers during the past 34 years. Also, we estimate the future changes in FD using the severity-duration magnitude matrix under the middle of the road (SSP2-4.5) and business as usual (SSP5-8.5), scenario. Lastly, the study investigates the role of anthropogenic warming using the fraction of attributable risk (FAR) approach and possible bivariate return periods of FD events. Our results demonstrate that the region has experienced multiple occurrences up to 72 pentads from 1980 to 2014. Underlying mechanisms revealed the compounding influence of Vapor Pressure Deficit (VPD), Potential Evapotranspiration (PET), and precipitation deficit that have a significant impact on the abrupt onset and rapid intensification of FD events and other hot extremes over the SAF region. Under a high emission scenario, the region will experience FD duration lasting for 30 days with >40 % severity projected to impact the region. Anthropogenic climate change and land use and land cover changes remain the most dominant drivers altering the FD events over the SAF region. The return period of FD events under the SSP5-8.5 scenario shows that the SAF region will witness multiple FD events of up to 80 pentads in the far future. These findings reinforce the need to limit the emission of greenhouse gases. Sustained warming of the climate will exacerbate the extreme events and other compounding factors, thus affecting the livelihoods of humans and life-supporting strata.

Protists and fungi: Reinforcing urban soil ecological functions against flash droughts

Rising instances of flash droughts are contributing to notable variability in soil moisture across terrestrial ecosystems. These phenomena challenge urban ecosystem services, yet the reaction of soil ecological functions (SEFs) to such events is poorly understood. This study investigates the responses of SEFs (about nutrient metabolism capacity and potential) and the microbiome under two specific scenarios: a flooding-drought sequence and a direct drought condition. Using quantitative microbial element cycling analysis, high-throughput sequencing, and enzyme activity measurements, we found that unlike in forests, the microbial composition in urban soils remained unchanged during flash drought conditions. However, SEFs were affected in both settings. Correlation analysis and Mantel test showed that forest soils exhibited more complex interactions among soil moisture, properties, and microbial communities. Positive linear correlation revealed that bacteria were the sole drivers of SEFs. Interestingly, while multi-threshold results suggested bacterial α diversity impeded the maximization of SEFs in urban soils, fungi and protists had a beneficial impact. Cross-domain network of urban soils had higher number of nodes and edges, but lower average degree and robustness than forest soils. Mantel test revealed that fungi and protist had significant correlations with bacterial composition in forest soils, but not in urban soils. In the urban network, the degree and eigenvector centrality of bacterial, fungal and protistan ASVs were significantly lower compared to those in the forest. These results suggest that the lower robustness of the microbial network in urban soils is attributed to limited interactions among fungi, consumer protists, and bacteria, contributing to the failure of microbial-driven ecological functions. Overall, our findings emphasize the critical role of fungi and protists in shielding urban soils from drought-induced disturbances and in enhancing the resistance of urban ecological functions amidst environmental changes.

Drought reduces nitrogen supply and N2O emission in coastal bays

Severe droughts are increasingly prevalent under global climate change, disrupting watershed hydrology and coastal nitrogen cycling. However, the specific effects of drought on nitrogen transport from land to sea and subsequent nitrogen dynamics remain inadequately understood. In this study, we evaluated the consequences of the 2020-2022 drought on nitrogen supply and N2O emissions in Xiamen Bay, Southeast China. The results showed that drought significantly reduced annual NH4N, NO2N, and NO3N concentrations in Xiamen Bay by 49.4 %, 32.1 %, and 40.3 %, respectively, compared with the pre-drought year of 2019. The decline in NH4N concentration was mainly attributed to reduced surface runoff across all seasons. NO3N and NO2N concentrations declined only during spring and summer, primarily due to increased potential evapotranspiration (PET) hindering nitrogen supply via groundwater and concurrently enhancing land denitrification. Annual N2O emission from Xiamen Bay decreased by 40.0∼72.7 % during the drought, highly correlated with the decline in the concentrations of NO3N, DIN, and DTN (p < 0.001). Comparative analysis revealed that NO3N concentration exhibited consistent negative linear regressions with PET and declined as evaporative demand drought conditions worsened across Xiamen Bay, Sansha Bay, and Chesapeake Bay throughout 2010-2022. NH4N concentration showed a positive regression with river discharge in Xiamen Bay, but negative regressions in the other two bays. Our results indicates that drought reduces N2O emission primarily driven by nitrate substrate reduction in the bay. This study provides new insights for predicting coastal nitrogen dynamics and greenhouse gas emissions under global environmental change.

A global flash drought inventory based on soil moisture volatility

Flash droughts, characterized by rapid onset and development, present significant challenges to agriculture and climate mitigation strategies. Operational drought monitoring systems, based on precipitation, soil moisture deficits, or temperature anomalies, often fall short in timely detection of these events, underscoring the need for customized identification and monitoring indices that account for the rapidity of flash drought onset. Recognizing this need, this paper introduces a global flash drought inventory from 1990 to 2021 derived using the Soil Moisture Volatility Index (SMVI). Our work expands the application of the SMVI methodology, previously focused on the United States, to a global scale, providing a tool for understanding and predicting these rapidly developing phenomena. The dataset encompasses detailed event characteristics, including onset, duration, and severity, across diverse climate zones. By integrating atmospheric variables through their impact on soil moisture, the inventory offers a platform for analyzing the drivers and impacts of flash droughts, and serves as a large, consistent dataset for use in training and evaluating flash drought prediction models.

Key microbial taxa play essential roles in maintaining soil muti-nutrient cycling following an extreme drought event in ecological buffer zones along the Yangtze River

Climatic extremes, especially extreme droughts, are occurring more frequently and profoundly impacting biogeochemical processes. However, the relative importance of microbial communities on soil nutrient cycling and community maintenance under natural extreme drought events remains elusive. During a record-breaking drought in the Yangtze River Basin (YRB) in the summer of 2022, we collected ambient soils and drought-affected bare and vegetated soils in ecological buffer zones from two sites with similar soil and vegetation characteristics along the YRB, and examined the relative contribution of soil bacterial communities in supporting multi-nutrient cycling index (MNCI) involving carbon-, nitrate- and phosphorus-cycling and their associations with microbial network. Extreme drought decreased (p < 0.05) bacterial α-diversity but increased MNCI in vegetated soils at both sites, while both remained unchanged (p > 0.05) in bare soils, possibly as a result of vegetation releasing rhizodeposits under drought which selectively recruited bacterial communities. Bacterial community compositions were shifted (p < 0.05) only in vegetated soils, and they exerted more influence than α-diversity on soil MNCI. Notably, the Anaerolineae, identified as a biomarker enriched in vegetated soils, had close associations with enzyme activities and soil MNCI at both sites, suggesting their potential recruitment by vegetation to withstand drought. Furthermore, key ecological clusters (Module 1) in bacterial co-occurrence networks at both sites supported (p < 0.05) higher MNCI, despite no substantial variation in network structure due to drought. Specifically, the most important taxa within Module 1 for predicting soil MNCI revealed by random forest modeling analysis (R2 = 0.44 - 0.63, p < 0.001), such as B1-7BS, SBR1031 and Nocardioides, could be deeply involved in soil nitrogen-cycling, suggesting an essential role of specialized interactions of bacterial communities in maintaining soil multifunctionality. Overall, this study demonstrates that changes in biomarkers and functional taxa under extreme drought may better reflect the biological mechanisms involved in microbial communities impacting ecosystem function, which may aid in forecasting the ecological consequences of ongoing climate change in the ecological buffer zones along the YRB.

Intra-growing season dry-wet spell pattern is a pivotal driver of maize yield variability in sub-Saharan Africa

Climate variability plays a crucial role in the annual fluctuations of crop yields, posing a substantial threat to food security. Maize, the main cereal in sub-Saharan Africa, has shown varied yield trends during increasingly warmer growing seasons. Here we explore how sub-seasonal dry-wet spell patterns contribute to this variability, considering the spatial heterogeneity of crop responses, to map weather-related risks at a regional level. Our results show that shifts in specific dry-wet spell patterns across growth stages influence maize yield fluctuations in sub-Saharan Africa, explaining up to 50-60% of the interannual variation, which doubles that explained by mean changes in precipitation and temperature (30-35%). Precipitation primarily drives the onset of dry spells, while the influence of temperature increases with event intensity and peaks at the start of the growing season. Our large-scale, data-limited analysis approach has the potential to inform climate-smart agriculture in developing regions.

Anthropogenic amplification of precipitation variability over the past century

As the climate warms, the consequent moistening of the atmosphere increases extreme precipitation. Precipitation variability should also increase, producing larger wet-dry swings, but that is yet to be confirmed observationally. Here we show that precipitation variability has already grown globally (over 75% of land area) over the past century, as a result of accumulated anthropogenic warming. The increased variability is seen across daily to intraseasonal timescales, with daily variability increased by 1.2% per 10 years globally, and is particularly prominent over Europe, Australia, and eastern North America. Increased precipitation variability is driven mainly by thermodynamics linked to atmospheric moistening, modulated at decadal timescales by circulation changes. Amplified precipitation variability poses new challenges for weather and climate predictions, as well as for resilience and adaptation by societies and ecosystems.

Case study on climate change effects and food security in Southeast Asia

Agriculture, a cornerstone of human civilization, faces rising challenges from climate change, resource limitations, and stagnating yields. Precise crop production forecasts are crucial for shaping trade policies, development strategies, and humanitarian initiatives. This study introduces a comprehensive machine learning framework designed to predict crop production. We leverage CMIP5 climate projections under a moderate carbon emission scenario to evaluate the future suitability of agricultural lands and incorporate climatic data, historical agricultural trends, and fertilizer usage to project yield changes. Our integrated approach forecasts significant regional variations in crop production across Southeast Asia by 2028, identifying potential cropland utilization. Specifically, the cropland area in Indonesia, Malaysia, Philippines, and Viet Nam is projected to decline by more than 10% if no action is taken, and there is potential to mitigate that loss. Moreover, rice production is projected to decline by 19% in Viet Nam and 7% in Thailand, while the Philippines may see a 5% increase compared to 2021 levels. Our findings underscore the critical impacts of climate change and human activities on agricultural productivity, offering essential insights for policy-making and fostering international cooperation.

Modeling the dynamic impacts of maritime network blockage on global supply chains

Recent phenomena such as pandemics, geopolitical tensions, and climate change-induced extreme weather events have caused transportation network interruptions, revealing vulnerabilities in the global supply chain. A salient example is the March 2021 Suez Canal blockage, which delayed 432 vessels carrying cargo valued at $92.7 billion, triggering widespread supply chain disruptions. Our ability to model the spatiotemporal ramifications of such incidents remains limited. To fill this gap, we develop an agent-based complex network model integrated with frequently updated maritime data. The Suez Canal blockage is taken as a case study. The results indicate that the effects of such blockages go beyond the directly affected countries and sectors. The Suez Canal blockage led to global losses of about $136.9 ($127.5-$147.3) billion, with India suffering 75% of these losses. Global losses show a nonlinear relationship with the duration of blockage and exhibit intricate trends post blockage. Our proposed model can be applied to diverse blockage scenarios, potentially acting as an early-alert system for the ensuing supply chain impacts. Furthermore, high-resolution daily data post blockage offer valuable insights that can help nations and industries enhance their resilience against similar future events.

A CAM-Related NF-YB Transcription Factor Enhances Multiple Abiotic Stress Tolerance in Arabidopsis

Abiotic stresses often occur simultaneously, and the tolerance mechanisms of plants to combined multiple abiotic stresses remain poorly studied. Extremophytes, adapted to abiotic stressors, might possess stress-adaptive or -responsive regulators that could enhance multiple abiotic stress resistance in crop plants. We identified an NF-YB transcription factor (TF) from the heat-tolerant obligate Crassulacean acid metabolism (CAM) plant, Kalanchoe fedtschenkoi, as a potential regulator of multiple abiotic stresses. The KfNF-YB3 gene was overexpressed in Arabidopsis to determine its role in multiple abiotic stress responses. Transgenic lines exhibited accelerated flowering time, increased biomass, larger rosette size, higher seed yield, and more leaves. Transgenic lines had higher germination rates under combined NaCl, osmotic, and water-deficit stress treatments compared to control plants. They also showed enhanced root growth and survival under simultaneous NaCl, osmotic, water-deficit, and heat stress conditions in vitro. Interestingly, potted transgenic lines had higher survival rates, yield, and biomass under simultaneous heat, water-deficit, and light stresses compared to control plants. Altogether, these results provide initial insights into the functions of a CAM-related TF and its potential roles in regulating multiple abiotic stress responses. The CAM abiotic stress-responsive TF-based approach appears to be an ideal strategy to enhance multi-stress resilience in crop plants.

Catalogue of drought events in peninsular Spanish along 1916-2020 period

We leveraged the most extensive and detailed gridded database of monthly precipitation data across the Spanish mainland (MOPREDAScentury), encompassing 1916-2020 time period, to pinpoint the most severe drought events within this timeframe and analyse their spatio-temporal dynamics. To identify these events, we employed the Standardized Precipitation Index (SPI) at a 12-month timescale. Drought events were identified as periods of at least three months where significantly dry conditions affected 20% or more of the study area, defined as grid cells with SPI values lower than -0.84. Our analysis revealed a total of 40 major drought events. Our catalogue contains detailed information on each episode's spatial extent, duration, severity, and spatio-temporal dynamics. The analysis of the propagation patterns of the events unveils substantial heterogeneity, implying that droughts stem from diverse atmospheric mechanisms, further influenced by complex local topography. The open-licensed drought database serves as a valuable resource. It not only facilitates exploration of drought onset and evolution mechanisms but also aids in assessing drought impact on agricultural and other socio-economic sectors.

A review of social-ecological system vulnerability in desertified regions: Assessment, simulation, and sustainable management

Desertified regions face considerable vulnerability due to the combined effects of climate change and human activities, which threaten regional ecological security and societal development. It is therefore necessary to assess, simulate, and manage the vulnerability of desertified regions from the perspective of the social-ecological system, to support desertification control and sustainable development. This study is a systematic review of the vulnerability of the social-ecological system in desertified regions (SESDR) based on a bibliometric analysis, and a summary of the research progresses in vulnerability assessment, simulation, and sustainable management is provided. It was found that SESDR vulnerability research started relatively late, but has developed rapidly in recent years, with an emphasis on the coupling between natural systems and human activities, and multi-scale interactions and dynamics. Using various indicators at different scales, SESDR vulnerability could be assessed in terms of exposure, sensitivity, and adaptability. Modeling the complex interactions among natural and human factors across multiple scales is essential to simulate the vulnerability dynamics of the SESDR. The sustainable management of SESDR vulnerability focuses on rational spatial planning to achieve the maximum benefits, with the right measures in the right places. Four priority research directions were proposed to develop a better understanding of the mechanisms of vulnerability and smart restoration of desertified land. The findings of this study will enable researchers, land managers, and policymakers to develop a more comprehensive understanding of SESDR vulnerability, thereby enabling them to better address the challenges posed by complex resource and environmental issues.

Understanding the effects of flash drought on vegetation photosynthesis and potential drivers over China

Flash droughts characterized by rapid onset and intensification are expected to be a new normal under climate change and potentially affect vegetation photosynthesis and terrestrial carbon sink. However, the effects of flash drought on vegetation photosynthesis and their potential dominant driving factors remain uncertain. Here, we quantify the susceptibility and response magnitude of vegetation photosynthesis to flash drought across different ecosystems (i.e., forest, shrubland, grassland, and cropland) in China based on reanalysis and satellite observations. By employing the extreme gradient boosting model, we also identify the dominant factors that influence these flash drought-photosynthesis relationships. We show that over 51.46 % of ecosystems across China are susceptible to flash drought, and grasslands are substantially suppressed, as reflected in both sensitivity and response magnitude (with median gross primary productivity anomalies of -0.13). We further demonstrate that background climate differences (e.g., mean annual temperature and aridity) predominantly regulate the response variation in forest and shrubland, with hotter/colder or drier ecosystems being more severely suppressed by flash drought. However, in grasslands and croplands, the differential vegetation responses are attributed to the intensity of abnormal hydro-meteorological conditions during flash drought (e.g., vapor pressure deficit (VPD) and temperature anomalies). The effects of flash droughts intensify with increasing VPD and nonmonotonically relate to temperature, with colder or hotter temperatures leading to more severe vegetation loss. Our results identify the vulnerable ecological regions under flash drought and enable a better understanding of vegetation photosynthesis response to climate extremes, which may be useful for developing effective management strategies.

Hydrological response of drought impacts across catchments worldwide

Drought will inevitably affect linkages between different water components, which have previously been investigated across different spatiotemporal scales. Elucidating drought-induced precipitation (P) partition effects remain uncertain because they involve drought propagation, even inducing streamflow (Q) non-stationarity. This study collected data on 1069 catchments worldwide to investigate Q and evapotranspiration (ET) impacts from P deficit-derived reductions in drought propagation. Results show that P deficits trigger soil moisture drought, subsequently inducing negative Q and ET anomalies that vary under different climate regimes. Generally, drought-induced hydrological legacies indicate that breaks in hydrological linkages cause a relatively rapid Q response (i.e., negative Q anomaly), amplified by drought strength and duration. Compared with the Q response, the ET response to drought stress involves a more complex, associative vegetation response and an associative evaporative state controlled by water and energy, which lags behind the Q response and can also intensify with increasing drought severity and duration. This is confirmed by the ET response under different climate regimes. Namely, in drier climates, a positive ET anomaly can be detected in its early stages, this is unusual in wetter climate. Additionally, Q and ET sensitivity to drought strength can be mechanistically explained by the water and energy status. This implies that ET is mainly controlled by water and energy, resulting in higher and lower drought sensitivity within water- and energy-limited regions, respectively. Understanding the impacts of drought on Q and ET response is essential for identifying key linkages in drought propagation across different climate regimes. Our findings will also be useful for developing early warning and adaptation systems that support both human and ecosystem requirements.

Tree-ring widths of Pinus tabulaeformis Carr reveal variability of winter half-year precipitation on the north-south transition zone in central China over the past 220 years

Long-term, high-resolution regional drought records contribute to understanding the impacts of drought on environmental and social systems in central China. Here, we develop a regional tree-ring width chronology of Pinus tabulaeformis Carr from the northern slope of Funiu Mountains on the north-south transition zone in central China. Monthly correlation analyses showed that temperature and humidity in current May and June are main limiting factors on tree growth. Despite that, the highest correlation with tree growth was found to be precipitation from previous December to current June (PreDJ, 0.718, p < 0.001), which was chosen for reconstruction. The reconstructed PreDJ revealed six drought periods and five wet periods over the past 220 years, and the recent dry spell would likely to continue. Spectral analyses indicated that the reconstructed PreDJ was closely related to the El Nino-Southern Oscillation (ENSO, 2-7a) and 35a climatic oscillation of Bruckner, and was also affected by the Quasi-Biennial Oscillation (QBO). Wavelet analyses showed that the quasi-cycle of 2-7a persisted over the past 220 years and strengthened after the 1980s, and the QBO signals appeared from the 1860s to 1970s and wear off thereafter, and 35a cycle only appeared during 1820-1920. Spatial analysis found that the reconstructed PreDJ had good spatial representation of precipitation in the central-eastern China. Therefore, the results of this study provide reliable information for understanding long-term drought impacts on environmental conditions and socioeconomic development in central China.

Revisiting the hydrological legacy of revegetation on China's Loess Plateau using Eagleson's ecohydrological perspective

Revegetation has resulted in a trend of increasing vegetation greenness on the Chinese Loess Plateau. However, it remains unclear whether the regional vegetation coverage exceeds hydroclimatic limitations in the context of revegetation, and the hydrological effects of greening are controversial. Eagleson's optimality hypothesis can explain some of the hydrological effects on the Loess Plateau. Here, building on previous research, the geospatial vegetation states were estimated for pre- and post-revegetation periods on the Loess Plateau from 1982 to 2015 using Eagleson's ecological optimality theory. Additionally, a drought composite analysis approach was utilized to investigate the hydrological effects related to drought (including sensitivity and partitioning) under various vegetation states. It was found that revegetation increased the proportion of catchments in the equilibrium state and decreased the proportion in the disturbed state, owing to a wetter climate compared with the pre-revegetation period. Root-zone soil drought, driven by precipitation (P) deficit, asymmetrically triggered hydrological effects for both the pre- and post-revegetation periods, with reduced runoff (Q) for both periods and a decrease in evapotranspiration (ET) during the pre-revegetation period but an increase in ET during the post-revegetation period. Moreover, catchments in an equilibrium state exhibited lower sensitivity between ET and P, and more stable partitioning of ET with regards to P, compared with those in a disturbed state. These results underscore the theoretical framework that an equilibrium state is crucial for maintaining ecosystem ET. Our results highlight the necessity of considering the hydrologic regulation of vegetation states when assessing the hydrological effects of vegetation change.

Consistent time allocation fraction to vegetation green-up versus senescence across northern ecosystems despite recent climate change

Extended growing season lengths under climatic warming suggest increased time for plant growth. However, research has focused on climatic impacts to the timing or duration of distinct phenological events. Comparatively little is known about impacts to the relative time allocation to distinct phenological events, for example, the proportion of time dedicated to leaf growth versus senescence. We use multiple satellite and ground-based observations to show that, despite recent climate change during 2001 to 2020, the ratio of time allocated to vegetation green-up over senescence has remained stable [1.27 (± 0.92)] across more than 83% of northern ecosystems. This stability is independent of changes in growing season lengths and is caused by widespread positive relationships among vegetation phenological events; longer vegetation green-up results in longer vegetation senescence. These empirical observations were also partly reproduced by 13 dynamic global vegetation models. Our work demonstrates an intrinsic biotic control to vegetation phenology that could explain the timing of vegetation senescence under climate change.

Seedling root system adaptation to water availability during maize domestication and global expansion

The maize root system has been reshaped by indirect selection during global adaptation to new agricultural environments. In this study, we characterized the root systems of more than 9,000 global maize accessions and its wild relatives, defining the geographical signature and genomic basis of variation in seminal root number. We demonstrate that seminal root number has increased during maize domestication followed by a decrease in response to limited water availability in locally adapted varieties. By combining environmental and phenotypic association analyses with linkage mapping, we identified genes linking environmental variation and seminal root number. Functional characterization of the transcription factor ZmHb77 and in silico root modeling provides evidence that reshaping root system architecture by reducing the number of seminal roots and promoting lateral root density is beneficial for the resilience of maize seedlings to drought.

A daily gap-free normalized difference vegetation index dataset from 1981 to 2023 in China

Long-term, daily, and gap-free Normalized Difference Vegetation Index (NDVI) is of great significance for a better Earth system observation. However, gaps and contamination are quite severe in current daily NDVI datasets. This study developed a daily 0.05° gap-free NDVI dataset from 1981-2023 in China by combining valid data identification and spatiotemporal sequence gap-filling techniques based on the National Oceanic and Atmospheric Administration daily NDVI dataset. The generated NDVI in more than 99.91% of the study area showed an absolute percent bias (|PB|) smaller than 1% compared with the original valid data, with an overall R2 and root mean square error (RMSE) of 0.79 and 0.05, respectively. PB and RMSE between our dataset and the MODIS daily gap-filled NDVI dataset (MCD19A3CMG) during 2000 to 2023 are 7.54% and 0.1, respectively. PB between our dataset and three monthly NDVI datasets (i.e., GIMMS3g, MODIS MOD13C2, and SPOT/PROBA) are only -5.79%, 4.82%, and 2.66%, respectively. To the best of our knowledge, this is the first long-term daily gap-free NDVI in China by far.

Application of a hybrid algorithm of LSTM and Transformer based on random search optimization for improving rainfall-runoff simulation

Flood forecasting using traditional physical hydrology models requires consideration of multiple complex physical processes including the spatio-temporal distribution of rainfall, the spatial heterogeneity of watershed sub-surface characteristics, and runoff generation and routing behaviours. Data-driven models offer novel solutions to these challenges, though they are hindered by difficulties in hyperparameter selection and a decline in prediction stability as the lead time extends. This study introduces a hybrid model, the RS-LSTM-Transformer, which combines Random Search (RS), Long Short-Term Memory networks (LSTM), and the Transformer architecture. Applied to the typical Jingle watershed in the middle reaches of the Yellow River, this model utilises rainfall and runoff data from basin sites to simulate flood processes, and its outcomes are compared against those from RS-LSTM, RS-Transformer, RS-BP, and RS-MLP models. It was evaluated against RS-LSTM, RS-Transformer, RS-BP, and RS-MLP models using the Nash-Sutcliffe Efficiency Coefficient (NSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Bias percentage as metrics. At a 1-h lead time during calibration and validation, the RS-LSTM-Transformer model achieved NSE, RMSE, MAE, and Bias values of 0.970, 14.001m3/s, 5.304m3/s, 0.501% and 0.953, 14.124m3/s, 6.365m3/s, 0.523%, respectively. These results demonstrate the model's superior simulation capabilities and robustness, providing more accurate peak flow forecasts as the lead time increases. The study highlights the RS-LSTM-Transformer model's potential in flood forecasting and the advantages of integrating various data-driven approaches for innovative modelling.

Effects of different hydrological conditions on the taxonomic structure and functional traits of mollusk communities in a large floodplain wetland

Floodplain wetlands are critical to the conservation of aquatic biodiversity and the ecological integrity of river networks. However, increasing drought severity and frequency caused by climate change can reduce floodplain wetlands' resistance and recovery capacities. Mollusks, which are common inhabitants of floodplain wetlands, are among the most vulnerable species to drought. However, the response of mollusk communities to drought has received little attention. Here, we investigated how the structure and functional traits of mollusk communities changed in response to varying hydrological conditions, including a flash drought (FD) in the Poyang Lake floodplain wetland. Our findings showed that FD strongly reduced mollusk abundance and biomass, decreased both α- and β-diversity, and resulted in the extinction of bivalve taxa. A sudden shift in community trait structure was discovered due to the extinction of many species. These traits, which include deposit feeding, crawling, scraping, aerial respiration, and dormancy, help mollusks survive in FD and tolerate completely dry out of their Changhuchi habitat. Finally, we discovered that dissolved oxygen was an important controlling variable for mollusk communities during drought. Our findings provide a scientific basis for the management and conservation of floodplain wetland biodiversity in the context of increasing drought frequency and intensity.

Global eight drought types: Spatio-temporal characteristics and vegetation response

The traditional classification of drought events into seasonal and flash types oversimplified the complexity and variability of global drought phenomena, limiting a deeper understanding of drought characteristics and their impacts on vegetation. To address this issue, soil moisture percentile methods and the Soil Moisture Anomaly Percentage Index (SMAPI) were employed to create time series for flash drought (FD) and seasonal drought (SD) events globally from 1981 to 2020. A novel categorization framework was proposed to subdivide the two basic drought categories into eight distinct drought types using a set relationship identification method. The results showed fluctuating trends in the frequencies of Independent FD and Inclusion FD, which declined rapidly after 2011 at rates of 0.05 and 0.04 times/year, respectively. Independent FD frequency was highest in humid areas and decreased with increasing aridity. The spatial distributions of Inclusion FD and SD were similar, with both frequencies highest in extremely arid areas and decreasing with increasing humidity. The frequency of Independent SD, which peaked in semi-arid areas, increased significantly after 2011 at a rate of 0.01 times/year. The occurrence of FD evolving into SD or emerging at the end of SD was rare, with a global average of 0.46 events/decade and little spatial variation. Between 1981 and 2020, FD showed a U-shaped trend in drought duration, while SD showed no clear pattern. The duration of FD showed little difference across arid and humid zones, but the duration of SD decreased significantly with increasing humidity. Vegetation responses to drought varied, with arid regions showing longer response time compared to humid regions. A positive correlation between temperature and solar-induced chlorophyll fluorescence (SIF) during droughts was observed, while precipitation generally showed a negative correlation with SIF. Radiation had a minimal effect on SIF during droughts. The study offered a comprehensive categorization of drought events, enhancing our understanding of their spatiotemporal characteristics and vegetation responses on a global scale.

Homogenized gridded dataset for drought and hydrometeorological modeling for the continental United States

We present a novel data set for drought in the continental US (CONUS) built to enable computationally efficient spatio-temporal statistical and probabilistic models of drought. We converted drought data obtained from the widely-used US Drought Monitor (USDM) from its native geo-referenced polygon format to a 0.5 degree regular grid. We merged known environmental drivers of drought, including those obtained from the North American Land Data Assimilation System (NLDAS-2), US Geological Survey (USGS) streamflow data, and National Oceanic and Atmospheric Administration (NOAA) teleconnections data. The resulting data set permits statistical and probabilistic modeling of drought with explicit spatial and/or temporal dependence. Such models could be used to forecast drought at short-range, seasonal to sub-seasonal, and inter-annual timescales with uncertainty, extending the reach and value of the current US Drought Outlook from the National Weather Service Climate Prediction Center. This novel data product provides the first common gridded dataset that includes critical variables used to inform hydrological and meteorological drought.

Re-intensification of flash drought in western China over the past decade: Implications of fluctuating wetting trend

Climate changes and human activities have led to a rise of frequency and intensity of the global flash droughts, resulting in severe consequences for ecosystems, agriculture, and human societies. However, research dedicated to flash droughts in the dryland of western China is relatively limited, leaving their evolutionary characteristics and development processes of these phenomena unclear. To bridge this gap, this study analyzed the spatiotemporal characteristics of flash droughts in western China from 1981 to 2020, based on the standardized evapotranspiration stress index. Additionally, we investigated the development mechanisms by taking meteorological conditions and soil moisture into account. The findings revealed that the northern Qinghai-Tibet Plateau, western Qilian Mountains, and western and southern Loess Plateau are hotspots of flash droughts, characterized by rapid development rates. Across most of the study area, flash drought events persisted between 25 and 30 days. Adequate precipitation is necessary before the onset of flash droughts in western China, while water scarcity and high temperatures played crucial roles in driving the mid-stage of flash droughts. Within the context of the observed "warming and wetting" trend, the average flash droughts occurrence from 2011 to 2020 was approximately 16 % lower than that from 1981 to 1990, and there was a significant annual decrease in spatial coverage of 0.01 % per year. However, in the "wetting in west, drying in east" trend, the spatial coverage of flash droughts has shifted from a declining trend to an insignificant increasing trend since 2000 in the study area, with significant regional differences between the western and eastern regions. Over the past decade, flash droughts had once again intensified in the central Qinghai-Tibet Plateau and the Loess Plateau due to warming and fluctuating wetting trends, raising significant concerns for future ecosystem and agricultural water management in these regions.

The miR166 targets CsHDZ3 genes to negatively regulate drought tolerance in tea plant (Camellia sinensis)

Drought is the stressor with a significant adverse impact on the yield stability of tea plants. HD-ZIP III transcription factors (TFs) play important regulatory roles in plant growth, development, and stress responses. However, whether and how HD-ZIP III TFs are involved in drought response and tolerance in tea plants remains unclear. Here, we identified seven HD-ZIP III genes (CsHDZ3-1 to CsHDZ3-7) in tea plant genome. The evolutionary analysis demonstrated that CsHDZ3 members were subjected to purify selection. Subcellular localization analysis revealed that all seven CsHDZ3s located in the nucleus. Yeast self-activation and dual-luciferase reporter assays demonstrated that CsHDZ3-1 to CsHDZ3-4 have trans-activation ability whereas CsHDZ3-5 to CsHDZ3-7 served as transcriptional inhibitors. The qRT-PCR assay showed that all seven CsHDZ3 genes could respond to simulated natural drought stress and polyethylene glycol treatment. Further assays verified that all CsHDZ3 genes can be cleaved by csn-miR166. Overexpression of csn-miR166 inhibited the expression of seven CsHDZ3 genes and weakened drought tolerance of tea leaves. In contrast, suppression of csn-miR166 promoted the expression of seven CsHDZ3 genes and enhanced drought tolerance of tea leaves. These findings established the foundation for further understanding the mechanism of CsHDZ3-miR166 modules' participation in drought responses and tolerance.

Agricultural drought research knowledge graph reasoning by using VOSviewer

Drought seriously affects agricultural systems and food security. While previous researchers have explored the causes, monitoring, and impacts of drought on agriculture, no systematic investigations into the development of agriculture drought (AD) and its relationships with related knowledge have been conducted. This study assessed existing publications, particularly those conducted between 2020 and 2023. Systematic analysis was carried out using VOSviewer software and the Web of Science (WoS) database. These findings reveal a rising trend in the literature, with a recent acceleration. A total of 7416 articles on AD were identified, with contributions from 6935 institutions across 166 countries. China leads with 1833 publications, followed by the USA with 1278. There are 457 journals publishing AD studies, with the top five being sustainability, frontiers in plant science, agricultural water management, water, and agronomy-basel. The most frequently used keywords reflecting the current significant research direction in the AD field include climate change, yield, variability, impact, growth, and adaptation. The study also highlights four research hotspots and four future research directions. This bibliometric analysis provides a novel guide for agricultural drought research.

Exogenous methylglyoxal alleviates drought-induced 'plant diabetes' and leaf senescence in maize

Drought-induced leaf senescence is associated with high sugar levels, which bears some resemblance to the syndrome of diabetes in humans; however, the underlying mechanisms of such 'plant diabetes' on carbon imbalance and the corresponding detoxification strategy are not well understood. Here, we investigated the regulatory mechanism of exogenous methylglyoxal (MG) on 'plant diabetes' in maize plants under drought stress applied via foliar spraying during the grain-filling stage. Exogenous MG delayed leaf senescence and promoted photoassimilation, thereby reducing the yield loss induced by drought by 14%. Transcriptome and metabolite analyses revealed that drought increased sugar accumulation in leaves through inhibition of sugar transporters that facilitate phloem loading. This led to disequilibrium of glycolysis and overaccumulation of endogenous MG. Application of exogenous MG up-regulated glycolytic flux and the glyoxalase system that catabolyses endogenous MG and glycation end-products, ultimately alleviating 'plant diabetes'. In addition, the expression of genes facilitating anabolism and catabolism of trehalose-6-phosphate was promoted and suppressed by drought, respectively, and exogenous MG reversed this effect, implying that trehalose-6-phosphate signaling in the mediation of 'plant diabetes'. Furthermore, exogenous MG activated the phenylpropanoid biosynthetic pathway, promoting the production of lignin and phenolic compounds, which are associated with drought tolerance. Overall, our findings indicate that exogenous MG activates defense-related pathways to alleviate the toxicity derived from 'plant diabetes', thereby helping to maintain leaf function and yield production under drought.

Characteristics of flash droughts and their association with compound meteorological extremes in China: Observations and model simulations

Flash droughts have gained considerable public attention due to the imminent threats they pose to food security, ecological safety, and human health. Currently, there has been little research exploring the projected changes in flash droughts and their association with compound meteorological extremes (CMEs). In this study, we applied the pentad-mean water deficit index to investigate the characteristics of flash droughts and their association with CMEs based on observational data and downscaled model simulations. Our analysis reveals an increasing trend in flash drought frequency in China based on historical observations and model simulations. Specifically, the proportion of flash drought frequency with a one-pentad onset time showed a consistent upward trend, with the southern parts of China experiencing a high average proportion during the historical period. Furthermore, the onset dates of the first (last) flash droughts during year are projected to shift earlier (later) in a warmer world. Flash droughts become significantly more frequent in the future, with a growth rate approximately 1.3 times higher in the high emission scenario than in the medium emission scenario. The frequency of flash droughts with a one-pentad onset time also exhibits a significant upward trend, indicating that flash droughts will occur more rapidly in the future. CMEs in southern regions of China were found to be more likely to trigger flash droughts in the historical period. The probability of CMEs triggering flash droughts is expected to increase with the magnitude of warming, particularly in the far-future under the high emissions scenario.

Australia's Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change

We examine the characteristics and causes of southeast Australia's Tinderbox Drought (2017 to 2019) that preceded the Black Summer fire disaster. The Tinderbox Drought was characterized by cool season rainfall deficits of around -50% in three consecutive years, which was exceptionally unlikely in the context of natural variability alone. The precipitation deficits were initiated and sustained by an anomalous atmospheric circulation that diverted oceanic moisture away from the region, despite traditional indicators of drought risk in southeast Australia generally being in neutral states. Moisture deficits were intensified by unusually high temperatures, high vapor pressure deficits, and sustained reductions in terrestrial water availability. Anthropogenic forcing intensified the rainfall deficits of the Tinderbox Drought by around 18% with an interquartile range of 34.9 to -13.3% highlighting the considerable uncertainty in attributing droughts of this kind to human activity. Skillful predictability of this drought was possible by incorporating multiple remote and local predictors through machine learning, providing prospects for improving forecasting of droughts.

A decade of advances in the study of buckwheat for organic farming and agroecology (2013-2023)

During the last decade, research has shown the environment and human health benefits of growing buckwheat (Fagopyrum spp.). This comprehensive review aims to summarize the major advancements made in the study of buckwheat from 2013 to 2023, focusing on its agronomic characteristics, nutritional value, and potential applications in sustainable agriculture. The review examines the diverse applications of buckwheat in organic and agroecological farming systems, and discusses the ability of buckwheat to control weeds through allelopathy, competition, and other sustainable farming methods, such as crop rotation, intercropping and green manure, while improving soil health and biodiversity. The review also explores the nutritional value of buckwheat. It delves into the composition of buckwheat grains, emphasizing their high protein content, and the presence of essential amino acids and valuable micronutrients, which is linked to health benefits such as lowering cholesterol levels, controlling diabetes and acting against different types of cancer, among others. Finally, the review concludes by highlighting the gaps in current knowledge, and proposing future research directions to further optimize buckwheat production in organic or agroecological farming systems. It emphasizes the need for interdisciplinary collaboration, and the integration of traditional knowledge with modern scientific approaches to unlock the full potential of buckwheat as a sustainable crop.

Drought triggers and sustains overnight fires in North America

Overnight fires are emerging in North America with previously unknown drivers and implications. This notable phenomenon challenges the traditional understanding of the 'active day, quiet night' model of the diurnal fire cycle1-3 and current fire management practices4,5. Here we demonstrate that drought conditions promote overnight burning, which is a key mechanism fostering large active fires. We examined the hourly diurnal cycle of 23,557 fires and identified 1,095 overnight burning events (OBEs, each defined as a night when a fire burned through the night) in North America during 2017-2020 using geostationary satellite data and terrestrial fire records. A total of 99% of OBEs were associated with large fires (>1,000 ha) and at least one OBE was identified in 20% of these large fires. OBEs were early onset after ignition and OBE frequency was positively correlated with fire size. Although warming is weakening the climatological barrier to night-time fires6, we found that the main driver of recent OBEs in large fires was the accumulated fuel dryness and availability (that is, drought conditions), which tended to lead to consecutive OBEs in a single wildfire for several days and even weeks. Critically, we show that daytime drought indicators can predict whether an OBE will occur the following night, which could facilitate early detection and management of night-time fires. We also observed increases in fire weather conditions conducive to OBEs over recent decades, suggesting an accelerated disruption of the diurnal fire cycle.

Characterization of carbon fluxes, stock and nutrients in the sacred forest groves and invasive vegetation stands within the human dominated landscapes of a tropical semi-arid region

In the semi-arid plains of Southern India, outside the protected area network, sacred groves forests and the barren lands invaded by Prosopis juliflora are reckoned to be the major greenery, but have homogenous and heterogeneous vegetation respectively. This study attempted to compare 50 Sacred Groves Stands (SGS) and 50 monodominant Prosopis juliflora Stands (PJS) for the functional diversity, evenness, floral diversity, carbon stock and dynamics, carbon-fixing traits, dendrochronology of trees, soil nutrient profiles, and soil erosion. Quadrat sample survey was adopted to record stand density, species richness, abundance, basal area and leaf area index; composite soil samples were collected at depths 0-30 cm for nutrient profiling (N, P, K, and OC). Photosynthesis rate (µmole co2 m2/sec), air temperature (°c), leaf intracellular co2 concentration (ppm), ambient photosynthetic active radiation (µmole m2/sec), transpiration rate (m. mole H2O m2/sec) were determined for the 51 tree species existed in SGS and PJS using Plant Photosynthesis system. Structural Equation Model (SEM) was applied to derive the carbon sequestering potential and photosynthetic efficiency of eight dominant tree species using vital input parameters, including eco-physiological, morphological, and biochemical characterization. The Revised Universal Soil Loss Equation (RUSLE) model, in conjunction with ArcGIS Pro and ArcGIS 10.3, was adopted to map soil loss. Carbon source/sink determinations inferred through Net Ecosystem Productivity (NEP) assessments showed that mature SGS potentially acted as a carbon sink (0.06 ± 0.01 g C/m2/day), while matured PJS acted as a carbon source (-0.34 ± 0.12 g C/m2/day). Soil erosion rates were significantly greater (29.5 ± 13.4 ton/ha/year) in SGS compared to PJS (7.52 ± 2.55 ton/ha/year). Of the eight selected tree species, SEM revealed that trees belonging to the family Fabaceae [Wrightia tinctoria (estimated coefficient: 1.28, p = 0.02) > Prosopis juliflora (1.22, p = 0.01) > Acacia nilotica (1.21, p = 0.03) > Albizia lebbeck (0.97, p = 0.01)] showed comparatively high carbon sequestering ability.

The first global multi-timescale daily SPEI dataset from 1982 to 2021

Global warming accelerates water cycle, causing more droughts globally that challenge monitoring and forecasting. The Standardized Precipitation Evapotranspiration Index (SPEI) is used to assess drought characteristics and response time of natural and economic systems at various timescales. However, existing SPEI datasets have coarse spatial or temporal resolution or limited spatial extent, restricting their ability to accurately identify the start or end dates or the extent of drought at the global scale. To narrow these gaps, we developed a global daily SPEI dataset (SPEI-GD), with a 0.25° spatial resolution from 1982 to 2021 at multiple timescales (5, 30, 90, 180 and 360 days), based on the precipitation from European Center for Medium Weather Forecasting Reanalysis V5 (ERA5) dataset and the potential evapotranspiration from Singer's dataset. Compared to widely used SPEIbase dataset, the SPEI-GD can improve the spatial-temporal resolution and the accuracy of SPEI in areas where meteorological sites are lacking. The SPEI-GD significantly correlates with site-based SPEI and soil moisture. Our dataset solidly supports sub-seasonal and daily-scale global and regional drought research.

Coupling heat wave and wildfire occurrence across multiple ecoregions within a Eurasia longitudinal gradient

Understanding the relationship between heat wave occurrence and wildfire spread represents a key priority in global change studies due to the significant threats posed on natural ecosystems and society. Previous studies have not explored the spatial and temporal mechanism underlying the relationship between heat waves and wildfires occurrence, especially over large geographical regions. This study seeks to investigate such a relationship with a focus on 37 ecoregions within a Eurasia longitudinal gradient. The analysis is based on the wildfire dataset provided by the GlobFire Final Fire Event Detection and the meteorological dataset ERA5-land from Copernicus Climate service. In both cases we focused on the 2001-2019 timeframe. By means of a 12 km square grid, three wildfire metrics, i.e., density, seasonality, and severity of wildfires, were computed as proxy of fire regime. Heat waves were also characterized in terms of periods, duration, and intensity for the same period. Statistical tests were performed to evaluate the different patterns of heat wave and wildfire occurrence in the 37 ecoregions within the study area. By using Geographically Weighted Regression (GWR) we modeled the spatial varying relationships between heat wave characteristics and wildfire metrics. As expected, our results suggest that the 37 ecoregions identified within the Eurasia longitudinal gradient differ in terms of fire regimes. However, the occurrence of heat waves did not show significant differences among ecoregions, but a more evident variability in terms of relationship between fire regime metrics and heat waves within the study area. The outcome of the GWR analysis allowed us to identify the spatial locations (i.e., hotspot areas) where the relationship between heat waves and wildfires is positive and significant. Hence, in hotspots the presence of heat waves can be seen as a driver of wildfire occurrence in forest and steppe ecosystems. The findings from this study could contribute to a more comprehensive assessment of wildfire patterns in this geographical region, thus supporting cross-regional prevention strategies for disaster risk mitigation.

Projecting the impact of climate change and elevated CO2 concentration on rice irrigation water requirement in China

Climate change and elevated CO2 concentrations significantly affect rice growth and water consumption. Understanding the specific impacts of climate change and elevated CO2 concentrations on rice physiological phenology, crop water demand (ETC), and irrigation water requirement (IR) is of great significance for the sustainable utilization of water resources and food security. This is particularly true in China, the world's largest rice producer. In this study, with the help of two rice phenological models, the modified Penman-Monteith equation, and the paddy water balance model, we project the changes in rice phenological period, ETC, and IR in four main rice-producing regions of China in the period 2015-2100 based on the 11 GCM outputs. The results show that the rice growing period is shortened in most rice-producing regions, except for the parts of the middle and lower reaches of the Yangtze River. Meanwhile, the trend of ETC and IR of rice varies slightly among regions in the future scenario, with almost all regions decreasing yearly except for the middle and lower reaches of the Yangtze River, where the trend is increasing. The progressively increasing atmospheric CO2 concentration has a "fertilization effect" on the crop, which can reduce the water requirements of rice. In the SSP585 scenario, the " CO2 fertilization effect" can reduce up to 8.87 × 108 m3 of ETC and 6.94 × 108 m3 of IR in the middle and lower reaches of the Yangtze River in the period of 2090s. This study provides beneficial references to understand the response of rice ETC and IR to future climate change and CO2 concentration elevation in China and highlights that the simulation in terms of crop irrigation must account for the "CO2 fertilization effect".

The negative-positive feedback transition thresholds of meteorological drought in response to agricultural drought and their dynamics

There are complex bidirectional feedback relationships among different types of droughts (e.g., meteorological and agricultural droughts). As agricultural drought intensifies, meteorological drought response to agricultural drought may be changed from negative to positive feedback. Nevertheless, the negative-positive feedback transition thresholds of meteorological drought in response to agricultural drought and their dynamics have remained unsolved. Herein, we proposed a new quantitative method to characterize the mutual feedback between meteorological drought and agricultural drought based on the vine copula function for the first time in this study. The negative-positive feedback transition threshold and the sensitivity of the feedback were quantified under certain drought conditions. In order to investigate the feedback relationship dynamics under a changing environment, the total study period was evenly divided into two stages: stage 1 (1982-1999) and stage 2 (2000-2018). Finally, the random forest method was used to explore the dominant factors on the transition threshold. Results indicate that: (1) the negative-positive feedback transition thresholds in August is generally lower than June and July in mainland China, the basin with large threshold is the Southwest River Basin; (2) the sensitivity of meteorological drought in response to agricultural drought was higher in positive feedback than in negative feedback; (3) the transition thresholds of stage 2 was mostly reduced, while the feedback sensitivity of positive feedback was mostly increased; and (4) compared with the single factor, the land-meteorological coupling strength (the correlation between precipitation and soil moisture) dominants the negative-positive feedback transition threshold. This study sheds new insights into droughts feedback.

Plant litter loss exacerbates drought influences on grasslands

Plant litter is known to affect soil, community, and ecosystem properties. However, we know little about the capacity of litter to modulate grassland responses to climate change. Using a 7-yr litter removal experiment in a semiarid grassland, here we examined how litter removal interacts with a 2-yr drought to affect soil environments, plant community composition, and ecosystem function. Litter loss exacerbates the negative impacts of drought on grasslands. Litter removal increased soil temperature but reduced soil moisture and nitrogen mineralization, which substantially increased the negative impacts of drought on primary productivity and the abundance of perennial rhizomatous graminoids. Moreover, complete litter removal shifted plant community composition from grass-dominated to forb-dominated and reduced species and functional group asynchrony, resulting in lower ecosystem temporal stability. Our results suggest that ecological processes that lead to reduction in litter, such as burning, grazing, and haying, may render ecosystems more vulnerable and impair the capacity of grasslands to withstand drought events.

Watershed health and ecological security zoning throughout Iran

Today, land degradation and the decrease in the expected services of watersheds have been mainly influenced by human-induced activities. Hence, it requires more attention to adaptively manage and provide feasible solutions to watershed disruptions. However, appropriate management of precious commodities such as water, soil, air, and vegetation cover needs insight planning on a proper scale. Nonetheless, such an integrated approach to comprehensive health assessment of watershed resources is yet to be indoctrinated by scholars, implemental agencies, managers, and policymakers. Accordingly, the present endeavor has tried to evaluate the health status of Iran's 30 second-order large watersheds with the pressure-state-response (PSR) approach. In this regard, 44 problem-oriented, influential, and, at the same time, accessible variables with compatible scales at the national level were primarily determined in climatic, hydrologic, anthropogenic, and natural sectors. The collinearity-free and independent variables were then finalized using the variance inflation factor (VIF) test. Ultimately, P, S, and R indices were calculated using the arithmetic mean of 25 normalized variables based on which PSR-based health and security indices were also mapped countrywide. The results indicated that P, S, and R indices varied from 0.49 to 0.69, 0.42 to 0.82, and 0.40 to 0.94, respectively. Health and security indices ranged from 0.46 to 0.69 and 0.30 to 0.89, respectively. The weighted mean of P, S, and R was 0.59, 0.62, and 0.67, respectively, wholly placing them in the intermediate class. The weighted health and security indices were also 0.58 and 0.59, representing the intermediate class. The results showed that study watersheds had different health and security conditions from interplaying watershed-specific factors. The results revealed the necessity of watershed-unique managerial strategies to cope with the existing unfavorable conditions at the country level. However, further insight with high resolution is recommended for the high-priority watersheds to plan implementation and executive projects.

Drought-Stress-Induced Changes in Chloroplast Gene Expression in Two Contrasting Strawberry Tree (Arbutus unedo L.) Genotypes

This study investigated the effect of drought stress on the expression of chloroplast genes in two different genotypes (A1 and A4) of strawberry tree plants with contrasting performances. Two-year-old plants were subjected to drought (20 days at 18% field capacity), and the photosynthetic activity, chlorophyll content, and expression levels of 16 chloroplast genes involved in photosynthesis and metabolism-related enzymes were analyzed. Genotype-specific responses were prominent, with A1 displaying wilting and leaf curling, contrasting with the mild symptoms observed in A4. Quantification of damage using the net CO2 assimilation rates and chlorophyll content unveiled a significant reduction in A1, while A4 maintained stability. Gene expression analysis revealed substantial downregulation of A1 (15 out of 16 genes) and upregulation of A4 (14 out of 16 genes). Notably, psbC was downregulated in A1, while it was prominently upregulated in A4. Principal Component Analysis (PCA) highlighted genotype-specific clusters, emphasizing distinct responses under stress, whereas a correlation analysis elucidated intricate relationships between gene expression, net CO2 assimilation, and chlorophyll content. Particularly, a positive correlation with psaB, whereas a negative correlation with psbC was found in genotype A1. Regression analysis identified potential predictors for net CO2 assimilation, in particular psaB. These findings contribute valuable insights for future strategies targeting crop enhancement and stress resilience, highlighting the central role of chloroplasts in orchestrating plant responses to environmental stressors, and may contribute to the development of drought-tolerant plant varieties, which are essential for sustaining agriculture in regions affected by water scarcity.

Assessment of the shift in the precipitation-streamflow relationship influenced by multiyear drought, Yellow River basin, China

Climate change intensification (e.g., long-term drought) dramatically triggers catchment property changes, which introduces larger uncertainties for describing catchment hydrological behavior. In this study, hydrological behavior responses to multiyear drought were explored, and then causes were explained. The hydrological response to multiyear drought was explored using a magnitude of shift (M) in describing the relationship between precipitation (P) and streamflow (Q) in different catchment states, and a novel method, the trigonometric function decomposition method within the Budyko framework (the TFD method), was applied to assess the causes of Q changes. Several conclusions can be drawn: (i) multiyear drought mainly caused insignificant and significant upward (p < 0.05) changes in the P-Q relationship among 95.45 % of the studied catchments (p < 0.05); (ii) more server drying, lower leaf area index (LAI) and slope can induce a higher M via multiyear drought. In particular, catchment water storage, indicated by the deep soil layer in the Loess Plateau, can effectively mitigate the Q reduction and resulted in a 77.27 % (17/22) upward shift compared with the expected Q reduction; (iii) an asymmetric effect was caused by a multiyear P deficit, that is, (P-Q)/P increase and catchment property parameter (n) decrease were induced by the increases in ratio between potential evapotranspiration and P (Ep/P), suggesting that the catchment properties can mitigate the Q reduction; and (iv) catchment properties had negative effects on the Q reduction (7.76 mm a-1), and partially offset Q reduction (-21.32 mm a-1) resulted from climate change during the multiyear drought period. All of these results indicated that multiyear drought triggered Q reduction, while catchment behavior in the changeable induction mechanism induced a nonlinear Q response to P reduction, which is important for accurate Q projections and appropriate adaptation strategies for droughts.

The key role of ecological resilience in radial growth processes of conifers under drought stress in the subalpine zone of marginal deserts

Global climate change is exacerbating drought pressure on forests. However, the response patterns and physiological mechanisms of conifer species to drought, specifically in terms of radial growth, ecological resilience and soil water utilization, are not clearly understood. This study aims to quantify the effects of resilience on radial growth and identify the role of soil moisture utilization strategies in the resilience of species under drought intensities. We focus on two conifer species, Picea crassifolia (spruce) and Pinus tabuliformis (pine), located on the southern edge of the Tengger Desert in northwestern China. The dynamics of radial growth and ecological resilience were identified, and the seasonal growth rates of species based on soil water were simulated using the VS-oscilloscope model under varying drought stress. The results showed that spruce growth and recovery contributed by soil water were suppressed with frequent severe droughts, leading to a decline in growth (-0.5 cm2 year-1/10a, p < 0.05), despite its greater resistance to mild and moderate drought (-4.63 %). However, pine exhibited a stronger recovery (+40.25 %, p < 0.05) and higher variation in growth (-0.3 cm2 year-1/10a, p < 0.05) under soil moisture stress, despite its weaker resistance to drought (-23.53 %, p < 0.05). These findings provide insights into the growth, resilience, and water adaptation mechanisms of species under drought events, and theoretical support for the conservation and management of conifer diversity and forest ecosystem stability in climate-sensitive regions.

Increased drought and extreme events over continental United States under high emissions scenario

The frequency, severity, and extent of climate extremes in future will have an impact on human well-being, ecosystems, and the effectiveness of emissions mitigation and carbon sequestration strategies. The specific objectives of this study were to downscale climate data for US weather stations and analyze future trends in meteorological drought and temperature extremes over continental United States (CONUS). We used data from 4161 weather stations across the CONUS to downscale future precipitation projections from three Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase Six (CMIP6), specifically for the high emission scenario SSP5 8.5. Comparing historic observations with climate model projections revealed a significant bias in total annual precipitation days and total precipitation amounts. The average number of annual precipitation days across CONUS was projected to be 205 ± 26, 184 ± 33, and 181 ± 25 days in the BCC, CanESM, and UKESM models, respectively, compared to 91 ± 24 days in the observed data. Analyzing the duration of drought periods in different ecoregions of CONUS showed an increase in the number of drought months in the future (2023-2052) compared to the historical period (1989-2018). The analysis of precipitation and temperature changes in various ecoregions of CONUS revealed an increased frequency of droughts in the future, along with longer durations of warm spells. Eastern temperate forests and the Great Plains, which encompass the majority of CONUS agricultural lands, are projected to experience higher drought counts in the future. Drought projections show an increasing trend in future drought occurrences due to rising temperatures and changes in precipitation patterns. Our high-resolution climate projections can inform policy makers about the hotspots and their anticipated future trajectories.

Non-perennial segments in river networks

Non-perennial river segments - those that recurrently cease to flow or frequently dry - occur in all river networks and are globally more abundant than perennial (always flowing) segments. However, research and management have historically focused on perennial river segments. In this Review, we outline how non-perennial segments are integral parts of river networks. Repeated cycles of flowing, non-flowing and dry phases in non-perennial segments influence biodiversity and ecosystem dynamics at different spatial scales, from individual segments to entire river networks. Varying configurations of perennial and non-perennial segments govern physical, chemical and ecological responses to changes in the flow regimes of each river network, especially in response to human activities. The extent of non-perennial segments in river networks has increased owing to warming, changing hydrological patterns and human activities, and this increase is predicted to continue. Moreover, the dry phases of flow regimes are expected to be longer, drier and more frequent, albeit with high regional variability. These changes will likely impact biodiversity, potentially tipping some ecosystems to compromised stable states. Effective river-network management must recognize ecosystem services (such as flood risk management and groundwater recharge) provided by non-perennial segments and ensure their legislative and regulatory protection, which is often lacking.

A novel framework for investigating the mechanisms of climate change and anthropogenic activities on the evolution of hydrological drought

Climate change and anthropogenic activity are the primary drivers of water cycle changes. Hydrological droughts are caused by a shortage of surface and/or groundwater resources caused by climate change and/or anthropogenic activity. Existing hydrological models have primarily focused on simulating natural water cycle processes, while limited research has investigated the influence of anthropogenic activities on water cycle processes. This study proposes a novel framework that integrates a distributed hydrological model and an attribution analysis method to assess the impacts of climate change and anthropogenic activities on hydrological drought The distributed dualistic water cycle model was applied to the Fuhe River Basin (FRB), and it generated a Nash-Sutcliffe efficiency coefficient > 0.85 with a relative error of <5 %. Excluding the year with extreme drought conditions, our analysis revealed that climate change negatively impacted the average drought duration (-105.5 %) and intensity (-23.6 %) because of increasing precipitation. However, anthropogenic activities continued to contribute positively to the drought, accounting for 5.5 % and 123.6 % of the average drought duration and intensity, respectively, because of increased water consumption. When accounting for extreme drought years, our results suggested that climate change has contributed negatively to the average duration of drought (-113.2 %) but positively to its intensity (7.8 %). Further, we found that anthropogenic activities contributed positively to both the average drought duration and intensity (13.2 % and 92.2 %, respectively). While climate change can potentially mitigate hydrological drought in the FRB by boosting precipitation levels, its overall effect may exacerbate drought through the amplification of extreme climate events resulting from global climate change. Therefore, greater attention should be paid to the effects of extreme drought.

A review of recent developments on drought characterization, propagation, and influential factors

Droughts have impacted human society throughout its history. However, the occurrence of severe drought events in the last century and the concerns on the potential effects of climate change have prompted remarkable advances in drought conceptualization and modeling in recent years. This review intends to present the state-of-the-art on drought characterization and propagation, as well as providing insights on how climate dynamics and anthropogenic activities might affect this phenomenon. For this purpose, we first address the distinct concepts of droughts and their relationships. Next, we present two frequently utilized methods based on the run theory for drought characterization and explain the development and recovery stages of droughts. Then, we discuss potential drivers for drought occurrence and propagation, with focus on meteorological factors, catchments' physical characteristics and human activities. Later, we describe how droughts can affect several parameters of water quality. This review also addressed flash droughts, encompassing their definitions, commonly used indices, and potential drivers. Finally, we briefly address the roles of climate change and long-term persistence on future drought scenarios. This review may be useful for researchers and stakeholders for attaining a broader understanding on drought dynamics and impacts.

Water scarcity is exacerbated in the south

The Southern Hemisphere has experienced a 20% drop in water availability in 20 years.

Reversal in the drought stress response of the Scots pine forest ecosystem: Local soil water regime as a key to improving climate change resilience

In a changing climate, forest ecosystems have become increasingly vulnerable to continuously exacerbating heat and associated drought conditions. Climate stress resilience is governed by a complex interplay of global, regional, and local factors, with hydrological conditions being among the key players. We studied a Scots pine (Pinus sylvestris L.) forest ecosystem located near the southern edge of the boreal ecotone, which is particularly subjected to frequent and prolonged droughts. By comparing the dendrochronological series of pines growing in apparently contrasting hydrological conditions ranging from the waterlogged peat bog area to the dry soil at the surrounding elevations, we investigated how the soil water regime affects the climate response and drought stress resilience of the forest ecosystem. We found that in the dry land area, a significant fraction of the trees were replaced after two major climate extremes: prolonged drought and extremely low winter temperatures. The latter has also been followed by a three- to ten-fold growth reduction of the trees that survived in the next year, whereas no similar effect has been observed in the peat bog area. Multi-scale detrended partial cross-correlation analysis (DPCCA) indicated that tree-ring width (TRW) was negatively correlated with spring and summer temperatures and positively correlated with the Palmer drought severity index (PDSI) for the same year. For the elevated dry land area, the above effect extends to interannual scales, indicating that prolonged heatwaves and associated droughts are among the factors that limit tree growth. In marked contrast, in the waterlogged peat bog area, a reversed tendency was observed, with prolonged dry periods as well as warmer springs and summers over several consecutive years, leading to increasing tree growth with a one- to three-year time lag. Altogether, our results indicate that the pessimal conditions of a warming climate could become favorable through the preservation of the soil water regime.

Securing maize reproductive success under drought stress by harnessing CO2 fertilization for greater productivity

Securing maize grain yield is crucial to meet food and energy needs for the future growing population, especially under frequent drought events and elevated CO2 (eCO2) due to climate change. To maximize the kernel setting rate under drought stress is a key strategy in battling against the negative impacts. Firstly, we summarize the major limitations to leaf source and kernel sink in maize under drought stress, and identified that loss in grain yield is mainly attributed to reduced kernel set. Reproductive drought tolerance can be realized by collective contribution with a greater assimilate import into ear, more available sugars for ovary and silk use, and higher capacity to remobilize assimilate reserve. As such, utilization of CO2 fertilization by improved photosynthesis and greater reserve remobilization is a key strategy for coping with drought stress under climate change condition. We propose that optimizing planting methods and mining natural genetic variation still need to be done continuously, meanwhile, by virtue of advanced genetic engineering and plant phenomics tools, the breeding program of higher photosynthetic efficiency maize varieties adapted to eCO2 can be accelerated. Consequently, stabilizing maize production under drought stress can be achieved by securing reproductive success by harnessing CO2 fertilization.