Response of vegetation to drought time-scales across global land biomes

Increased stress from compound drought and heat events on vegetation

Compound drought and heat events (CDHEs), which are frequently occurring compound extreme climate events, have garnered considerable attention because of their detrimental effects on ecosystems. However, the intricacies of the spatial and temporal distributions of different durations of compound events, along with the variability in vegetation responses remain unclear. Here, we delineated the CDHEs based on meteorological observation data and investigated the spatial and temporal characteristics of CDHEs from 1993 to 2020 using the Theil-Sen trend test and Mann-Kendall nonparametric test. Furthermore, we utilized sliding correlation analysis to evaluate the impacts of CDHEs on vegetation among different climatic regions and ecosystems. Our findings indicate significant increasing trends in both the frequency and persistence of CDHEs from 1993 to 2020. The average trend of CDHEs frequency across different duration periods amounted to 13.80 %/decade. The fractional contribution of CDHEs lasting more than three days exhibited a significant increase, with an average trend of 2.00 %/decade. We also observed that vegetation is most significantly affected by compound events lasting 5-9 days. During the study period, the geographical extent of vegetation significantly impacted by CDHEs expanded by 0.89 %, correlation strength increased by 0.02, and lag time decreased by 0.25 months. These insights highlight the growing impact of CDHEs on vegetation under climate change, improving our understanding of vegetation responses to these compound events.

Time-lag and accumulation responses of vegetation growth to average and extreme precipitation and temperature events in China between 2001 and 2020

Climate change is often closely related to vegetation dynamics; time lag (Tlag) and accumulative effects (Tacc) are non-negligible phenomena when studying the interaction between climate and vegetation. But, amidst the escalating frequency of extreme climatic events, the quantification of temporal effects (Teffects) of such extremes on vegetation remains scarce. This research quantifies the Tlag and Tacc responses of China's vegetation to episodes of extreme temperature and precipitation since the early 2000s, utilizing daily meteorological data series. Overall, the precipitation in China has become wetter, and nighttime temperatures have risen significantly. The proportion of areas with Teffects ranged from 1.15 % to 15.95 %, and the correlation coefficient between the climate indices and the Normalized Difference Vegetation Index (NDVI) increased by 0.05 to 0.38 when considering the Teffects, compared to not considering it. The Tacc of vegetation had the strongest response (70.74-88.01 %) to extreme events among all the tested climate indices. Moreover, the Tacc of consecutive climate events had a greater impact on vegetation growth than individual climate event. The average Tacc for extreme temperature and extreme precipitation was 1.7-3.09 months and 2.17-3.25 months, respectively. Events like the over 95 % (R95p) and 99 % (R99p) percentile heavy precipitation and the maximum precipitation amount in one day (Rx1day) caused significant Teffects on NDVI. In addition, 90 % of grasslands exhibit Tacc, mainly contributed by the extreme precipitation indices (55.7 %), while the Teffects of forests were stronger than those of extreme temperature. Furthermore, NDVI was more affected by annual precipitation than by extreme precipitation, but the opposite was true for temperature. The results of this study highlight the importance of considering the Tlag and Tacc when predicting the effects of climate change on vegetation dynamics.

Assessment of meteorological drought impacts on rainfed agriculture using remote sensing-derived biomass productivity

Assessing drought impacts is necessary for pursuing sustainable development goals relevant to food security and land degradation. Data availability is a major restriction and remote sensing has been promoted for this purpose. Version 3 of WaPOR has been released in 2023, which provides global coverage of remote sensing-derived water productivity indicators and could allow improved analysis of drought impacts, but validation is still needed. This study explores the utility of remote sensing-derived productivity data from WaPOR as a proxy indicator for agricultural drought impacts. The analysis utilized (1) production surveys, (2) meteorological measurements for drought analysis, and (3) remote sensing-derived gross and net biomass water productivities (GBWP & NBWP) and total biomass production (TBP). All layers were analyzed against the Standardized Precipitation and Standardized Precipitation Evapotranspiration Indices (SPI and SPEI) over drought-vulnerable locations in Irbid and Madaba governorates in Jordan. Strong and significant correlations (R2 0.5-0.8, P < 0.05) were obtained between drought intensities and GBWP and NBWP layers, particularly in the May-Sep periods. These correlations were higher than previously tested remotely sensed indicators for agricultural drought impacts. Water productivity and biomass production averages were lower during drier periods and higher during wet periods, but pairwise testing did not reveal significant differences. There is sufficient evidence that WaPOR data demonstrates behavior that reflects agricultural response to drought, and further assessment in other agroclimatic zones is recommended. This could potentially allow for enhanced evaluation of management strategies, decision support, and policy recommendations for drought mitigation.

The impacts of rising vapour pressure deficit in natural and managed ecosystems

An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land-atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co-evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

Precipitation changes alter plant dominant species and functional groups by changing soil salinity in a coastal salt marsh

Specific mechanisms of precipitation change due to global climate variability on plant communities in coastal salt marsh ecosystems remain unknown. Hence, a field manipulative precipitation experiment was established in 2014 and 5 years of field surveys of vegetation from 2017 to 2021 to explore the effects of precipitation changes on plant community composition. The results showed that changes in plant community composition were driven by dominant species, and that the dominance of key species changed significantly with precipitation gradient and time, and that these changes ultimately altered plant community traits (i.e., community density, height, and species richness). Community height increased but community density decreased with more precipitation averaged five years. Furthermore, changes in precipitation altered dominant species composition and functional groups mainly by influencing soil salinity. Salinity stress caused by decreased precipitation shifted species composition from a dominance of taller perennials and grasses to dwarf annuals and forbs, while the species richness decreased. Conversely, soil desalination caused by increased precipitation increased species richness, especially increasing in the dominance of grasses and perennials. Specifically, Apocynaceae became dominance from rare while Amaranthaceae decreased in response to increased precipitation, but Poaceae was always in a position of dominance. Meanwhile, the dominance of grasses and perennials has the cumulative effect of years and their proportion increased under the increased 60% of ambient precipitation throughout the years. However, the annual forb Suaeda glauca was gradually losing its dominance or even becoming extinct over years. Our study highlights that the differences in plant salinity tolerance are key to the effects of precipitation changes on plant communities in coastal salt marsh. These findings aim to provide a theoretical basis for predicting vegetation dynamics and developing ecological management strategies to adapt to future precipitation changes.

Resistance of grassland productivity to drought and heatwave over a temperate semi-arid climate zone

Drought and heatwave are the primary climate extremes for vegetation productivity loss in the global temperate semi-arid grassland, challenging the ecosystem productivity stability in these areas. Previous studies have indicated a significant decline in the resistance of global grassland productivity to drought, but we still lack a systematic understanding of the mechanisms determining the spatiotemporal variations in grassland resistance to drought and heatwave. In this study, we focused on temperate semi-arid grasslands of China (TSGC) to assess the spatiotemporal variations of grassland productivity resistance to different climate extremes: compound dry-hot events, individual drought events, and individual heatwave events that occurred during 2000-2019. Based on the explainable machine learning model, we explored the resistance to the interaction of drought and heatwave and identify the dominant factors determining the spatiotemporal variations in resistance. The results revealed that grassland resistance to climate extremes had decreased in Xilingol Grassland and Mu Us Sandy Land, and had a not significant increase in Otindag Desert during 2000-2019. Human activities and the increase in CO2 concentration causes a decline in resistance in Mu Us Sandy Land, and the increase of VPD and shift of vegetation loss event timing caused a decline in resistance in Xilingol Grassland, while the weakening of climate extremes, especially the shortening of drought duration, increase the resistance in Otindag Desert. Mean annual temperature dominates the spatial differences in resistance among different grasslands. When drought and heatwave occur simultaneously, there is an additive effect on resistance and causes lower resistance to compound dry-hot events compared to individual drought and heatwave events. Our analysis provides crucial insights into understanding the impact of climate extremes on the temperate semi-arid grasslands of China.

The effects of various degrees of meteorological drought on forest vegetation in ecologically Fragile Karst Areas of Guangxi, China

ABSTRACTDrought presents a major challenge to the management of rocky desertification and ecological restoration in the delicate karst ecosystems of Guangxi. In this study, the normalized difference vegetation index (NDVI), fractional vegetation cover (FVC) and net primary productivity (NPP) were selected as vegetation remote sensing parameters, and the spatial response characteristics of different types of vegetation in karst areas of Guangxi Province to light, moderate, severe and extreme drought were analyzed to provide scientific basis for the evaluation of the impact of drought on vegetation in karst areas. The results are as follows: (1) NDVI, FVC and NPP showed a fluctuating increasing trend from 2000 to 2022, and the increasing rates were 0.058, 6.90%, and 43.3gC.m-2 per decade respectively. During this period, the number of light, moderate and severe drought days showed a decreasing trend, but the number of extreme drought days tended to increase. (2) The negative correlation of NDVI, FVC and NPP and drought increased from moderate to extreme drought, and from light to extreme drought, the negative correlation between NDVI and FVC and drought decreased, while that of NPP increased. (3) Light and moderate droughts had obvious negative impact on Chinese fir and broad-leaved forest, whereas severe and extreme droughts had obvious negative effect on eucalyptus and bamboo forest.

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.

Assessing the responses of ecosystem patterns, structures and functions to drought under climate change in the Yellow River Basin, China

Understanding how ecosystems respond and adapt to drought has become an urgent issue as drought stress intensifies under climate change, yet this topic is not fully understood. Currently, conclusions on the response of ecosystems in different regions to drought disturbance are inconsistent. Based on long MODIS data and observed data, this study systematically explored the relationships between ecosystem patterns, structures and functions and drought, taking a typical climate change-sensitive area and an ecologically fragile area-the Yellow River Basin-as a case study. Drought assessment results revealed that the Yellow River Basin has experienced meteorological and hydrological drought during most of the last two decades, predominantly characterized by medium and slight droughts. The ecosystem patterns and structures changed dramatically as the grassland decreased and the landscape fragmentation index (F) increased with increasing wetness. The annual gross primary productivity (GPP) increased, the water use efficiency (WUE) declined and ecosystem service value (ESV) exhibited a W-shaped increase at the watershed scale, but there were significant regional differences. There were positive correlations between F, GPP, ESV and drought indices, while there was a negative correlation between WUE and drought indices at the watershed scale. Under drought stress, the ecosystem structure in the basin was disrupted, the GPP and ESV decreased, but the WUE increased. Notably, approximately 106 %, 20 %, and 1 % of the maximum reductions in F, GPP, and ESV, respectively, were caused by drought, while the maximum 4 % of WUE increased. Responses of some functions in the wetland and grassland to drought vary from those in other ecosystems. The mechanisms underlying ecosystem responses to drought were further investigated. This study enhances the understanding of these responses and will help stakeholders formulate drought mitigation policies and protect ecosystem health.

Dynamics of solar-induced chlorophyll fluorescence (SIF) and its response to meteorological drought in the Yellow River Basin

Solar-induced chlorophyll fluorescence (SIF) has been used since its discovery to characterize vegetation photosynthesis and is an effective tool for monitoring vegetation dynamics. Its response to meteorological drought enhances our comprehension of the ecological consequences and adaptive mechanisms of plants facing water scarcity, informing more efficient resource management and efforts in mitigating climate change. This study investigates the spatial and temporal patterns of SIF and examines how vegetation SIF in the Yellow River Basin (YRB) responds to meteorological drought. The findings reveal a gradual southeast-to-northwest decline in SIF across the Yellow River Basin, with an overall increase-from 0.1083 W m-2μm-1sr-1 in 2001 to 0.1468 W m-2μm-1sr-1 in 2019. Approximately 96% of the YRB manifests an upward SIF trend, with 75% of these areas reaching statistical significance. The Standardized Precipitation Evapotranspiration Index (SPEI) at a time scale of 4 months (The SPEI-4), based on the Liang-Kleeman information flow method, is identified as the most suitable drought index, adeptly characterizing the causal relationship influencing SIF variations. As drought intensified, the SPEI-4 index markedly deviated from the baseline, resulting in a decrease in SIF values to their lowest value; subsequently, as drought lessened, it gravitated towards the baseline, and SIF values began to gradually increase, eventually recovering to near their annual maximum. The key finding is that the variability of SIF with SPEI is relatively pronounced in the early growing season, with forests demonstrating superior resilience compared to grasslands and croplands. The responsiveness of vegetation SIF to SPEI can facilitate the establishment of effective drought early warning systems and promote the rational planning of water resources, thereby mitigating the impacts of climate change.

Identifying drivers of non-stationary climate-growth relationships of European beech

The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species' ecological amplitude. Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees' rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech's drought sensitivity, which needs to be taken into consideration when assessing this species' response to climate change.

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.

Changes in vegetation-water response in the Sahel-Sudan during recent decades

Study region

The Africa Sahel-Sudan region, defined by annual rainfall between 150 and 1200 mm.

Study focus

Understanding the mechanism of vegetation response to water availability could help mitigate the potential adverse effects of climate change on global dryland ecosystems. In the Sahel-Sudan region, spatio-temporal changes and drivers of the vegetation-water response remain unclear. This study employs long-term satellite water and vegetation products as proxies of water availability and vegetation productivity to analyze changes in vegetation-water sensitivity and the cumulative effect duration (CED) representing a measure of the legacy effect of the impact of water constraints on vegetation. A random forest model was subsequently used to analyze potential climatic drivers of the observed vegetation response.

New hydrological insights for the region

During 1982-2016 we found a significant decrease (p < 0.05) in the sensitivity of vegetation productivity to water constraints in 26% of the Sahel-Sudan region, while 9% of the area showed a significantly increased sensitivity, mainly in the sub-humid zone. We further showed that CED significantly increased and decreased, respectively in around 9% of the study area in both cases. Our climatic driver attribution analysis suggested the existence of varying underlying mechanisms governing vegetation productivity in response to water deficit across the Sahel-Sudan dryland ecosystems. Our findings emphasize the need for diverse strategies in sustainable ecosystem management to effectively address these varying mechanisms.

Spatiotemporal patterns of net primary productivity of subtropical forests in China and its response to drought

Net primary productivity (NPP) is an important indicator used to evaluate the carbon sequestration capacity of forest ecosystems. Subtropical forest ecosystems play an indispensable role in maintaining the global carbon balance, while frequently occurring drought events in recent years have seriously damaged their productivity. However, the spatiotemporal patterns of NPP, as well as its response to drought, remain uncertain. In this study, the multiscale drought characteristics in subtropical China during 1981-2015 were analyzed based on the standardized precipitation evapotranspiration index. Then, simulated and analyzed the spatiotemporal NPP of subtropical forests by the boreal ecosystem productivity simulator model. Finally, the response of NPP to drought was analyzed based on multiple statistical indices. The results show that most regions in subtropical China experienced mild and moderate drought during 1981-2015. In particular, the extent of drought severity has shown a noticeable increasing trend after 2000. The forest NPP ranged from 622.64 to 1323.82 gC·m-2·a-1, with an overall increase rate of 16.15 gC·m-2·a-1; in particular, the contribution of the western forest NPP became increasingly important. Drought stress has limited the growth of subtropical forest NPP in China, with summer and wet season time scales of drought having the greatest impact on forest NPP anomalies, followed by autumn time scales. The limitation is mostly because the drought duration continually increased, leading to differences in the impact of drought on forest NPP before and after 2000, with declines of 59.55 % and 82.45 %, respectively, mainly concentrated in southwestern regions, such as Yunnan, Guangxi, and Sichuan provinces. This study quantitatively analyzed the impact of drought on subtropical forest NPP, and provides scientific basis for subtropical forest response and adaptation to climate change.

Quantifying the drought sensitivity of grassland under different climate zones in Northwest China

Grassland is essential for maintaining the stability and functionality of terrestrial ecosystems. Although previous research has explored how grassland responds to drought, the drought sensitivity of grassland (DSG) across climate zones and aridity gradients remains uncertain. In this study, we conducted a comprehensive investigation spanning 1982 to 2015 in Northwest China. To assess the time-cumulative effect (TCE) and the time-lag effect (TLE) of drought on grassland, we employed Spearman rank correlation analysis, utilizing long-term datasets of the normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI). This analysis allowed us to quantify the DSG in the region and further examine its variations across climate zones and aridity gradient. Our results revealed that 81.2 % and 99.7 % of the grassland in Northwest China was influenced by the TCE and TLE of drought, respectively, with 38.2 % and 60.9 % of these effects being statistically significant (p < 0.05). The mean accumulated and lagged timescales of drought on grassland were 7.89 and 9.41 months, respectively. Remarkably, the highest DSG was observed in the semi-arid zone (0.58), followed by the arid (0.54), sub-humid (0.51), and humid (0.44) zones. Furthermore, we identified significant nonlinear variation patterns of DSG along the aridity gradient, characterized by several discernible trend breaks. These findings contribute to our understanding of the impacts of drought on vegetation, particularly in ecologically fragile regions.

Climate-limited vegetation change in the conterminous United States of America

The effects of climate change on vegetation composition and distribution are evident in different ecosystems around the world. Although some climate-derived alterations on vegetation are expected to result in changes in lifeform fractional cover, disentangling the direct effects of climate change from different non-climate factors, such as land-use change, is challenging. By applying "Liebig's law of the minimum" in a geospatial context, we determined the climate-limited potential for tree, shrub, herbaceous, and non-vegetation fractional cover change for the conterminous United States and compared these potential rates to observed change rates for the period 1986 to 2018. We found that 10% of the land area of the conterminous United States appears to have climate limitations on the change in fractional cover, with a high proportion of these sites located in arid and semiarid ecosystems in the Southwest part of the country. The rates of change in lifeform fractional cover for the remaining area of the country are likely limited by non-climate factors such as the disturbance regime, land management, land-use history, soil conditions, and species interactions and adaptations.

Response of grassland growing season length to extreme climatic events on the Qinghai-Tibetan Plateau

Extreme Climatic Events (ECEs) are increasing in intensity, frequency, and duration as the earth warms, which greatly affects the vegetation phenology. However, the response of vegetation phenology to different types of ECEs (e.g., extreme hot, extreme cold, extreme drought, and extreme wet) has not been extensively studied. To fill this knowledge gap, we investigated the relationship between the length of growing season (LOS) of grassland and ECEs on the Qinghai-Tibetan Plateau (QTP). First, we analyzed the spatial distribution and interannual trends of phenology based on the MODIS Normalized Difference Vegetation Index (NDVI). Second, we used Coincidence Rate (CR) analysis to quantify the relationship between LOS anomalies and ECEs. Finally, we analyzed the sensitivity of LOS to the intensity of ECEs. The results indicated that the spatial distribution of LOS was closely related to local hydrothermal conditions, with longer LOS in places with more precipitation or higher temperatures during the growing season, and LOS extended by 0.28 days/year from 2000 to 2022. Moreover, we found that the CR of negative LOS anomalies to ECEs notably exhibited variations along climatic gradients, with higher CR to extreme hot generally occurring in warmer areas. Meanwhile, the CR of extreme wet increased while the CR of extreme drought decreased with increasing precipitation. We also found that the sensitivity of LOS to ECEs changed more markedly, along the climatic gradients, in alpine ecoregions compared to temperate ecoregions. Overall, the sensitivities of LOS ranked in descending order of absolute sensitivity to extreme drought, extreme wet, extreme hot, and extreme cold. This study furthers our understanding of the grassland response to ECEs under different hydrothermal conditions, which can provide valuable reference for the management and conservation of grassland ecosystems in QTP under future climate change scenarios.

Grassland vegetation decline is exacerbated by drought and can be mitigated by soil improvement in Inner Mongolia, China

Grassland activity is highly susceptible to drought while drivers from climate and soil attributes can largely affect drought propagation. However, understanding how these drives regulate the risk of vegetation decline under drought conditions remains limited, potentially impeding the adoption of appropriate adaptation strategies. To address this knowledge gap, we conducted a case study focusing on grassland activity in Inner Mongolia, China. In this study, we applied copula theorem to estimate the conditional probabilities of vegetation decline under drought conditions. Additionally, we utilized a structural equation model and a machine learning approach to identify the relative contributions of external drivers to the risk of vegetation decline. Our findings demonstrated a positive correlation between anomalies in vegetation activity and the status of water balance, and grassland vegetation in drier regions exhibited a more rapid response to water deficit. Increasing water deficit continuously reduced vegetation activity with risks of 77.27 %, 83.83 %, and 88.35 % under moderate, severe, and extreme drought conditions, respectively. Furthermore, the risks of vegetation decline under drought conditions were primarily governed by climate attributes, followed by soil properties and topography. Soil with high soil organic carbon stock content contributed significantly to mitigating the adverse effects of drought on grassland vegetation. In addition, we detected nonlinear patterns among environmental drivers and vegetation decline risks caused by drought. These findings highlight the importance of climate, soil properties, topography, and their intricate interconnections in regulating vegetation decline. This knowledge provides valuable insights into drought risk management for vegetation in advance and offers potential solutions to enhance vegetation resistance in the face of extreme drought events.

Shifting climatic responses of tree rings and NDVI along environmental gradients

Variations in the growth of aboveground biomass compartments such as tree stem and foliage significantly influence the carbon cycle of forest ecosystems. Yet the patterns of climate-driven responses of stem and foliage and their modulating factors remain poorly understood. In this study, we investigate the climatic response of Norway spruce (Picea abies) at 138 sites covering wide spatial and site fertility gradients in temperate forests in Central Europe. To characterize the annual growth rate of stem biomass and seasonal canopy vigor, we used tree-ring chronologies and time-series of NDVI derived from Landsat imagery. We calculated correlations of tree-ring width and NDVI with mean growing season temperature and standardized precipitation evapotranspiration index (SPEI). We evaluated how these climate responses varied with aridity index, soil category, stand age, and topographical factors. The results show that the climate-growth responses of tree rings shift from positive to negative for SPEI and from negative to positive for temperature from dry (warm) to wet (cold) areas. By contrast, NDVI revealed a negative response to temperature across the entire climatic gradient. The negative response of NDVI to temperature likely results from drought effects in warm areas and supporting effects of cloudy conditions on foliage greenness in wet areas. Contrary to NDVI, climate responses of tree rings differed according to stand age and were unaffected by local topographical features and soil conditions. Our findings demonstrate that the decoupling of stem and foliage climatic responses may result from their different climatic limitation along environmental gradients. These results imply that in temperate forest ecosystems, the canopy vigor may show different trends compared to stem growth under ongoing climate change.

Declining coupling between vegetation and drought over the past three decades

Droughts have been implicated as the main driver behind recent vegetation die-off and are projected to drive greater mortality under future climate change. Understanding the coupling relationship between vegetation and drought has been of great global interest. Currently, the coupling relationship between vegetation and drought is mainly evaluated by correlation coefficients or regression slopes. However, the optimal drought timescale of vegetation response to drought, as a key indicator reflecting vegetation sensitivity to drought, has largely been ignored. Here, we apply the optimal drought timescale identification method to examine the change in coupling between vegetation and drought over the past three decades (1982-2015) with long-term satellite-derived Normalized Difference Vegetation Index and Standardized Precipitation-Evapotranspiration Index data. We find substantial increasing response of vegetation to drought timescales globally, and the correlation coefficient between vegetation and drought under optimal drought timescale overall declines between 1982 and 2015. This decrease in vegetation-drought coupling is mainly observed in regions with water deficit, although its initial correlation is relatively high. However, vegetation in water-surplus regions, with low coupling in earlier stages, is prone to show an increasing trend. The observed changes may be driven by the increasing trend of atmospheric CO2 . Our findings highlight more pressing drought risk in water-surplus regions than in water-deficit regions, which advances our understanding of the long-term vegetation-drought relationship and provides essential insights for mapping future vegetation sensitivity to drought under changing climate conditions.

Drought thresholds that impact vegetation reveal the divergent responses of vegetation growth to drought across China

Identifying droughts and accurately evaluating drought impacts on vegetation growth are crucial to understanding the terrestrial carbon balance across China. However, few studies have identified the critical drought thresholds that impact China's vegetation growth, leading to large uncertainty in assessing the ecological consequences of droughts. In this study, we utilize gridded surface soil moisture data and satellite-observed normalized difference vegetation index (NDVI) to assess vegetation response to droughts in China during 2001-2018. Based on the nonlinear relationship between changing drought stress and the coincident anomalies of NDVI during the growing season, we derive the spatial patterns of satellite-based drought thresholds (T SM ) that impact vegetation growth in China via a framework for detecting drought thresholds combining the methods of feature extraction, coincidence analysis, and piecewise linear regression. The T SM values represent percentile-based drought threshold levels, with smaller T SM values corresponding to more negative anomalies of soil moisture. On average, T SM is at the 8.7th percentile and detectable in 64.4% of China's vegetated lands, with lower values in North China and Jianghan Plain and higher values in the Inner Mongolia Plateau. Furthermore, T SM for forests is commonly lower than that for grasslands. We also find that agricultural irrigation modifies the drought thresholds for croplands in the Sichuan Basin. For future projections, Earth System Models predict that more regions in China will face an increasing risk for ecological drought, and the Hexi Corridor-Hetao Plain and Shandong Peninsula will become hotspots of ecological drought. This study has important implications for accurately evaluating the impacts of drought on vegetation growth in China and provides a scientific reference for the effective ecomanagement of China's terrestrial ecosystems.

Enhanced growth resistance but no decline in growth resilience under long-term extreme droughts

The frequency, intensity, and duration of extreme droughts, with devastating impacts on tree growth and survival, have increased with climate change over the past decades. Assessing growth resistance and resilience to drought is a crucial prerequisite for understanding the responses of forest functioning to drought events. However, the responses of growth resistance and resilience to extreme droughts with different durations across different climatic zones remain unclear. Here, we investigated the spatiotemporal patterns in growth resistance and resilience in response to extreme droughts with different durations during 1901-2015, relying on tree-ring chronologies from 2389 forest stands over the mid- and high-latitudinal Northern Hemisphere, species-specific plant functional traits, and diverse climatic factors. The findings revealed that growth resistance and resilience under 1-year droughts were higher in humid regions than in arid regions. Significant higher growth resistance was observed under 2-year droughts than under 1-year droughts in both arid and humid regions, while growth resilience did not show a significant difference. Temporally, tree growth became less resistant and resilient to 1-year droughts in 1980-2015 than in 1901-1979 in both arid and humid regions. As drought duration lengthened, the predominant impacts of climatic factors on growth resistance and resilience weakened and instead foliar economic traits, plant hydraulic traits, and soil properties became much more important in both climatic regions; in addition, such trends were also observed temporally. Finally, we found that most of the Earth system models (ESMs) used in this study overestimated growth resistance and underestimated growth resilience under both 1-year and 2-year droughts. A comprehensive ecophysiological understanding of tree growth responses to longer and intensified drought events is urgently needed, and a specific emphasis should be placed on improving the performance of ESMs.

An evaluation framework for quantifying vegetation loss and recovery in response to meteorological drought based on SPEI and NDVI

Drought affects vegetation growth to a large extent. Understanding the dynamic changes of vegetation during drought is of great significance for agricultural and ecological management and climate change adaptation. The relations between vegetation and drought have been widely investigated, but how vegetation loss and restoration in response to drought remains unclear. Using the standardized precipitation evapotranspiration index (SPEI) and the normalized difference vegetation index (NDVI) data, this study developed an evaluation framework for exploring the responses of vegetation loss and recovery to meteorological drought, and applied it to the humid subtropical Pearl River basin (PRB) in southern China for estimating the loss and recovery of three vegetation types (forest, grassland, cropland) during drought using the observed NDVI changes. Results indicate that vegetation is more sensitive to drought in high-elevation areas (lag time < 3 months) than that in low-elevation areas (lag time > 8 months). Vegetation loss (especially in cropland) is found to be more sensitive to drought duration than drought severity and peak. No obvious linear relationship between drought intensity and the extent of vegetation loss is found. Regardless of the intensity, drought can cause the largest probability of mild loss of vegetation, followed by moderate loss, and the least probability of severe loss. Large spatial variability in the probability of vegetation loss and recovery time is found over the study domain, with a higher probability (up to 50 %) of drought-induced vegetation loss and a longer recovery time (>7 months) mostly in the high-elevation areas. Further analysis suggests that forest shows higher but cropland shows lower drought resistance than other vegetation types, and grassland requires a shorter recovery time (4.2-month) after loss than forest (5.1-month) and cropland (4.8-month).

The strengthened impact of water availability at interannual and decadal time scales on vegetation GPP

Water availability (WA) is a key factor influencing the carbon cycle of terrestrial ecosystems under climate warming, but its effects on gross primary production (EWA-GPP ) at multiple time scales are poorly understood. We used ensemble empirical mode decomposition (EEMD) and partial correlation analysis to assess the WA-GPP relationship (RWA-GPP ) at different time scales, and geographically weighted regression (GWR) to analyze their temporal dynamics from 1982 to 2018 with multiple GPP datasets, including near-infrared radiance of vegetation GPP, FLUXCOM GPP, and eddy covariance-light-use efficiency GPP. We found that the 3- and 7-year time scales dominated global WA variability (61.18% and 11.95%), followed by the 17- and 40-year time scales (7.28% and 8.23%). The long-term trend also influenced 10.83% of the regions, mainly in humid areas. We found consistent spatiotemporal patterns of the EWA-GPP and RWA-GPP with different source products: In high-latitude regions, RWA-GPP changed from negative to positive as the time scale increased, while the opposite occurred in mid-low latitudes. Forests had weak RWA-GPP at all time scales, shrublands showed negative RWA-GPP at long time scales, and grassland (GL) showed a positive RWA-GPP at short time scales. Globally, the EWA-GPP , whether positive or negative, enhanced significantly at 3-, 7-, and 17-year time scales. For arid and humid zones, the semi-arid and sub-humid zones experienced a faster increase in the positive EWA-GPP , whereas the humid zones experienced a faster increase in the negative EWA-GPP . At the ecosystem types, the positive EWA-GPP at a 3-year time scale increased faster in GL, deciduous broadleaf forest, and savanna (SA), whereas the negative EWA-GPP at other time scales increased faster in evergreen needleleaf forest, woody savannas, and SA. Our study reveals the complex and dynamic EWA-GPP at multiple time scales, which provides a new perspective for understanding the responses of terrestrial ecosystems to climate change.

Differential responses of crop yields to multi-timescale drought in mainland China: Spatiotemporal patterns and climate drivers

Increasingly frequent and severe droughts pose a growing threat to food security in China. However, our understanding of how different crops respond to multi-timescale drought under varying climatic conditions remains limited, hindering effective drought risk management. To address this knowledge gap, we applied spatial principal component analysis (SPCA) to unveil spatiotemporal patterns in annual yields of major grain crops (rice, wheat, maize) and cotton in response to multi-timescale drought, as indicated by the standardized precipitation evapotranspiration index (SPEI) across China. Subsequently, predictive discriminant analysis (PDA) was employed to identify the primary climatic factors driving these response patterns. The findings indicated that drought-induced interannual variability of crop yields were spatially and temporally heterogeneous, closely tied to the timescale used for drought assessment. Crop types displayed distinct responses to drought, evident in the variations of months and corresponding timescales for their strongest reactions. The initial three principal components, capturing over 65 % of drought-related yield variance, unveiled short- to medium-term patterns for rice, maize, and cotton, and long-term patterns for wheat. Specifically, rice was highly susceptible to drought on a 4-month timescale in September, wheat on a 6-month timescale in May, maize on a 3-month timescale in August, and cotton on a 3-month timescale in September. Moreover, the first three discriminant functions explaining over 90 % of the total variance, effectively distinguish spatiotemporal crop yield response patterns to drought. These patterns primarily stem from seasonal climatic averages, with water balance (precipitation minus potential evapotranspiration) and temperature being the most influential variables (p < 0.05). Interestingly, we observed a weak correlation between drought severity and crop yield in humid conditions, with responses tending to manifest over longer timescales. These findings enhance our comprehension of how drought timescales impact crop yields in China, providing valuable insights for the implementation of rational irrigation management strategies.

Divergent impacts of VPD and SWC on ecosystem carbon-water coupling under different dryness conditions

Ecosystem water use efficiency (WUE) is an indicator of carbon-water interactions and is defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET). However, it is currently unclear how WUE responds to atmospheric and soil drought events in terrestrial ecosystems with different dryness conditions. Additionally, the contributions of GPP and ET to the WUE response remain poorly understood. Based on measurements from 26 flux tower sites distributed worldwide, the binning method and random forest model were employed to separate the sensitivities of daily ecosystem WUE, GPP, and ET to vapor pressure deficit (VPD) and soil water content (SWC) under different dryness conditions (dryness index = potential evapotranspiration/precipitation, DI). Results showed that the sensitivity of WUE to VPD was negative at humid sites (DI < 1), while the sensitivity of WUE to SWC was positive at arid sites (DI > 2). Furthermore, the contribution of GPP to VPD-induced WUE variability was 63 % at humid sites, and the contribution of ET to SWC-induced WUE variability was 68 % when SWC was less than the 60th percentile at arid sites. Consequently, one increasing VPD-induced decrease in GPP was generally linked to a decrease in WUE at humid sites, and one drying soil moisture-caused decrease in ET was linked to a WUE increase under low SWC conditions at arid sites. Finally, VPD had a stronger effect on WUE than SWC when VPD was less than the 90th percentile or SWC was greater than the 50th percentile. Our findings underscore the importance of considering ecosystem dryness when investigating the impacts of VPD and SWC on ecosystem carbon-water coupling.

The role of satellite remote sensing in mitigating and adapting to global climate change

Climate change has critical adverse impacts on human society and poses severe challenges to global sustainable development. Information on essential climate variables (ECVs) that reflects the substantial changes that have occurred on Earth is critical for assessing the influence of climate change. Satellite remote sensing (SRS) technology has led to a new era of observations and provides multiscale information on ECVs that is independent of in situ measurements and model simulations. This enhances our understanding of climate change from space and supports policy-making in combating climate change. However, it remains challenging to remotely retrieve ECVs due to the complexity of the climate system. We provide an update on the studies on the role of SRS in climate change research, specifically in monitoring and quantifying ECVs in the atmosphere (greenhouse gases, clouds and aerosols), ocean (sea surface temperature, sea ice melt and sea level rise, ocean currents and mesoscale eddies, phytoplankton and ocean productivity), and terrestrial ecosystems (land use and land cover change and carbon flux, water resource and hydrological hazards, solar-induced chlorophyll fluorescence and terrestrial gross primary production). The benefits and challenges of applying SRS in climate change studies are also examined and discussed. This work will help us apply SRS and recommend future SRS studies to mitigate and adapt to global climate change.

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.

Forgotten giants: Robust climate signal in pollarded trees

Tree ring records are among the most valuable resources to create high-resolution climate reconstructions. Most climate reconstructions are based on old trees growing in inaccessible mountainous areas with low human activity. Therefore, reconstruction of climate conditions in lowlands is usually based on data from distant mountains. Albeit old trees can be common in humanized areas, they are not used for climate reconstructions. Pollarding was a common traditional management in Europe that enabled trees to maintain great vitality for periods exceeding the longevity of unmanaged trees. We evaluate the potential of pollarded deciduous oaks to record past climate signal. We sampled four pollarded woodlands in Central Spain under continental Mediterranean climate. We hypothesized that pollarded trees have a strong response to water availability during current period without pollarding management, but also in the period under traditional management if pruning was asynchronous among trees. Moreover, we hypothesized that if climate is a regional driver of oak secondary growth, chronologies from different woodlands will be correlated. Pollard oaks age exceeded 500 years with a strong response to Standardized Precipitation-Evapotranspiration Index (SPEI) from 9 to 11 months. Climate signal was exceptionally high in three of the sites (r2 = 0.443-0.655) during low management period (1962-2022). The largest fraction of this climate signal (≈70 %) could be retrieved during the traditional management period (1902-1961) in the three sites where pollarding was asynchronous. Chronologies were significantly correlated since the 19th century for all the studied period, highlighting a shared climate forcing. We identified critical points to optimize pollard tree sampling schema. Our results show the enormous potential of pollarded woodlands to reconstruct hydroclimate conditions in the Mediterranean with a fine spatial grain. Studying pollarded trees is an urgent task, since the temporal window to retrieve the valuable information in pollarded trees is closing as these giants collapse and their wood rots.

Climate-dependent responses of root and shoot biomass to drought duration and intensity in grasslands-a meta-analysis

Understanding the effects of altered precipitation regimes on root biomass in grasslands is crucial for predicting grassland responses to climate change. Nonetheless, studies investigating the effects of drought on belowground vegetation have produced mixed results. In particular, root biomass under reduced precipitation may increase, decrease or show a delayed response compared to shoot biomass, highlighting a knowledge gap in the relationship between belowground net primary production and drought. To address this gap, we conducted a meta-analysis of nearly 100 field observations of grassland root and shoot biomass changes under experimental rainfall reduction to disentangle the main drivers behind grassland responses to drought. Using a response-ratio approach we tested the hypothesis that water scarcity would induce a decrease in total biomass, but an increase in belowground biomass allocation with increased drought length and intensity, and that climate (as defined by the aridity index of the study location) would be an additional predictor. As expected, meteorological drought decreased root and shoot biomass, but aboveground and belowground biomass exhibited contrasting responses to drought duration and intensity, and their interaction with climate. In particular, drought duration had negative effects on root biomass only in wet climates while more intense drought had negative effects on root biomass only in dry climates. Shoot biomass responded negatively to drought duration regardless of climate. These results show that long-term climate is an important modulator of belowground vegetation responses to drought, which might be a consequence of different drought tolerance and adaptation strategies. This variability in vegetation responses to drought suggests that physiological plasticity and community composition shifts may mediate how climate affects carbon allocation in grasslands, and thus ultimately carbon storage in soil.

Drought sensitivity in mesic forests heightens their vulnerability to climate change

Climate change is shifting the structure and function of global forests, underscoring the critical need to predict which forests are most vulnerable to a hotter and drier future. We analyzed 6.6 million tree rings from 122 species to assess trees' sensitivity to water and energy availability. We found that trees growing in wetter portions of their range exhibit the greatest drought sensitivity. To test how these patterns of drought sensitivity influence vulnerability to climate change, we predicted tree growth through 2100. Our results suggest that drought adaptations in arid regions will partially buffer trees against climate change. By contrast, trees growing in the wetter, hotter portions of their climatic range may experience unexpectedly large adverse impacts under climate change.

Diverse responses of gross primary production and leaf area index to drought on the Mongolian Plateau

Drought is a crucial factor regulating vegetation growth on the Mongolian Plateau (MP). Previous studies of drought effects on the MP have mainly concentrated on drought characterization, while the response of vegetation to drought remains unclear. To close this knowledge gap, we examined the response of MP vegetation to drought in terms of gross primary production (GPP) and leaf area index (LAI) from 1982 to 2018. Our findings show that intra-seasonally the frequency of drought occurrence in autumn had a greater impact on GPP (relative importance over 70 %), while the intensity of drought was more influential for LAI (relative importance approximately 60 %). Inter-seasonally, summer droughts had the most pronounced effect on vegetation (with median standardized anomalies of -0.72 for GPP and -0.4 for LAI, respectively). Additionally, we found that meteorological drought was more consistent with atmospheric aridity (high vapor pressure deficit) than soil drought (low soil moisture). This study advances knowledge of vegetation's susceptibility to climate extremes and improves the precision of predicting ecosystem response to climate change.

Advanced time-lagged effects of drought on global vegetation growth and its social risk in the 21st century

Extensive studies have demonstrated the restricting effect of past and present drought conditions on vegetation growth over the past three decades. However, the underlying mechanism of the impact of prior drought on vegetation growth - along with the magnitude of its impact over the rest of the 21st century - remains uncertain. Herein, we examined the evolution and characteristics of global vegetation growth and drought for both baseline (1982-2014) and future (2015-2100) periods under four representative pathways using the gross primary productivity (GPP) and the Standardized Precipitation Evapotranspiration Index from the CMIP6. Further, we investigated the time-lagged effects of drought on vegetation growth and the intensity of population and economy exposure to drought by identifying drought-threatened areas under four emission scenarios. The results show that, at the end of the 21st century, the global terrestrial GPP will experience an increasing trend under four scenarios, especially in SSP5-8.5, with a growth rate of 0.032 kg C m-2/decade, which is 10 times higher than that in SSP1-2.6. From the SSP1-2.6 to the SSP5-8.5 scenario, the SPEI change rates are -0.03, -0.01, -0.017, and -0.018/decade, respectively, indicating that the intensity of global drought events will rise with increases in CO2 emissions. 28.3%, 24.7%, 30.4%, and 35% of global land exhibit downward mean time-lagged months in four scenarios, especially in the middle-high latitudes of the northern hemisphere (>45°N), indicating an advanced response of vegetation to drought. Nearly 8, 9.1, 12.9, and 11.5 billion people - valued at 94,138 (SSP1-2.6), 976,020 (SSP2-4.5), 526,595 (SSP3-7.0), and 204,728 (SSP5-8.5) billion US$, respectively - will be threatened by continuous drought. Globally, the population and economy exposure to moderate and extreme drought zones is larger, and the economic risk from extreme droughts is 8 times greater under the high emissions scenario than the low emissions scenario.

Plants alter their aboveground and belowground biomass allocation and affect community-level resistance in response to snow cover change in Central Asia, Northwest China

It is important to elucidate the changing distribution pattern of net primary productivity (NPP) to mechanistically understand the changes in aboveground and belowground ecosystem functions. In water-scarce desert environments, snow provides a crucial supply of water for plant development and the spread of herbaceous species. Yet uncertainty persists regarding how herbaceous plants' NPP allocation responds to variation in snow cover. The goal of this study was to investigate how variation in snow cover in a temperate desert influenced the NPP allocation dynamics of herbaceous species and their resistance to environmental change in terms aboveground and belowground productivity. In the Gurbantunggut Desert, wintertime snow cover depth was adjusted in plots by applying four treatments: snow removal (-S), ambient snow, double snow (+S), and triple snow (+2S). We examined their species richness, aboveground NPP (ANPP), belowground NPP (BNPP), and the resistance of ANPP and BNPP. We found that species diversity of the aboveground community increased significantly with increasing snow cover and decreased significantly Pielou evenness in plots. This resulted in greater ANPP with increasing snow cover; meanwhile, BNPP first increased and then decreased with increasing snow cover. However, this productivity in different soil layers responded differently to changed snow cover. In the 0-10 cm soil layer, productivity first rose and then declined, while it declined linearly in both the 10-20 cm and 20-30 cm soil layers, whereas in the 30-40 cm soil layer it showed an increasing trend. Belowground resistance would increase given that greater snow cover improved the BNPP in deeper soil and maintained the resource provisioning for plant growth, thus improving overall belowground stability. These results can serve as a promising research foundation for future work on how the functioning of desert ecosystems becomes altered due to changes in plant community expansion and, in particular, changes in snow cover driven by global climate change.

A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022

Droughts cause multiple ecological and social damages. Drought indices are key tools to quantify drought severity, but they are mainly limited to timescales of monthly or longer. However, shorter-timescale (e.g., daily) drought indices enable more accurate identification of drought characteristics (e.g., onset and cessation time) and help timely potential mitigation of adverse effects. Here, we propose a dataset of a daily drought index named daily evapotranspiration deficit index (DEDI), which is produced for global land areas from 1979 to 2022 using actual and potential evapotranspiration data. Validation efforts show that the DEDI dataset can well identify dry and wet variations in terms of spatial patterns and temporal evolutions when compared with other available drought indices on a daily scale. The dataset also has the capability to capture recent drying trends and to detect ecology- or agriculture-related droughts. Overall, the DEDI dataset is a step forward in facilitating drought monitoring and early warning at higher temporal resolution than other compared existing products.

Spatial assessment of sediment risk with integrated entropy-based WASPAS and fuzzy clustering methods in Turkey: impact of forestry activities and meteorological factors

The sediment formed during erosion processes is acknowledged as one of the important contributors to environmental damage. In forest areas, sediment production occurs as a result of meteorological factors and wood harvesting, as well as forest road construction activities carried out for the continuity of forests. In this context, the aim of the study is to reveal the sediment risk in forest areas at the provincial level in Turkey by using entropy-based weighted aggregated sum product assessment (WASPAS) and fuzzy clustering methods. The results establish that the weights of the factors affecting the sediment risk are the forest road construction rate (0.3721), the wood harvesting rate (0.3463), the average precipitation (0.2227), and the average temperature (0.0587). Seven provinces were found in the highest risk class of the cluster in terms of sediment risk. Two of those (Yalova and Kocaeli) are located in the Marmara Region, while the others (Bartın, Düzce, Giresun, Ordu, and Zonguldak) are located in the Black Sea Region. Four of the provinces in the lowest risk class of the cluster (Bingöl, Bitlis, Erzincan, and Malatya) are located in the Eastern Anatolia Region, while a fifth (Siirt) is located in the Southeastern Anatolia Region. As is seen in the study, multi-criteria decision-making methods make it possible to evaluate different scenarios for sedimentation estimation and control and to select the most effective solutions. In conclusion, the use of WASPAS, entropy, and fuzzy clustering methods can provide a comprehensive and effective approach for assessing the sediment risk.

The impact of ecological restoration on ecosystem services change modulated by drought and rising CO2

Ecological restoration projects (ERPs) are an indispensable component of natural climate solutions and have proven to be very important for reversing environmental degradation in vulnerable regions and enhancing ecosystem services. However, the level of enhancement would be inevitably influenced by global drought and rising CO2 , which remain less investigated. In this study, we took the Beijing-Tianjin sand source region (which has experienced long-term ERPs), China, as an example and combined the process-based Biome-BGCMuSo model to set multiple scenarios to address this issue. We found ERP-induced carbon sequestration (CS), water retention (WR), soil retention (SR), and sandstorm prevention (SP) increased by 22.21%, 2.87%, 2.35%, and 28.77%, respectively. Moreover, the ecosystem services promotion from afforestation was greater than that from grassland planting. Approximately 91.41%, 98.13%, and 64.51% of the increased CS, SR, and SP were contributed by afforestation. However, afforestation also caused the WR to decline. Although rising CO2 amplified ecosystem services contributed by ERPs, it was almost totally offset by drought. The contribution of ERPs to CS, WR, SR, and SP was reduced by 5.74%, 32.62%, 11.74%, and 14.86%, respectively, under combined drought and rising CO2 . Our results confirmed the importance of ERPs in strengthening ecosystem services provision. Furthermore, we provide a quantitative way to understand the influence rate of drought and rising CO2 on ERP-induced ecosystem service dynamics. In addition, the considerable negative climate change impact implied that restoration strategies should be optimized to improve ecosystem resilience to better combat negative climate change impacts.

The Mechanism by Which Umbrella-Shaped Ratchet Trichomes on the Elaeagnus angustifolia Leaf Surface Collect Water and Reflect Light

Leaves are essential for plants, enabling photosynthesis and transpiration. In arid regions, water availability limits plant growth. Some plants, like Elaeagnus angustifolia, a sandy sub-tree species widely distributed in arid and semi-arid regions, have unique leaf structures to reduce water loss and solar radiation. Here, we describe the leaves of Elaeagnus angustifolia L., with special functioning trichomes. Through leaf submicroscopic structure observation, in situ water collection experiments, photosynthesis measurements, and reflection spectrum analysis, we investigated E. angustifolia leaves, focusing on their functioning trichomes. These trichomes capture water vapor, reflect UV and NIR light, and possess a 3D interface structure composed of 1D and 2D structures. The 1D conical structure captures water droplets, which are then gathered by the radial conical structure and guided towards the stomata through wedge-shaped grooves on the 2D umbrella structure. The trichomes also reflect sunlight, with micropapillae reflecting UV light and the umbrella structure reflecting NIR light. These mechanisms reduce leaf temperature, respiration, and water transpiration, protecting against solar radiation damage. This study provides insights into water collection and light-reflection mechanisms, revealing adaptive strategies of plants with large leaves in arid regions.

Warming influences CO2 emissions from China's coastal saltmarsh wetlands more than changes in precipitation

Coastal wetlands are an important carbon sink but are sensitive to climate changes. The response of CO₂ emissions to these changes differs under different hydroclimatic conditions. Here, this article used meta-analysis to synthesize data from Chinese coastal salt marshes, to analyze sensitivities for CO₂ emissions, and then to assess the relative contributions of air temperature (T_a) and precipitation (Pre). This article used the ratio between potential evaporation (E_p) and Pre to divide Chinese coastal saltmarshes into water- (E_p/Pre > 1) and energy-limited regions (E_p/Pre ≤ 1). Results show that emissions are more sensitive to both Pre and T_a in water-limited regions (E¯ = 0.60 eV, slope = 0.37) than in energy-limited regions (E¯ = 0.23 eV, slope = 0.04). Comparing the relative effects of changes in T_a (△CO₂ = 21.86 mg m^-2 h^-1) and Pre (△CO₂ = 7.19 mg m^-2 h^-1) on CO₂ emissions shows that warming contributes more to changes in CO₂ emissions. The response of emissions to changes in Pre is asymmetric and shows that warmer and drier may have antagonistic effects, while warmer and wetter may have synergistic effects. There was a 2.15 mg m^-2 h^-1 change in emissions in energy-limited regions when Pre increased by 139.69 mm, and a decrease of -0.15 mg m^-2 h^-1 in emissions when Pre decreased by 1.28 mm in water-limited regions. Climate change has the greatest impact on Phragmites australis in CO₂ emissions, especially under warmer and wetter conditions in energy-limited regions. This indicates that warming drives CO₂ emissions, while changes in Pre (resulting in wetter or dryer conditions) can mitigate or strengthen CO₂ emissions from coastal wetlands in China. This article offers a new perspective and suggests that differences in hydroclimatic conditions should be considered when discussing carbon emissions from coastal wetlands.

Riparian forest response to extreme drought is influenced by climatic context and canopy structure

Droughts significantly impact forest ecosystems, reducing forest health and productivity, compromising ecosystem functioning, and nature-based solutions for climate change. The response and resilience of riparian forests to drought are poorly understood despite their key role in the functioning of aquatic and terrestrial ecosystems. Here we investigate riparian forest drought responses and resilience to an extreme drought event at a regional scale. We also examine how drought event characteristics, average climate conditions, topography, soil, vegetation structure, and functional diversity shape the resilience of riparian forests to drought. We used a time series of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) to calculate the resistance to and recovery after an extreme drought (2017-2018) in 49 sites across an Atlantic-Mediterranean climate gradient in North Portugal. We used generalized additive models and multi-model inference to understand which factors best explained drought responses. We found a trade-off between drought resistance and recovery (maximum r = -0.5) and contrasting strategies across the climatic gradient of the study area. Riparian forests in the Atlantic regions showed comparatively higher resistance, while Mediterranean forests recovered more. Canopy structure and climate context were the most relevant predictors of resistance and recovery. However, median NDVI and NDWI had not returned to pre-drought levels (Rc_NDWI mean = 1.21, Rc_NDVI mean = 1.01) three years after the event. Our study shows that riparian forests have contrasting drought response strategies and may be susceptible to extended legacy effects associated with extreme and/or recurring droughts, similarly to upland forests. This work highlights the drought vulnerability of riparian ecosystems and emphasises the need for further studies on long-term resilience to droughts.

Thresholds for triggering the propagation of meteorological drought to hydrological drought in water-limited regions of China

Propagation thresholds that trigger a transition between meteorological drought and hydrological drought are poorly understood, which hinders effective establishment of drought warning systems and prevention measures. Here, propagation thresholds were assessed by firstly identifying drought events during 1961-2016 in the Yellow River Basin, China, subsequently pooling, excluding, and matching them, and finally assessing their threshold conditions by using a combined Copula function and transition rate (T_r) analysis. These results show that response time changed according to variations in drought duration and watershed characteristics. Importantly, response times increased according to the timescales over which they were studied; for example, the Wenjiachuan watershed recorded response times of 8, 10, 10, and 13 months when examined at 1-, 3-, 6-, and 12-month timescales, respectively. Additionally, the severity and duration of meteorological and hydrological drought events both increased when events were combined rather than studied individually. These effects were also amplified for matched meteorological and hydrological droughts by factors of 1.67 (severity) and 1.45 (duration), respectively. Shorter response times were identified in the Linjiacun (LJC) and Zhangjiashan (ZJS) watersheds, and correlated with their relatively small T_r values of 43 % and 47 %, respectively. Higher propagation thresholds for drought characteristics (e.g., 1.81 and 1.95 for drought severity in the LJC and ZJS watersheds, respectively) imply that shorter response times tended to have greater effects on hydrological drought events and lowered their T_r, and vice versa. These results provide new insight into propagation thresholds used for water resource planning and management, and may help to mitigate the effects of future climate change.

Simulation of future land use/cover change (LUCC) in typical watersheds of arid regions under multiple scenarios

The rapid development of the social economy has promoted a continuous increase in the intensity and scale of land use by humans, which has seriously affected the sustainable development of the region. It is important to understand the land use/cover change (LUCC) in the arid region and its future development trends and to make reasonable planning recommendations for the sustainable development of the ecological environment. This study validates the patch-generating land use simulation (PLUS) model in a typical arid region, the Shiyang River Basin (SRB), and analyzes the applicability of the model in arid regions. On this basis, the PLUS model is combined with the scenario analysis method to design four scenarios including no policy intervention, farmland protection, ecological protection and sustainable development to analyze the dynamic changes in past and future land use in the SRB and to make corresponding planning recommendations for the development of each type of land use in the arid region. The results showed that the PLUS model had a better simulation effect in the SRB (its overall accuracy reached 0.97). Coupled models obtain better simulation results than quantitative and spatial models by comparing the mainstream models, with PLUS model that combines CA model and patch generation strategy showing better simulation results in the same category. From 1987 to 2017, the spatial centroid of each LUCC in the SRB moved to varying degrees due to a continuous increase in human activities. The spatial centroid of water bodies had the most obvious change, with a moving speed of 1.49 km/a, while the moving speed of built-up land increased year by year. The spatial centroid of farmland, built-up land and unused land all shifted toward the middle and lower plains, which is a further indication of increased human activity. Due to different government policies, the development trend of land use was also different under different scenarios. However, the four scenarios all showed that the area of built-up land will be increasing exponentially from 2017 to 2037, which would seriously affect the surrounding ecological land and have a negative impact on the local agro-ecological environment. Therefore, we proposed the following planning recommendations: (1) Land leveling work should be carried out on scattered farmland located at high altitudes and with slopes over 25°. Additionally, the land use of low-altitude areas should strictly adhere to basic farmland, increase the diversification of cropping patterns and improve the efficiency of agricultural water. (2) The relationship between ecology, farmland and cities should be reasonably coordinated and the existing idle built-up land should be efficiently used. (3) Forestland and grassland resources should be strictly protected and the ecological redline should be strictly observed. This study can provide new ideas for LUCC modeling and prediction in other parts of the world and provide a strong basis for ecological management and sustainable development in arid areas.

An improved global vegetation health index dataset in detecting vegetation drought

Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic wildfires, and have seriously affected socio-economic development and agricultural production. In this study, a global long-term (1981-2021), high-resolution (4 km) improved vegetation health index (VHI) dataset integrating climate, vegetation and soil moisture was developed. Based on drought records from the Emergency Event Database, we compared the detection efficiency of the VHI before and after its improvement in the occurrence and scope of observed drought events. The global drought detection efficiency of the improved high-resolution VHI dataset reached values as high as 85%, which is 14% higher than the original VHI dataset. The improved VHI dataset was also more sensitive to mild droughts and more accurate regarding the extent of droughts. This improved dataset can play an important role in long-term drought monitoring but also has the potential to assess the impact of drought on the agricultural, forestry, ecological and environmental sectors.

Identification and prediction of climate factors based on factor analysis and a grey prediction model in China

Identifying and predicting the impacts of climate change are crucial for various purposes, such as maintaining biodiversity, agricultural production, ecological security, and environmental conservation in different regions. In this paper, we used the surface pressure (SP), surface temperature (ST), 2-m air temperature (AT), 2-m dewpoint temperature (DT), 10-m wind speed (WS), precipitation (PRE), relative humidity (RH), actual evapotranspiration (ET_a), potential evapotranspiration (ET_P), total solar radiation (TRs), net solar radiation (NRs), UV intensity (UVI), sunshine duration (SD), convective available potential energy (CAPE) as factors in our climate modeling. The spatiotemporal distribution characteristics of the climate factors were analyzed and identified based on historical data for China from 1950 to 2020 using factor analysis and a grey model (GM (1,1)), and their future change characteristics were predicted. The results show that there is a strong correlation between climate factors. ST, AT, DT, PRE, RH, and ET_a are the main factors that have the potential to cause heavy rain, thunderstorms, and other severe weather. Meanwhile, PRE, RH, TR_s, NR_s, UVI, and SD are among the major factors linked to climate change. Specifically, SP, ST, AT, and WS are among the minor factors in most areas. The top ten provinces in terms of combined factor scores are Heilongjiang, Neimenggu, Qinghai, Beijing, Shandong, Xizang, Shanxi, Tianjin, Guangdong, and Henan. The trend of climate factors in China is expected to remain relatively stable over the next 30 years, with a noteworthy decrease observed in CAPE compared to the past 71 years. Our findings can help to better mitigate the risks associated with climate change and enhance resilience; they also provide a scientific basis for environmental, ecological, and agricultural systems to cope with climate change.

Long-term evidence of differential resistance and resilience of grassland ecosystems to extreme climate events

Grassland ecosystems are affected by the increasing frequency and intensity of extreme climate events (e.g., droughts). Understanding how grassland ecosystems maintain their functioning, resistance, and resilience under climatic perturbations is a topic of current concern. Resistance is the capacity of an ecosystem to withstand change against extreme climate, while resilience is the ability of an ecosystem to return to its original state after a perturbation. Using the growing season Normalized Difference Vegetation Index (NDVI_gs, an index of vegetation growth) and the Standardized Precipitation Evapotranspiration Index (a drought index), we evaluated the response, resistance, and resilience of vegetation to climatic conditions for alpine grassland, grass-dominated steppe, hay meadow, arid steppe, and semi-arid steppe in northern China for the period 1982-2012. The results show that NDVI_gs varied significantly across these grasslands, with the highest (lowest) NDVI_gs values in alpine grassland (semi-arid steppe). We found increasing trends of greenness in alpine grassland, grass-dominated steppe, and hay meadow, while there were no detectable changes of NDVI_gs in arid and semi-arid steppes. NDVI_gs decreased with increasing dryness from extreme wet to extreme dry. Alpine and steppe grasslands exhibited higher resistance to and lower resilience after extreme wet, while lower resistance to and higher resilience after extreme dry conditions. No significant differences in resistance and resilience of hay meadow under climatic conditions suggest the stability of this grassland under climatic perturbations. This study concludes that highly resistant grasslands under conditions of water surplus are low resilient, but low resistant ecosystems under conditions of water shortage are highly resilient.

Effects of climate change on vegetation dynamics of the Qinghai-Tibet Plateau, a causality analysis using empirical dynamic modeling

Given the vital role of the Qinghai-Tibet Plateau (QTP) as water tower in Asia and regulator for regional and even global climate, the relationship between climate change and vegetation dynamics on it has received considerable focused attention. Climate change may influence the vegetation growth on the plateau, but clear empirical evidence of such causal linkages is sparse. Herein, using datasets CRU-TS v4.04 and AVHHR NDVI from 1981 to 2019, we quantify causal effects of climate factors on vegetation dynamics with an empirical dynamical model (EDM) -- a nonlinear dynamical systems analysis approach based on state-space reconstruction rather than correlation. Results showed the following: (1) climate change promotes the growth of vegetation on the QTP, and specifically, this favorable influence of temperature is stronger than precipitation's; (2) the direction and strength of climate effects on vegetation varied over time, and the effects are seasonally different; (3) a significant increase in temperature and a slight increase in precipitation are beneficial to vegetation growth, specifically, NDVI will increase within 2% in the next 40 years with the climate trend of warming and humidity. Besides the above results, another interesting finding is that the two seasons in which precipitation strongly influence vegetation in the Three-River Source region (part of the QTP) are spring and winter. This study provides insights into the mechanisms by which climate change affects vegetation growth on the QTP, aiding in the modeling of vegetation dynamics in future scenarios.

Animal conflicts escalate in a warmer world

The potential for climate change to affect animal behaviour is widely recognized, yet its possible consequences on aggressiveness are still unclear. If warming and drought limit the availability of food resources, climate change may elicit an increase of intraspecific conflicts stemming from resource competition. By measuring aggressivity indices in a group-living, herbivorous mammal (the Apennine chamois Rupicapra pyrenaica ornata) in two sites differing in habitat quality, and coupling them with estimates of plant productivity, we investigated whether harsh climatic conditions accumulated during the growing season influenced agonistic contests at feeding via vegetation-mediated effects, and their interaction with the site-specific habitat quality. We focused on females, which exhibit intra-group contest competition to access nutritious food patches. Accounting for confounding variables, we found that (1) the aggression rate between foraging individuals increased with the warming accumulated over previous weeks; (2) the probability to deliver more aggressive behaviour patterns toward contestants increased with decreasing rainfall recorded in previous weeks; (3) the effects of cumulative warming and drought on aggressivity indices occurred at time windows spanning 15-30 days, matching those found on vegetation productivity; (4) the effects of unfavourable climatic conditions via vegetation growth on aggressivity were independent of the site-specific habitat quality. Simulations conducted on our model species predict a ~50 % increase in aggression rate following the warming projected over the next 60 years. Where primary productivity will be impacted by warming and drought, our findings suggest that the anticipated climate change scenarios may trigger bottom-up consequences on intraspecific animal conflicts. This study opens the doors for a better understanding of the multifactorial origin of aggression in group-living foragers, emphasising how the escalation of agonistic contests could emerge as a novel response of animal societies to ongoing global warming.