Search Results (267)

Drought disturbances are becoming more frequent with global warming. Accurately assessing the regulatory effect of drought on vegetation phenology is key to understanding terrestrial ecosystem response mechanisms in the context of climate change. Previous studies on cumulative and lagged effects of drought on vegetation growth have mostly focused on a single vegetation type or the overall vegetation NDVI, overlooking the possible influence of different adaptation strategies of different vegetation types and differences in drought effects on different phenological nodes. This study investigates the cumulative and lagged effects of drought on vegetation phenology across a region of East Asia from 2001 to 2020 using NDVI data and the Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the start of growing season (SOS) and end of growing season (EOS) responses to drought across four vegetation types: deciduous needleleaf forests (DNFs), deciduous broadleaf forests (DBFs), shrublands, and grasslands. Results reveal contrasting phenological responses: drought delayed SOS in grasslands through a “drought escape” strategy but advanced SOS in forests and shrublands. All vegetation types showed earlier EOS under drought stress. Cumulative drought effects were strongest on DNFs, SOS, and shrubland SOS, while lagged effects dominated DBFs and grassland SOS. Drought impacts varied with moisture conditions: they were stronger in dry regions for SOS but more pronounced in humid areas for EOS. By confirming that drought effects vary by vegetation type and phenology node, these findings enhance our understanding of vegetation adaptation strategies and ecosystem responses to climate stress. Full article

Climate change is generally having a negative impact on forest health by inducing drought stress and favouring the spread of pest species, such as bark beetles. The terrestrial monitoring of bark beetle infestation is very time-consuming, especially in the early stages, and therefore not feasible for extensive areas, emphasising the need for a comprehensive approach based on remote sensing. Although numerous studies have researched the use of optical data for this task, radar data remains comparatively underexplored. Therefore, this study uses the weekly and cloud-free acquisitions of Sentinel-1 in the Bavarian Forest National Park. Time series analysis within a Multi-SAR framework using Random Forest enables the monitoring of moisture content loss and, consequently, the assessment of tree vitality, which is crucial for the detection of stress conditions conducive to bark beetle outbreaks. High accuracies are achieved in predicting future bark beetle infestation (R² of 0.83–0.89). These results demonstrate that forest vitality trends ranging from healthy to bark beetle-affected states can be mapped, supporting early intervention strategies. The standard deviation of 0.44 to 0.76 years indicates that the model deviates on average by half a year, mainly due to the uncertainty in the reference data. This temporal uncertainty is acceptable, as half a year provides a sufficient window to identify stressed forest areas and implement targeted management actions before bark beetle damage occurs. The successful application of this technique to extensive test sites in the state of North Rhine-Westphalia proves its transferability. For the first time, the results clearly demonstrate the expected relationship between radar backscatter expressed in the Kennaugh elements K₀ and K₁ and bark beetle infestation, thereby providing an opportunity for the continuous and cost-effective monitoring of forest health from space. Full article

The Inner Mongolia Plateau (IMP), situated in the arid and semi-arid ecological transition zone of northern China, is particularly vulnerable to both climate change and human activities. Understanding the spatiotemporal vegetation dynamics and their driving forces is essential for regional ecological management. This study employs Sen’s slope estimation, BFAST analysis, residual trend method and Geodetector to analyze the spatial patterns of Normalized Difference Vegetation Index (NDVI) variability and distinguish between climatic and anthropogenic influences. Key findings include the following: (1) From 1982 to 2022, vegetation cover across the IMP exhibited a significant greening trend. Zonal analysis showed that this spatial heterogeneity was strongly regulated by regional hydrothermal conditions, with varied responses across land cover types and pronounced recovery observed in high-altitude areas. (2) In the western arid regions, vegetation trends were unstable, often marked by interruptions and reversals, contrasting with the sustained greening observed in the eastern zones. (3) Vegetation growth was primarily temperature-driven in the eastern forested areas, precipitation-driven in the central grasslands, and severely limited in the western deserts due to warming-induced drought. (4) Human activities exerted dual effects: significant positive residual trends were observed in the Hetao Plain and southern Horqin Sandy Land, while widespread negative residuals emerged across the southern deserts and central grasslands. (5) Vegetation change was driven by climate and human factors, with recovery mainly due to climate improvement and degradation linked to their combined impact. These findings highlight the interactive mechanisms of climate change and human disturbance in regulating terrestrial vegetation dynamics, offering insights for sustainable development and ecosystem education in climate-sensitive systems. Full article

Evapotranspiration (ET) crucially regulates water storage dynamics and is an essential component of the terrestrial water cycle. Understanding ET dynamics is fundamental for sustainable water resource management, particularly in regions facing increasing drought risks under climate change. In regions like southwestern China, where extreme drought events are prevalent due to complex terrain and climate warming, ET becomes a key factor in understanding water availability and drought dynamics. Using the SWAT model, this study investigates ET dynamics and influencing factors in the Jizi Basin, Yunnan Province, a small basin with over 71% forest coverage. The model calibration and validation results demonstrated a high degree of consistency with observed discharge data and ERA5, confirming its reliability. The results show that the annual average ET in the Jizi Basin is 573.96 mm, with significant seasonal variations. ET in summer typically ranges from 70 to 100 mm/month, while in winter, it drops to around 20 mm/month. Spring ET exhibits the highest variability, coinciding with the occurrence of extreme hydrological events such as droughts. The monthly anomalies of ET effectively reproduce the spring and early summer 2019 drought event. Notably, ET variation exhibits significant uncertainty under scenarios of +1 °C temperature and −20% precipitation. Furthermore, although land use changes had relatively small effects on overall ET, they played crucial roles in promoting groundwater recharge through enhanced percolation, especially forest cover. The study highlights that, in addition to climate and land use, soil moisture and groundwater conditions are vital in modulating ET and drought occurrence. The findings offer insights into the hydrological processes of small forested basins in southwestern China and provide important support for sustainable water resource management and effective climate adaptation strategies, particularly in the context of increasing drought vulnerability. Full article

As an extreme event driven by global climate change, drought poses a severe threat to terrestrial ecosystems. The Yangtze River Basin (YZRB) and Yellow River Basin (YRB) are key ecological barriers and economic zones in China, holding strategic importance for exploring the evolution of drought patterns and their ecological impacts. Using meteorological station data and Climatic Research Unit Gridded Time Series (CRU TS) data, this study analyzed the spatiotemporal characteristics of drought evolution in the YZRB and YRB from 1961 to 2021 using the standardized precipitation evapotranspiration index (SPEI) and run theory. Additionally, this study examined drought effects on ecosystem carbon sequestration (CS) at the city, county, and pixel scales. The results revealed the following: (1) the CRU data effectively captured precipitation (annual r = 0.94) and temperature (annual r = 0.95) trends in both basins, despite significantly underestimating winter temperatures, with the optimal SPEI calculation accuracy found at the monthly scale; (2) both basins experienced frequent autumn–winter droughts, with the YRB facing stronger droughts, including nine events which exceeded 10 months (the longest lasting 25 months), while the mild droughts increased in frequency and extreme intensity; and (3) the drought impacts on CS demonstrated a significant threshold effect, where the intensified drought unexpectedly enhanced CS in western regions, such as the Garzê Autonomous Prefecture in Sichuan Province and Changdu City in the Xizang Autonomous Region, but suppressed CS in the midstream and downstream plains. The CS responded positively under weak drought conditions but declined once the drought intensity surpassed the threshold. This study revealed a nonlinear relationship between drought and CS across climatic zones, thereby providing a scientific foundation for enhancing ecological resilience. Full article

Climate change intensifies hydrological cycles, leading to an increased variability in terrestrial water storage anomalies (TWSAs) and a heightened drought risk. Understanding the spatiotemporal dynamics of TWSAs and their driving factors is crucial for sustainable water management. While previous studies have primarily attributed TWSAs to regional factors, this study employs wavelet coherence, partial correlation analysis, and multiple linear regression to comprehensively analyze TWSA dynamics and their drivers in the Hengduan Mountains (HDM) region from 2003 to 2022, incorporating both regional and global influences. Additionally, dry–wet variations were quantified using the GRACE-based Drought Severity Index (GRACE-DSI). Key findings include the following: The annual mean TWSA showed a non-significant decreasing trend (−2.83 mm/y, p > 0.05), accompanied by increased interannual variability. Notably, approximately 36.22% of the pixels in the western HDM region exhibited a significantly decreasing trend. The Nujiang River Basin (NRB) (−17.17 mm/y, p < 0.01) and the Lancang (−17.17 mm/y, p < 0.01) River Basin experienced the most pronounced declines. Regional factors—particularly precipitation (PRE)—drove TWSA in 59% of the HDM region, followed by potential evapotranspiration (PET, 28%) and vegetation dynamics (13%). Among global factors, the North Atlantic Oscillation showed a weak correlation with TWSAs (r = −0.19), indirectly affecting it via winter PET (r = −0.56, p < 0.05). The decline in TWSAs corresponds to an elevated drought risk, notably in the NRB, which recorded the largest GRACE-DSI decline (slope = −0.011, p < 0.05). This study links TWSAs to climate drivers and drought risk, offering a framework for improving water resource management and drought preparedness in climate-sensitive mountain regions. Full article

Accurate terrestrial evapotranspiration (ET) estimation is crucial for understanding land–atmosphere interactions, evaluating ecosystem functions, and supporting water resource management, particularly across climatically diverse regions. To address the limitations of traditional ET models, we propose a simple yet robust Sigmoid-RH model that characterizes the nonlinear relationship between relative humidity and ET. Unlike conventional approaches such as the Penman–Monteith or Priestley–Taylor models, the Sigmoid-RH model requires fewer inputs and is better suited for large-scale applications where data availability is limited. In this study, we applied the Sigmoid-RH model to estimate ET over mainland China from 2001 to 2018 by using satellite remote sensing and meteorological reanalysis data. Key driving inputs included air temperature (Ta), net radiation (Rn), relative humidity (RH), and the normalized difference vegetation index (NDVI), all of which are readily available from public datasets. Validation at 20 flux tower sites showed strong performance, with R-square (R²) ranging from 0.26 to 0.93, Root Mean Squard Error (RMSE) from 0.5 to 1.3 mm/day, and Kling-Gupta efficiency (KGE) from 0.16 to 0.91. The model performed best in mixed forests (KGE = 0.90) and weakest in shrublands (KGE = 0.27). Spatially, ET shows a clear increasing trend from northwest to southeast, closely aligned with climatic zones, with national mean annual ET of 560 mm/yr, ranging from less than 200 mm/yr in arid zones to over 1100 mm/yr in the humid south. Seasonally, ET peaked in summer due to monsoonal rainfall and vegetation growth, and was lowest in winter. Temporally, ET declined from 2001 to 2009 but increased from 2009 to 2018, influenced by changes in precipitation and NDVI. These findings confirm the applicability of the Sigmoid-RH model and highlight the importance of hydrothermal conditions and vegetation dynamics in regulating ET. By improving the accuracy and scalability of ET estimation, this model can provide practical implications for drought early warning systems, forest ecosystem management, and agricultural irrigation planning under changing climate conditions. Full article

As an essential part of terrestrial ecosystems, forests are key to sustaining ecological balance, supporting the carbon cycle, and offering various ecosystem services. In recent years, forests in Southwest China have experienced notable greening. However, the rising occurrence and severity of droughts present a significant threat to the stability of forest ecosystems in this region. This study adopted the near-infrared reflectance of vegetation (NIRv) and the lag-1 autocorrelation of NIRv as indicators to assess the dynamics and resilience of forests in Southwest China. We identified a progressive decline in forest resilience since 2008 despite a dominant greening trend in Southwest China’s forests during the last 20 years. By developing the eXtreme Gradient Boosting (XGBoost) model and Shapley additive explanation framework (SHAP), we classified forests in Southwest China into coniferous and broadleaf types to evaluate the driving factors influencing changes in forest resilience and mapped the spatial distribution of dominant drivers. The results showed that the resilience of coniferous forests was mainly driven by variations in elevation and land surface temperature (LST), with mean absolute SHAP values of 0.045 and 0.038, respectively. In contrast, the resilience of broadleaf forests was primarily influenced by changes in photosynthetically active radiation (PAR) and soil moisture (SM), with mean absolute SHAP values of 0.032 and 0.028, respectively. Regions where elevation and LST were identified as dominant drivers were mainly distributed in coniferous forest areas across central, eastern, and northern Yunnan Province as well as western Sichuan Province, accounting for 32.9% and 20.0% of the coniferous forest area, respectively. Meanwhile, areas where PAR and SM were dominant drivers were mainly located in broadleaf forest regions in Sichuan and eastern Guizhou, accounting for 29.9% and 27.7% of the broadleaf forest area, respectively. Our study revealed that the forest greening does not necessarily accompany an enhancement in resilience in Southwest China, identifying the driving factors behind the decline in forest resilience and highlighting the necessity of differentiated restoration strategies for forest ecosystems in this region. Full article

Drought, a natural phenomenon intricately intertwined with the broader canvas of climate change, exacts a heavy toll by ushering in acute terrestrial water scarcity. Its ramifications reverberate most acutely within the agricultural heartlands, particularly those nestled in arid regions. To address this pressing issue, this study harnesses the temperature vegetation dryness index (TVDI) as a robust drought indicator, enabling a granular estimation of land water content trends. This endeavor unfolds through the sophisticated integration of geographic information systems (GISs) and remote sensing technologies (RSTs). The methodology bedrock lies in the judicious utilization of 72 high-resolution satellite images captured by the Landsat 7 and 8 platforms. These images serve as the foundational building blocks for computing TVDI values, a key metric that encapsulates the dynamic interplay between the normalized difference vegetation index (NDVI) and the land surface temperature (LST). The findings resonate with significance, unveiling a conspicuous and statistically significant uptick in the TVDI time series. This shift, observed at a confidence level of 0.05 (Z_S = 1.648), raises a crucial alarm. Remarkably, this notable surge in the TVDI exists in tandem with relatively insignificant upticks in short-term precipitation rates and LST, at statistically comparable significance levels. The implications are both pivotal and starkly clear: this profound upswing in the TVDI within agricultural domains harbors tangible environmental threats, particularly to groundwater resources, which form the lifeblood of these regions. The call to action resounds strongly, imploring judicious water management practices and a conscientious reduction in water withdrawal from reservoirs. These measures, embraced in unison, represent the imperative steps needed to defuse the looming crisis. Full article

Wetlands and meadows are two terrestrial ecosystems that are strikingly distinct in terms of hydrological conditions and biogeochemical characteristics. Wetlands generally feature saturated soils, high accumulation of organic matter, and hypoxic environments. They support unique microbial communities and play crucial roles as carbon sinks and nutrient retainers. In contrast, meadows are characterized by lower water supply, enhanced aeration, and accelerated turnover of organic matter. The transition from wetlands to meadows under global climate change and human activities has triggered severe ecological consequences in the Sanjiangyuan region, yet the mechanisms driving microbial network stability remain unclear. This study integrates microbial sequencing, soil physicochemical analyses, and structural equation modeling (SEM) to reveal systematic changes in microbial communities during wetland degradation. Key findings indicate: (1) critical soil parameter shifts (moisture: 48.5%→19.3%; SOM: −43.6%; salinity: +170%); (2) functional microbial restructuring with drought-tolerant Actinobacteria (+62.8%) and Ascomycota (+48.3%) replacing wetland specialists (Nitrospirota: −43.2%, Basidiomycota: −28.6%); (3) fundamental network reorganization from sparse wetland connections to hypercomplex meadow networks (bacterial nodes +344%, fungal edges +139.2%); (4) SEM identifies moisture (λ = 0.82), organic matter (λ = 0.68), and salinity (λ = −0.53) as primary drivers. Particularly, the collapse of methane-oxidizing archaea (−100%) and emergence of pathogenic fungi (+28.6%) highlight functional thresholds in degradation processes. These findings provide microbial regulation targets for wetland restoration, emphasizing hydrologic management and organic carbon conservation as priority interventions. Future research should assess whether similar microbial and network transitions occur in degraded wetlands across other alpine and temperate regions, to validate the broader applicability of these ecological thresholds. Restoration efforts should prioritize re-saturating soils, reducing salinity, and enhancing organic matter retention to stabilize microbial networks and restore essential ecosystem functions. Full article

Numerous studies have focused on dioecious plants and their sex-specific responses to drought stress. However, sexual dimorphism in drought stress responses between male and female Litsea cubeba, a dioecious species significant to the terrestrial ecosystem in China that is frequently exposed to drought conditions, remains insufficiently characterized. In this study, we examined the sex-specific physiological and biochemical responses of L. cubeba to natural drought stress. The results revealed that natural drought induced significant sexual dimorphism in physiological and biochemical traits of L. cubeba. Females exhibited a higher malondialdehyde (MDA) content than males under prolonged drought conditions; females also exhibited significantly higher catalase (CAT) and peroxidase (POD) activities in both leaves and roots compared to males, with the average CAT and POD activities of all varieties increasing by 104.28% and 23.67% in leaves and 51.17% and 174.57% in roots, respectively. Meanwhile, the dehydrogenase (DHA) activity and chlorophyll (chl) and carotenoid levels of females were higher than those of males. The contents of proline (Pro), soluble sugar (SS), abscisic acid (ABA), and jasmonic acid (JA) in females were significantly higher than those in males. Our results demonstrated that females possess a greater tolerance to natural drought stress than males; this is due to their more efficient antioxidant system, better osmotic adjustment, lower chlorophyll degradation rate, and higher concentrations of ABA and JA, which aid in stomatal closure and facilitate the reactive oxygen species (ROS)-scavenging abilities of females in response to drought stress. Our findings provide evidence that dioecious L. cubeba may adopt distinct survival strategies during natural drought events and enhance our understanding of sexually dimorphic responses to drought stress in L. cubeba. Full article

Drought represents a prevalent abiotic stress in terrestrial plants, frequently impairing crop growth and yield. In this paper, we characterized the functional role of OsNAC25, a member of the NAC transcription factor family, in drought tolerance. OsNAC25 was predominantly localized in both the cytoplasm and nucleus, with its expression being markedly induced under drought conditions. Under severe drought stress, the overexpression of OsNAC25 rice exhibited decreased malondialdehyde (MDA) levels, attenuated oxidative damage, and improved survival rate during the vegetative growth stage. The transcriptome analysis revealed that OsNAC25 coordinates drought response through key pathways associated with phenylpropanoid biosynthesis, plant hormone signal transduction, and diterpenoid biosynthesis. Collectively, our findings highlight OsNAC25 as a pivotal transcriptional regulator governing drought resistance in rice. This study not only provides a candidate gene for improving drought tolerance in rice but also offers valuable insights into the molecular mechanisms underlying drought adaptation in cereal crops. Full article

As a critical region for ecological construction in China, the upper Yellow River is still relatively short of research on the time-lag and cumulative effects of regional-scale drought on vegetation growth. Therefore, based on net primary productivity (NPP) estimated by the improved CASA (Carnegie–Ames–Stanford approach) model and multi-time scale SPEI, trend analysis, significance test and partial correlation analysis were employed to explore the spatial and temporal patterns of NPP and quantitatively evaluate its response to drought. The results showed that (1) From 2001 to 2022, NPP was higher in the south and lower in the north, decreasing from southwest to northeast, and annual NPP was increasing in 87.9% of the regions. NPP in spring, summer and autumn has been significantly improved. (2) In terms of interannual and spatial distribution, except for spring and winter, annual, summer and autumn all showed an insignificant trend of humidification. (3) The lag and cumulative effects of drought on vegetation in most areas are positively correlated. About 82.58% of NPP in the growing season has a time-lag effect with drought, which mainly focuses on 1–2 months. The average lag time was 3.6 months, indicating that NPP had the strongest correlation with the meteorological drought index of the previous 3.6 months. For cumulative effect, about 66.14% of NPP had a cumulative effect on drought, and the cumulative time scales were mainly March, April, November and December. With the worsening of drought conditions, the effect of drought on NPP is enhanced. These findings enhance the understanding of the long-term consequences of drought on terrestrial ecosystems and provide a basis for the development of mitigation and adaptation strategies aimed at alleviating the adverse effects of drought on agriculture and ecosystems. Full article

Trees and forests are nature-based solutions of strategic importance for climate change mitigation. Policy and popular media are focused on the number of trees to plant, but that cannot be a definitive solution. A growing number of scientific papers address the problems concerning tree plantations and forest restoration for climatic purposes. In this review, we analyze ecological limitations and trade-offs to be considered for the realization and management of these interventions. Terrestrial sinks (forests and other terrestrial natural ecosystems) can absorb only a fraction of the carbon emitted, and the establishment of new effective forests is constrained by ecological limitations. Moreover, the stimulation of tree growth due to carbon fertilization is offset by the harshening of ecological conditions due to climate change (higher temperatures beyond the optimum for photosynthesis, increasing drought, and nutritional imbalances). The increase in frequency and severity of disturbances can turn forests from sinks to sources of carbon. Finally, physiological mechanisms connected to albedo and the emission of organic volatile compounds (VOCs) reduce the efficacy of climate cooling. Although such constraints exist, the establishment of new plantations and the restoration of existing forests are still necessary but are just one of the actions to fight climate change and must not be seen as an alternative to reducing carbon emissions. Considering limitations and trade-offs in the models to estimate tree growth and carbon storage will allow us to produce more realistic plans for climate mitigation. Full article

Geodetic data, especially from the Global Navigation Satellite System (GNSS) and Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GFO), are extensively employed in hydrological drought monitoring across various spatial scales due to their unique spatial resolution. In recent years, Brazil has experienced some of the most severe drought events in decades. This study focuses on Brazil and its northeastern Amazon Plain, investigates the spatiotemporal characteristics of terrestrial water storage (TWS) changes, and calculates the hydrological drought severity index (DSI) and meteorological drought index for comprehensive analysis of drought conditions. The results indicate that the time series of TWS changes derived from different data sources are highly correlated, with correlation coefficients exceeding 0.85, and are consistent with the trend of precipitation variation, reflecting notable seasonal fluctuations, i.e., an increase in precipitation during the spring and summer seasons leads to a rise in TWS, while a decrease in precipitation during the autumn and winter seasons triggers a reduction in TWS. In terms of spatial distribution, the annual amplitude of TWS variation is most pronounced in the northeastern Amazon Plain. The highest amplitude, approximately 800 mm, is observed near the Amazon River Basin, and this amplitude gradually weakens from northeast to southwest. GNSS and GRACE/GFO data reveal four hydrological drought events in Brazil from 2013 to 2024, with two of these events detected using GRACE/GFO data. The most severe droughts occurred between 2023 and 2024, primarily driven by prolonged precipitation deficits and the El Niño phenomenon, lasting up to nine months. Additionally, three distinct drought events were identified in the Amazon Plain, suggesting that its hydrological dynamics significantly influenced Brazil’s drought conditions. These results demonstrate the capability of geodetic data to effectively monitor water deficit and drought duration on both small spatial scales and short timeframes, thereby providing crucial support for timely responses to and the management of hydrological drought events. Full article