Deciphering impacts of climate extremes on Tibetan grasslands in the last fifteen years

Vegetation redistribution is predicted to intensify soil organic carbon loss under future climate changes on the Tibetan Plateau

Vegetation redistribution may bring unexpected climate-soil carbon cycling in terrestrial biomes. However, whether and how vegetation redistribution alters the soil carbon pool under climate change is still poorly understood on the Tibetan Plateau. Here, we applied the G-Range model to simulate the cover of herbs, shrubs and trees, net primary productivity (NPP) and soil organic carbon density (SOCD) at the depth of 60 cm on Tibetan Plateau for the individual years 2020 and 2060, using climate projection for Representative Concentration Pathways (RCP) 4.5 and RCP8.5 scenarios with the RegCM4.6 model system. Vegetation redistribution was defined as the transitions in bare ground, herbs, shrubs and trees between 2020 and 2060, with approximately 57.9 % (RCP4.5) and 59 % (RCP8.5) of the area will redistribute vegetation over the whole Tibetan Plateau. The vegetation cover will increase by about 2.4 % (RCP4.5) and 1.9 % (RCP8.5), while the NPP and SOCD will decrease by about -14.3 g C m-2 yr-1 and -907 g C m-2 (RCP4.5), and -1.8 g C m-2 yr-1and -920 g C m-2 (RCP8.5). Shrubs and trees will expand in the east, and herbs will expand in the northwest part of the Plateau. These areas are projected to be hotspots with greater SOCD reduction in response to future climate change, and will include lower net plant carbon input due to the negative NPP. Our study indicates that the SOC pool will become a carbon source under increased air temperature and rainfall on the Tibetan Plateau by 2060, especially for the area with vegetation redistribution. These results revealed the potential risk of vegetation redistribution under climate change in alpine ecosystems, indicating the policymakers need to pay attention on the vegetation redistribution to mitigate the soil carbon emission and achieve the goal of carbon neutrality on the Tibetan Plateau.

Effects of climate change and ozone on vegetation phenology on the Tibetan Plateau

The vegetation phenology, encompassing the start (SOS) and end (EOS) of the growing season on the Tibetan Plateau, has been significantly impacted by global climate change. Furthermore, ozone (O3) has gradually become the main pollutant in this region, substantially influencing carbon cycle and ecosystems on Earth. While ongoing studies have focused mainly on the implications of climate parameters, including temperature, precipitation, and radiation, the effects of O3 on the SOS and EOS remain unclear. Here, we compared the responses and sensitivities of the SOS and EOS to both climatic factors and O3 in this region. With the use of partial correlation analysis, we found that increased precipitation was the most important factor influencing the SOS and caused earlier occurrence (4.8 % vs. 21.9 %) for most plant functional types. In comparison, temperature only dominated in shrublands. In particular, we found that the EOS responded comparably to climatic factors with similar proportions between advancing and delaying patterns. However, higher O3 levels consistently advanced the EOS for almost all plant functional types and was the main factor controlling EOS variations based on the sensitivity analysis. Our results emphasized that O3 pollution should be considered for obtaining better phenological forecasts and determining the impacts of the environment and atmospheric composition on carbon sequestration in terrestrial ecosystems.

Extreme low air temperature and reduced moisture jointly inhibit respiration in alpine grassland on the Qinghai-Tibetan Plateau

Alpine grassland is the main vegetation on the Qinghai-Tibetan Plateau (QTP) and exhibits high sensitivity to extreme weather events. With global warming, extreme weather events are projected to become more frequent on the QTP. However, the impact of these extreme weather events on the carbon cycle of alpine grassland remains unclear. The long-term in-situ carbon fluxes data was collected from 2013 to 2022 at an alpine grassland site to examine the impact of extreme low air temperature (ELT) and reduced moisture (including air and soil) on carbon fluxes during the growing season. Our findings indicated that a significant increase in net ecosystem production (NEP) after 2019, with the average NEP increasing from 278.91 ± 43.27 g C m-2 year-1 during 2013-2018 to 415.45 ± 45.29 g C m-2 year-1 during 2019-2022. The ecosystem carbon use efficiency (CUE) increased from 0.38 ± 0.06 during 2013-2018 to 0.62 ± 0.11 during 2019-2022. By combining concurrently measured environmental factors and remote sensing data, we identified the factors responsible for the abrupt change in the NEP after 2019. This phenomenon was caused by an abrupt decrease in ecosystem respiration (Reco) after 2019, which resulted from the inhibition imposed by ELT and reduced moisture. In contrast, gross primary production (GPP) remained stable from 2013 to 2022, which was confirmed by the remotely sensed vegetation index. This study highlights that combined extreme weather events associated with climate change can significantly impact the NEP of alpine grassland, potentially affecting different carbon fluxes at different rates. These findings provide new insights into the mechanisms governing the carbon cycle of alpine grassland.

Alpine grassland greening on the Northern Tibetan Plateau driven by climate change and human activities considering extreme temperature and soil moisture

Alpine grassland is among the world's most vulnerable ecosystems, characterized by a high sensitivity to climate change (CC) and human activities (HA). Quantifying the relative contributions of CC and HA to grassland change plays a crucial role in safeguarding grassland ecological security and devising sustainable grassland management strategies. Although there were adequate studies focusing on the separate impacts of CC and HA on alpine ecosystem, insufficient attention has been given to investigating the effects of extreme temperatures and soil moisture. In this study, the spatiotemporal variations of alpine grassland were analyzed based on MODIS NDVI during the growing season from 2000 to 2020 in Naqu, using partial least squares regression and residual analysis methods to analyze the importance of climate factors and the impacts of CC and HA on grassland change. The results show that the NDVI during the growing season in Naqu exhibited an increasing trend of 0.0046/10a. At the biome scale, the most significant and rapid increase was observed in alpine desert and alpine desert grassland. Extreme temperature and soil moisture (SM) exerted a more significant importance on alpine grassland at whole scale. SM always showed a significant importance at biome and grid scale. The contributions of CC and HA to the change during the growing season were calculated as 0.0032/10a and 0.0015/10a, respectively, accounting for 68.05 % and 31.05 %. CC dominated the increase in NDVI during the growing season; HA contributed positively to NDVI in most areas of Naqu. The results are expected to enhance our understanding of grassland variations under CC and HA and provide a scientific basis for future ecological conservation in alpine regions.

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.

Opposing effects of warming on the stability of above- and belowground productivity in facing an extreme drought event

Climate warming, often accompanied by extreme drought events, could have profound effects on both plant community structure and ecosystem functioning. However, how warming interacts with extreme drought to affect community- and ecosystem-level stability remains a largely open question. Using data from a manipulative experiment with three warming treatments in an alpine meadow that experienced one extreme drought event, we investigated how warming modulates resistance and recovery of community structural and ecosystem functional stability in facing with extreme drought. We found warming decreased resistance and recovery of aboveground net primary productivity (ANPP) and structural resistance but increased resistance and recovery of belowground net primary productivity (BNPP), overall net primary productivity (NPP), and structural recovery. The findings highlight the importance of jointly considering above- and belowground processes when evaluating ecosystem stability under global warming and extreme climate events. The stability of dominant species, rather than species richness and species asynchrony, was identified as a key predictor of ecosystem functional resistance and recovery, except for BNPP recovery. In addition, structural resistance of common species contributed strongly to the resistance changes in BNPP and NPP. Importantly, community structural resistance and recovery dominated the resistance and recovery of BNPP and NPP, but not for ANPP, suggesting the different mechanisms underlie the maintenance of stability of above- versus belowground productivity. This study is among the first to explain that warming modulates ecosystem stability in the face of extreme drought and lay stress on the need to investigate ecological stability at the community level for a more mechanistic understanding of ecosystem stability in response to climate extremes.

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).

Negative relationship between photosynthesis and late-stage canopy development and senescence over Tibetan Plateau

Canopy greening, which is associated with significant canopy structure changes, is the most notable signal of ecosystem changes in response to anthropogenic climate change. However, our knowledge of the changing pattern of canopy development and senescence, and its endogenous and climatic drivers is still limited. Here, we used the Normalized Difference Vegetation Index (NDVI) to quantify the changes in the speed of canopy development and senescence over the Tibetan Plateau (TP) during 2000-2018, and used a solar-induced chlorophyll fluorescence dataset as a proxy for photosynthesis, in combination with climate datasets to decipher the endogenous and climatic drivers of the interannual variation in canopy changes. We found that the canopy development during the early green-up stage (April-May) is accelerating at a rate of 0.45-0.8 × 10^-3  month^-1  year^-1 . However, this accelerating canopy development was largely offset by a decelerating canopy development during June and July (-0.61 to -0.51 × 10^-3  month^-1  year^-1 ), leading to the peak NDVI over the TP increasing at a rate of only one fifth of that in northern temperate regions, and less than one tenth of that in the Arctic and boreal regions. During the green-down period, we observed a significant accelerating canopy senescence during October. Photosynthesis was found to be the dominant driver for canopy changes over the TP. Increasing photosynthesis stimulates canopy development during the early green-up stage. However, slower canopy development and accelerated senescence was found with larger photosynthesis in late growth stages. This negative relationship between photosynthesis and canopy development is probably linked to the source-sink balance of plants and shifts in the allocation regime. These results suggest a sink limitation for plant growth over the TP. The impact of canopy greening on the carbon cycle may be more complicated than the source-oriented paradigm used in current ecosystem models.

Multiple pressures and vegetation conditions shape the spatiotemporal variations of ecosystem services in the Qinghai-Tibet Plateau

Human activities and environmental change can impact the supply of ecosystem services (ESs) as pressures. Understanding the mechanisms of these impacts is crucial to support ecological conservation and restoration policy and applications. In this study, we highlighted the contribution of vegetation to mitigating these impacts on ESs in the Qinghai-Tibet Plateau (QTP) of China. First, we identified hot and cold spots of pressures from human activities and environmental factors and mapped the cumulative provision of five ESs (i.e., water yield, soil retention, carbon sequestration, habitat quality, and landscape aesthetics). Then, we clustered these ESs into five bundles based on their supply level. Furthermore, structural equation modeling was used to quantify the pathways of multiple pressures on ESs. The results indicated that 1) for 2000, 2010 and 2019, the percentages of hot spots with high pressure were 28.88%, 27.59% and 45.66% respectively, with significant spatial heterogeneity from northwest to southeast; 2) both regions with high and low cumulative ES values experienced increased volatility; and 3) the joint effects of multiple pressures shaped ESs through pressure-ES (direct) and pressure-vegetation-ES (indirect) pathways. Specifically, precipitation had the largest positive effect on regulating services (rα ≥ 0.76), and landscape fragmentation had the largest negative effect on cultural services (-0.10 ≤ rα ≤ -0.07). Vegetation played an important role in modulating multiple pressures on ESs. This study contributes to ecosystem management by effectively coping with anthropogenic and environmental pressures and sustaining the supply of ESs, particularly in alpine and plateau regions.

Shifting from a thermal-constrained to water-constrained ecosystem over the Tibetan Plateau

Introduction

Understanding the seasonality of vegetation growth is important for maintaining sustainable development of grassland livestock systems over the Tibetan Plateau (TP). Current knowledge of changes in the seasonality of TP grasslands is restricted to spring and autumn phenology, with little known about the date of peak vegetation growth, the most relevant quantity for grassland productivity.

Methods

We investigate the shifts of the date of peak vegetation growth and its climatic controls for the alpine grasslands over the TP during 2001-2020 using a framework based on the law of minimum, which is based on the assumption that peak vegetation growth would be consistent with the peak timing of the most limiting climatic resource.

Results

The date of peak vegetation growth over the TP advanced by 0.81 days decade-1 during 2001-2020. This spring-ward shift mainly occurs in the semi-humid eastern TP, where the peak growth date tracks the advancing peak precipitation, and shifted towards the timing of peak temperature. The advancing peak growth over the eastern TP significantly stimulated the ecosystem production by 1.99 gCm-2 year-1 day-1 during 2001-2020, while this positive effect weakened from 3.02 gCm-2 year-1 day-1 during 2000s to 1.25 gCm-2 year-1 day-1 during 2010s.

Discussion

Our results highlighted the importance of water availability in vegetation growth over the TP, and indicated that the TP grassland is moving towards a tipping point of transition from thermal-constrained to water-constrained ecosystem under the rapid warming climate.

Climate Drivers Contribute in Vegetation Greening Stalls of Arid Xinjiang, China: An Atmospheric Water Drying Effect

Xinjiang, an arid region of China, has experienced a substantial warming–wetting trend over the past five decades. However, climate change has affected vegetation growth/greening in arid Central Asia in unexpected ways due to complex ecological effects. We found a significant greening trend (consistent increase in the normalized difference vegetation index or NDVI) from 1982 to 1996, during the growing season; however, the NDVI consequently decreased and plateaued from 1997 to 2015, especially in naturally vegetated regions. Atmospheric vapor pressure deficit (VPD) is a critical driver of vegetation growth, is a direct measure of atmospheric aridity, and has increased sharply in recent decades. A partial correlation analysis indicated a significant relationship between growing season NDVI and VPD from 1997 to 2015. This implies that decreased VPD corresponds to increasing NDVI, and increasing VPD corresponds to a decrease and plateauing in the NDVI trend. Using the partial derivative equation method, our results suggest that the trend in growing season NDVI was affected primarily by increasing VPD (contributing 87.57%) from 1997 to 2015, especially in the grassland and desert biomes. Rising temperatures lead to a greater VPD, resulting in exacerbated evaporative water loss. Soil drought and atmospheric aridity limit plant stomatal conductance and could effectively lead to a decrease in the greening trend and increased vegetation mortality in arid Xinjiang. Our results emphasize the importance of VPD as a limiting factor of greening trends in arid regions. The influence of VPD on vegetation growth should be considered when evaluating arid ecosystem functioning under global warming.

Heatwaves Significantly Slow the Vegetation Growth Rate on the Tibetan Plateau

In recent years, heatwaves have been reported frequently by literature and the media on the Tibetan Plateau. However, it is unclear how alpine vegetation responds to the heatwaves on the Tibetan Plateau. This study aimed to identify the heatwaves using long-term meteorological data and examine the impact of heatwaves on vegetation growth rate with remote sensing data. The results indicated that heatwaves frequently occur in June, July, and August on the Tibetan Plateau. The average frequency of heatwaves had no statistically significant trends from 2000 to 2020 for the entire Tibetan Plateau. On a monthly scale, the average frequency of heatwaves increased significantly (p < 0.1) in August, while no significant trends were in June and July. The intensity of heatwaves indicated a negative correlation with the vegetation growth rate anomaly (ΔVGR) calculated from the normalized difference vegetation index (NDVI) (r = −0.74, p < 0.05) and the enhanced vegetation index (EVI) (r = −0.61, p < 0.1) on the Tibetan Plateau, respectively. Both NDVI and EVI consistently demonstrate that the heatwaves slow the vegetation growth rate. This study outlines the importance of heatwaves to vegetation growth to enrich our understanding of alpine vegetation response to increasing extreme weather events under the background of climate change.

Relative Impact of Climate Change and Grazing on NDVI Changes in Grassland in the Mt. Qomolangma Nature Reserve and Adjacent Regions during 2000–2018

As the roof of the world, the Mt. Qomolangma National Nature Reserve and adjacent regions have a fragile environment and are very sensitive to global climate change. Based on the MODIS and SPOT remote sensing data during 2000–2018, we aimed to explore the change trend and driving factors of grassland in this area under the dual influence of climate change and human activities. Here, temperature and precipitation data were enrolled as the main indicators of climate change, while the number of livestock at the end of the year was regarded as the key indicator of grazing. The results showed that: (1) during 2000–2018, the grassland NDVI reflected an overall increasing trend, and the impact of precipitation was more significant than those of temperature and grazing at both pixel and county levels; (2) probably due to the large population and high grazing intensity, the grassland NDVI in Tingri County was controlled by both precipitation and grazing. In general, precipitation exerts a greater impact on the NDVI changes since this region is characterized by arid and semiarid climates. In some areas, vegetation growth is simultaneously affected by both grazing and climate factors due to the relatively greater pressure of grazing. In the context of future warming, control of the number of tourists for Mt. Qomolangma, as well as that of livestock in Tingri County, will help improve sustainability development and to reduce the adverse effects of grassland degradation.

Warming reduces the production of a major annual forage crop on the Tibetan Plateau

Climate warming has been proposed to increase primary production of natural grasslands in cold regions. However, how climate warming affects the production of artificial pastures in cold regions remains unknown. To address this question, we used open-top chambers to simulate warming in a major artificial pasture (forage oat) on the cold Tibetan Plateau for three consecutive years. Surprisingly, climate warming decreased aboveground and belowground biomass production by 23.1%-44.8% and 35.0%-46.5%, respectively, without a significant impact on their ratio. The adverse effects on biomass production could be attributed to the adverse effects of high-temperatures on leaf photosynthesis through increases in water vapor pressure deficit (by 0.05-0.10 kPa), damages to the leaf oxidant system, as indicated by a 46.6% increase in leaf malondialdehyde content, as well as reductions in growth duration (by 4.7-6.7 days). The adverse effects were also related to exacerbated phosphorus limitation, as indicated by decreases in soil available phosphorus and plant phosphorus concentrations by 31.9%-40.7% and 14.3%-49.4%, respectively, and increases in the plant nitrogen: phosphorus ratio by 19.2%-108.3%. The decrease in soil available phosphorus concentration could be attributed to reductions in soil phosphatase activities (by 9.6%-18.5%). The findings of this study suggest an urgent need to advance agronomic techniques and cultivate more resilient forage genotypes to meet the increasing demand of forage for feeding livestock and to reduce grazing damage to natural grasslands on the warming-sensitive Tibetan Plateau.

Quantification of Natural and Anthropogenic Driving Forces of Vegetation Changes in the Three-River Headwater Region during 1982–2015 Based on Geographical Detector Model

The three-river headwater region (TRHR) supplies the Yangtze, Yellow, and Lantsang rivers, and its ecological environment is fragile, hence it is important to study the surface vegetation cover status of the TRHR to facilitate its ecological conservation. The normalized difference vegetation index (NDVI) can reflect the cover status of surface vegetation. The aims of this study are to quantify the spatial heterogeneity of the NDVI, identify the main driving factors influencing the NDVI, and explore the interaction between these factors. To this end, we used the global inventory modeling and mapping studies (GIMMS)-NDVI data from the TRHR from 1982 to 2015 and included eight natural factors (namely slope, aspect, elevation, soil type, vegetation type, landform type, annual mean temperature, and annual precipitation) and three anthropogenic factors (gross domestic product (GDP), population density, and land use type), which we subjected to linear regression analysis, the Mann-Kendall statistical test, and moving t-test to analyze the spatial and temporal variability of the NDVI in the TRHR over 34 years, using a geographical detector model. Our results showed that the NDVI distribution of the TRHR was high in the southeast and low in the northwest. The change pattern exhibited an increasing trend in the west and north and a decreasing trend in the center and south; overall, the mean NDVI value from 1982 to 2015 has increased. Annual precipitation was the most important factor influencing the NDVI changes in the TRHR, and factors, such as annual mean temperature, vegetation type, and elevation, also explained the vegetation coverage status well. The influence of natural factors was generally stronger than that of anthropogenic factors. The NDVI factors had a synergistic effect, exhibiting mutual enhancement and nonlinear enhancement relationships. The results of this study provide insights into the ecological conservation of the TRHR and the ecological security and development of the middle and lower reaches.

Carbon turnover times shape topsoil carbon difference between Tibetan Plateau and Arctic tundra

The Tibetan Plateau (TP) and Arctic permafrost constitute two large reservoirs of organic carbon, but processes which control carbon accumulation within the surface soil layer of these areas would differ due to the interplay of climate, soil and vegetation type. Here, we synthesized currently available soil carbon data to show that mean organic carbon density in the topsoil (0-10 cm) in TP grassland (3.12 ± 0.52 kg C m^-2) is less than half of that in Arctic tundra (6.70 ± 1.94 kg C m^-2). Such difference is primarily attributed to their difference in radiocarbon-inferred soil carbon turnover times (547 years for TP grassland versus 1609 years for Arctic tundra) rather than to their marginal difference in topsoil carbon inputs. Our findings highlight the importance of improving regional-specific soil carbon turnover and its controlling mechanisms across permafrost affected zones in ecosystem models to fully represent carbon-climate feedback.

Spatial Heterogeneity and Complexity of the Impact of Extreme Climate on Vegetation in China

The impact of extreme climate on natural ecosystems and socioeconomic systems is more serious than that of the climate’s mean state. Based on the data of 1698 meteorological stations in China from 2001 to 2018, this study calculated the 27 extreme climate indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). Through correlation analysis and collinearity diagnostics, we selected two representative extreme temperature indices and three extreme precipitation indices. The spatial scale of the impact of extreme climate on Normalized Difference Vegetation Index (NDVI) in China during the growing season from 2001 to 2018 was quantitatively analyzed, and the complexity of the dominant factors in different regions was discussed via clustering analysis. The research results show that extreme climate indices have a scale effect on vegetation. There are spatial heterogeneities in the impacts of different extreme climate indices on vegetation, and these impacts varied between the local, regional and national scales. The relationship between the maximum length of a dry spell (CDD) and NDVI was the most spatially nonstationary, and mostly occurred on the local scale, while the effect of annual total precipitation when the daily precipitation amount was more than the 95th percentile (R95pTOT) showed the greatest spatial stability, and mainly manifested at the national scale. Under the current extreme climate conditions, extreme precipitation promotes vegetation growth, while the influence of extreme temperature is more complicated. As regards intensity and range, the impact of extreme climate on NDVI in China over the past 18 years can be categorized into five types: the humidity-promoting type, the cold-promoting and drought-inhibiting compound type, the drought-inhibiting type, the heat-promoting and drought-inhibiting compound type, and the heat-promoting and humidity-promoting compound type. Drought is the greatest threat to vegetation associated with extreme climate in China.

Spatio-Temporal Characteristics of Drought Events and Their Effects on Vegetation: A Case Study in Southern Tibet, China

Frequent droughts in a warming climate tend to induce the degeneration of vegetation. Quantifying the response of vegetation to variations in drought events is therefore crucial for evaluating the potential impacts of climate change on ecosystems. In this study, the standardized precipitation index (SPI) was calculated using the precipitation data sourced from the China Meteorological Forcing Dataset (CMFD), and then the drought events in southern Tibet from 1982 to 2015 were identified based on the SPI index. The results showed that the frequency, severity, and intensity of drought events in southern Tibet decreased from 1982 to 2015, and the highest frequency of drought was found between 1993 and 2000. To evaluate the impact of drought events on vegetation, the vegetation characteristic indexes were developed based on the normalized difference vegetation index (NDVI) and the drought characteristics. The assessment of two drought events showed that the alpine grasslands and alpine meadows had high vegetation vulnerability (AI). The assessment of multiple drought events showed that responses of vegetation to drought were spatially heterogeneous, and the total explain rate of environmental factors to the variations in AI accounted for 40%. Among the many environmental factors investigated, the AI were higher at middle altitudes (2000–3000 m) than low altitudes (<2000 m) and high altitudes (3000–4500 m). Meanwhile, the silt soil fraction in the upper soil layer (0–30 cm) had the greatest positive correlation with AI, suggesting that areas with a high silt soil fraction were more sensitive to drought. The relative contribution rates of environmental factors were predicted by a multivariate linear regression (MLR) model. The silt soil fraction was found to make the greatest relative contribution (23.3%) to the changes in AI.

Evaluating the cumulative and time-lag effects of drought on grassland vegetation: A case study in the Chinese Loess Plateau

The increased frequency of drought events in recent years is known to be responsible for significantly altering plant biodiversity in many of Earth's ecosystems, though the specifics of vegetation-drought interactions, especially the cumulative and time-lag responses, remains unclear. This study aimed to quantitatively investigate how grassland vegetation over the Chinese Loess Plateau (CLP) reacts to drought, specifically the observed cumulative and time-lag effects which are caused, using a combination of the Normalized Difference Vegetation Index (NDVI) and a multiple time-scale drought index (Standardized Precipitation and Evapotranspiration Index, SPEI). Our results revealed that while drought conditions have widespread cumulative impacts on grass growth in the CLP, the time lag effect of drought covered about half of the total area of the CLP. The cumulative effect of drought on grass was found to take place over various time scales, ranging from 5 to 10 months, while the time lag effect occurred within 2-3 months. The different response time of vegetation growth to the cumulative effect of drought in the CLP was found to be highly related to different water conditions. The accumulated months and mean r_max-cum both had a significant negative correlation with the mean annual SPEI (R² = 0.90, P < 0.001; R² = 0.70, P < 0.001, respectively). The lagged months and mean r_max-lag were also found to be negatively correlated with the mean annual SPEI (R² = 0.547, P < 0.05; R² = 0.785, P < 0.01, respectively).

Continuous Wetting on the Tibetan Plateau during 1970–2017

Based on daily observation records at 277 meteorological stations on the Tibetan Plateau (TP) and its surrounding areas during 1970–2017, drought evolution was investigated using the Standardized Precipitation Evapotranspiration Index (SPEI). First, the spatiotemporal changes in the growing season of SPEI (SPEIgs) were re-examined using the Mann–Kendall and Sen’s slope approach—the piecewise linear regression and intensity analysis approach. Then, the persistence of the SPEIgs trend was predicted by the Hurst exponent. The results showed that the SPEIgs on the TP exhibited a significant increasing trend at the rate of 0.10 decade−1 (p < 0.05) and that there is no significant trend shift in SPEIgs (p = 0.37), indicating that the TP tended to undergo continuous wetting during 1970–2017. In contrast, the areas surrounding the TP underwent a significant trend shift from an increase to a decrease in SPEIgs around 1984 (p < 0.05), resulting in a weak decreasing trend overall. Spatially, most of the stations on the TP were characterized by an increasing trend in SPEIgs, except those on the Eastern fringe of TP. The rate of drought/wet changes was relatively fast during the 1970s and 1980s, and gradually slowed afterward on the TP. Finally, the consistent increasing trend and decreasing trend of SPEIgs on the TP and the area East of the TP were predicted to continue in the future, respectively. Our results highlight that the TP experienced a significant continuous wetting trend in the growing season during 1970–2017, and this trend is likely to continue.