Spatiotemporal Variation of Vegetation on the Qinghai–Tibet Plateau and the Influence of Climatic Factors and Human Activities on Vegetation Trend (2000–2019)

Spatiotemporal patterns, sustainability, and primary drivers of NDVI-derived vegetation dynamics (2003-2022) in Nepal

Understanding the vegetation dynamics and their drivers in Nepal has significant scientific reference value for implementing sustainable ecological policies. This study provides a comprehensive analysis of the spatio-temporal variations in vegetation cover in Nepal from 2003 to 2022 using MODIS NDVI data and explores the effects of climatic factors and anthropogenic activities on vegetation. Mann-Kendall test was used to assess the significant trend in NDVI and was integrated with the Hurst exponent to predict future trends. The driving factors of NDVI dynamics were analyzed using Pearson's correlation, partial derivative, and residual analysis methods. The results indicate that over the last 20 years, Nepal has experienced an increasing trend in NDVI at 0.0013 year-1, with 80% of the surface area (vegetation cover) showing an increasing vegetation trend (~ 28% with a significant increase in vegetation). Temperature influenced vegetation dynamics in the higher elevation areas, while precipitation and human interventions influenced the lower elevation areas. The Hurst exponent analysis predicts an improvement in the vegetation cover (greening) for a larger area compared to vegetation degradation (browning). A significantly increased area of NDVI residuals indicates a positive anthropogenic influence on vegetation cover. Anthropogenic activities have a higher relative contribution to NDVI variation followed by temperature and then precipitation. The results of residual trend and Hurst analysis in different regions of Nepal help identify degraded areas, both in the present and future. This information can assist relevant authorities in implementing appropriate policies for a sustainable ecological environment.

Primary driving factors of ecological environment system change based on directed weighted network illustrating with the Three-River Headwaters Region

The primary driving factors of ecological environment change have received significant attention. However, previous research methods for identifying the main drivers of ecological environment change have primarily relied on correlation analysis and regression analysis. While these methods can reveal co-occurrences, associations, and correlations among elemental characteristics, they often struggle to uncover the deep-seated interactions among elements within complex, unstable, nonlinear, and high-dimensional systems. To address this, we used the Three-River Headwaters Region as a case study and introduced a complex network model from the perspective of the ecological environment system to investigate the main driving factors of ecological environment change. In our analysis, we considered 12 factors related to the atmosphere, hydrology, vegetation, and soil, including evaporation, long-wave radiation, short-wave radiation, specific humidity, soil temperature, precipitation rate, soil water content, air temperature, air pressure, vegetation normalization index, wind speed, and natural surface runoff. Watersheds were selected as the fundamental units for constructing ecological environment datasets. We applied the Ensemble Empirical Mode Decomposition (EEMD) method and Hilbert-Huang Transform (HHT) to analyze causal relationships between time series pairs and constructed two directed weighted network models based on sub-catchments. The results showed that both network models yielded consistent conclusions, with the sparse network exhibiting higher efficiency. Radiation and temperature were identified as the primary driving factors of ecosystem change, and the water cycle was determined to be the ultimate manifestation of ecological system change throughout the Three-River Headwaters Region. Furthermore, based on node out-strength, we generated a vegetation protection priority map.

Spatial variations in the difference in elevational shifts between greenness and temperature isolines across the Tibetan Plateau grasslands under warming

Climate warming has induced widespread isotherm shifts toward higher elevations on the Tibetan Plateau, but elevational shifts of vegetation greenness (indicated by Normalized Difference Vegetation Index, NDVI) do not necessarily keep pace with the isotherm shifts. Thus, there should be spatial variations in the difference between the velocities of vertical movement of greenness isolines (VNDVI) and isotherms (VT) across the Tibetan Plateau grasslands. Using satellite-observed NDVI and gridded climate data during 2000-2017, we found uphill shifts of the isotherms in 81.8 % of the surveyed areas, mainly in the eastern, central, southwestern, and northeastern parts, whereas upward shifts of the greenness isolines were observed only in 49.7 % of these areas, mainly in the southeastern, west-central, and southwestern edge of Tibetan Plateau grasslands. In the areas where both the greenness isolines and isotherms shifted uphill, VDNVI was faster than VT in the west-central and northeastern parts, and VNDVI was smaller than VT in the western, south-central, central, and southeastern regions; the difference between VNDVI and VT was positively related with elevational gradient of NDVI (NDVIEG) in the areas where NDVIEG was negative and the temporal trend of NDVI was positive, and was negatively related with NDVIEG and temporal trends of NDVI and temperature in the areas where NDVIEG was positive and temporal trend of NDVI was negative. Our results revealed spatial heterogeneity in the difference in the elevational shifts between the isotherm and vegetation greenness isoline across the Tibetan Plateau grasslands, which is related with both diverse adaptation to local environment (NDVIEG) and complex responses of vegetation greenness to warming in terms of both direction and magnitude. These findings have important implications for the prediction of vegetation production and carbon cycle and the adaptive management of alpine grasslands under climate change.

Effects of hydrothermal factors and human activities on the vegetation coverage of the Qinghai-Tibet Plateau

A systematic understanding of the spatio-temporal changes and driving factors in the Qinghai-Tibet Plateau holds significant scientific reference value for the future of ecological sustainable development. This paper utilizes MODIS normalized difference vegetation index (NDVI) and meteorological data to investigate the spatio-temporal changes and driving factors of vegetation coverage in the Qinghai-Tibet Plateau from 2001 to 2020. Methods employed include the dimidiate pixel model, trend analysis, partial correlation analysis, and residual analysis. The results demonstrate a generally fluctuating upward trend in vegetation coverage across the Tibetan Plateau over the past two decades, with spatial expansion occurring from northwest to southeast. Vegetation coverage exhibits a positive correlation with climate factors. Approximately 60.7% of the area showed a positive correlation between vegetation fractional cover (FVC) and precipitation, with 8.66% of the area demonstrating extremely significant (p < 0.05) and significant (p < 0.01) positive correlation. Human activities, on the whole, have contributed to the enhancement of vegetation cover in the Qinghai-Tibet Plateau. The areas where human activities have positively impacted vegetation cover are primarily situated in north-central Qinghai and north of Ngari, while areas experiencing degradation include certain grassland regions in central-eastern Yushu, Nagqu, and Lhasa.

Should time-lag and time-accumulation effects of climate be considered in attribution of vegetation dynamics? Case study of China's temperate grassland region

Although the time-lag and time-accumulation effects (TLTAEs) of climatic factors on vegetation growth have been investigated extensively, the uncertainties caused by disregarding TLTAEs in the attribution analysis of long-term changes in vegetation remain unclear. This hinders our understanding of the associated changes in ecosystems and the effects of climate change. In this study, using multiple methods, we evaluate the biases of attribution analyses of vegetation dynamics caused by the non-consideration of TLTAEs in the temperate grassland region (TGR) of China from 2000 to 2019. Based on the datasets of the normalized difference vegetation index (NDVI), temperature (TMP), precipitation (PRE), and solar radiation (SR), the temporal reaction patterns of vegetation are analyzed, and the relationships among these variables under two scenarios (considering and disregarding TLTAEs) are compared. The results indicate that most areas of the TGR show a greening trend. A time-lag or time-accumulation effect of the three climatic variables is observed in most areas with significant spatial differences. The lagged times of the vegetation response to PRE are particularly prominent, with an average of 2.12 months in the TGR. When the TLTAE is considered, the areas where changes in the NDVI are affected by climatic factors expanded significantly, whereas the explanatory power of climate change on NDVI change increased by an average of 9.3% in the TGR; these improvements are more prominent in relatively arid areas. This study highlights the importance of including TLTAEs in the attribution of vegetation dynamics and the assessment of climatic effects on ecosystems.

Impacts of human pressure and climate on biodiversity-multifunctionality relationships on the Qinghai-Tibetan Plateau

Many studies have investigated the effects of environmental context on biodiversity or multifunctionality in alpine regions, but it is uncertain how human pressure and climate may affect their relationships. Here, we combined the comparative map profile method with multivariate datasets to assess the spatial pattern of ecosystem multifunctionality and further identify the effects of human pressure and climate on the spatial distribution of biodiversity-multifunctionality relationships in alpine ecosystems of the Qinghai-Tibetan Plateau (QTP). Our results indicate that at least 93% of the areas in the study region show a positive correlation between biodiversity and ecosystem multifunctionality across the QTP. Biodiversity-multifunctionality relationships with increasing human pressure show a decreasing trend in the forest, alpine meadow, and alpine steppe ecosystems, while an opposite pattern was found in the alpine desert steppe ecosystem. More importantly, aridity significantly strengthened the synergistic relationship between biodiversity and ecosystem multifunctionality in forest and alpine meadow ecosystems. Taken together, our results provide insights into the importance of protecting and maintaining biodiversity and ecosystem multifunctionality in response to climate change and human pressure in the alpine region.

Optimality principles explaining divergent responses of alpine vegetation to environmental change

Recent increases in vegetation greenness over much of the world reflect increasing CO₂ globally and warming in cold areas. However, the strength of the response to both CO₂ and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (F_max ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year^-1 in drier regions and a browning of 0.12 ± 0.08% year^-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in F_max with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year^-1 ) and browning (0.07 ± 0.06% year^-1 ). We also predicted the observed reduced sensitivities of F_max to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces F_max in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO₂ stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.

Greening or browning? The macro variation and drivers of different vegetation types on the Qinghai-Tibetan Plateau from 2000 to 2021

Vegetation greenness is one of the main indicators to characterize changes in terrestrial ecosystems. China has implemented a few large-scale ecological restoration programs on the Qinghai-Tibetan Plateau (QTP) to reverse the trend of ecosystem degradation. Although the effectiveness of these programs is beginning to show, the mechanisms of vegetation degradation under climate change and human activities are still controversial. Existing studies have mostly focused on changes in overall vegetation change, with less attention on the drivers of change in different vegetation types. In this study, earth satellite observation records were used to robustly map changes in vegetation greenness on the QTP from 2000 to 2021. The random forest (RF) algorithm was further used to detect the drivers of greenness browning on the QTP as a whole and in seven different vegetation types. The results show that an overall trend of greening in all seven vegetation types on the QTP over a 21-year period. The area of greening was 46.54×10⁴ km², and browning was 5.32×10⁴ km², representing a quarter and 2.86% of the natural vegetation area, respectively. The results of the browning driver analysis show that areas with high altitude, reduced annual precipitation, high intensity of human activity, average annual maximum and average annual minimum precipitation of approximately 500 mm are most susceptible to browning on the QTP. For the seven different vegetation types, their top 6 most important browning drivers and the ranking of drivers differed. DEM and precipitation changes are important drivers of browning for seven vegetation types. These results reflect the latest spatial and temporal dynamics of vegetation on the QTP and highlight the common and characteristic browning drivers of vegetation ecosystems. They provide support for understanding the response of different vegetation to natural and human impacts and for further implementation of site-specific restoration measures.

Vegetation Dynamics in Response to Climate Change and Human Activities in a Typical Alpine Region in the Tibetan Plateau

Understanding past and future vegetation dynamics is important for assessing the effectiveness of ecological engineering, designing policies for adaptive ecological management, and improving the ecological environment. Here, inter-annual changes in vegetation dynamics during 2000-2020, contributions of climate change (CC) and human activities (HA) to vegetation dynamics, and sustainability of vegetation dynamics in the future were determined in Gannan Prefecture (a typical alpine region in the Tibetan Plateau), China. MODIS-based normalized difference vegetation index (NDVI), air temperature, precipitation, and land cover data were used, and trend analysis, multiple regression residuals analysis, and Hurst exponent analysis were employed. NDVI increased at a rate of 2.4 × 10^-3∙a^-1 during the growing season, and vegetation improved in most parts of the study area and some sporadically degraded areas also existed. The increasing rate was the highest in the Grain to Green Project (GTGP) areas. The vegetation in the southern and northern regions was mainly affected by CC and HA, respectively, with CC and HA contributions to vegetation change being 52.32% and 47.68%, respectively. The GTGP area (59.89%) was most evidently affected by HA. Moreover, a Hurst exponent analysis indicated that, in the future, the vegetation in Gannan Prefecture would continuously improve. The study can assist in formulating ecological protection and restoration projects and ensuring sustainable development.

Biogeographic Patterns of Leaf Element Stoichiometry of Stellera chamaejasme L. in Degraded Grasslands on Inner Mongolia Plateau and Qinghai-Tibetan Plateau

Plant leaf stoichiometry reflects its adaptation to the environment. Leaf stoichiometry variations across different environments have been extensively studied in grassland plants, but little is known about intraspecific leaf stoichiometry, especially for widely distributed species, such as Stellera chamaejasme L. We present the first study on the leaf stoichiometry of S. chamaejasme and evaluate its relationships with environmental variables. S. chamaejasme leaf and soil samples from 29 invaded sites in the two plateaus of distinct environments [the Inner Mongolian Plateau (IM) and Qinghai-Tibet Plateau (QT)] in Northern China were collected. Leaf C, N, P, and K and their stoichiometric ratios, and soil physicochemical properties were determined and compared with climate information from each sampling site. The results showed that mean leaf C, N, P, and K concentrations were 498.60, 19.95, 2.15, and 6.57 g kg⁻¹; the average C:N, C:P, N:P, N:K and K:P ratios were 25.20, 245.57, 9.81, 3.13, and 3.21, respectively. The N:P:K-ratios in S. chamaejasme leaf might imply that its growth is restricted by K- or K+N. Moreover, the soil physicochemical properties in the S. chamaejasme-infested areas varied remarkably, and few significant correlations between S. chamaejasme leaf ecological stoichiometry and soil physicochemical properties were observed. These indicate the nutrient concentrations and stoichiometry of S. chamaejasme tend to be insensitive to variations in the soil nutrient availability, resulting in their broad distributions in China’s grasslands. Besides, different homeostasis strength of the C, N, K, and their ratios in S. chamaejasme leaves across all sites were observed, which means S. chamaejasme could be more conservative in their use of nutrients improving their adaptation to diverse conditions. Moreover, the leaf C and N contents of S. chamaejasm were unaffected by any climate factors. However, the correlation between leaf P content and climate factors was significant only in IM, while the leaf K happened to be significant in QT. Besides, MAP or MAT contribution was stronger in the leaf elements than soil by using mixed effects models, which illustrated once more the relatively weak effect of the soil physicochemical properties on the leaf elements. Finally, partial least squares path modeling suggested that leaf P or K contents were affected by different mechanisms in QT and IM regions, suggesting that S. chamaejasme can adapt to changing environments by adjusting its relationships with the climate or soil factors to improve its survival opportunities in degraded grasslands.

Evaluating the effects of dams and meteorological variables on riparian vegetation NDVI in the Tibetan Plateau

As the third pole of the world, the Qinghai-Tibet Plateau (QTP) has a very special climate and geographical environment. In the past 20 years, with the increasing demand for clean energy, more than ten hydropower stations have been built. The impacts of these hydropower stations on riparian vegetation (RV) have only been described qualitatively in previous studies, while the contribution of dams and meteorological variables to riparian vegetation has not been quantitatively assessed. This study selected eight representative large-scale hydropower stations in the QTP, calculated and analyzed the dynamics of the standardized difference vegetation index (NDVI) of the RV pre-and post the dams construction, combined with the measured temperature and precipitation data to explore the driving factors of RV changes. The results show that the dams promoted the growth of RV and they were the main contributor (>50%) while precipitation and temperature had relatively small impacts. The effect of dams varies for different regions, compared with the sub-cold regions, it was more significant in humid and semi-humid regions of temperate zone. The dams affected RV in an indirect way through regulating the microclimate, promoting precipitation and slowing down the rate of temperature rise and these effects may come from the increase of the upstream water surface area.

Vegetation Dynamics and Their Influencing Factors in China from 1998 to 2019

Vegetation is a critical component of ecosystems that is influenced by climate change and human activities. It is therefore of great importance to investigate trends in vegetation dynamics and explore how these are influenced by climate and human activities. This will help formulate effective ecological restoration policies and ensure sustainable development. As the Normalized Difference Vegetation Index (NDVI) is strongly correlated with vegetation dynamics and may be used as a proxy measure for vegetation condition, the spatiotemporal characteristics of NDVI derived from SPOT/VEGETATION NDVI data in China over the 1998–2019 period were assessed using the Mann–Kendall test and the Hurst exponent. The Pearson correlation analysis and residual analysis methods were employed to analyze the influencing factors of NDVI dynamics. Integrating the results of the Hurst exponent and the NDVI trend analysis, it was found that the majority area of China is presenting an increasing NDVI trend at present but is likely to reverse in the future. A significant positive correlation between the NDVI and temperature was observed on the southeast coast of China and the north Qinghai–Tibet Plateau. Precipitation was the dominant factor affecting vegetation dynamics as indicated by a positive correlation with the NDVI for most parts of China except for the inland area in the Northwest and the Hengduan Mountains in Southwest China. Extreme temperature and extreme precipitation have also shown varying degrees of influence on vegetation dynamics at various locations. In addition, this study revealed trends of increasing NDVI, suggesting improved vegetation condition attributable to the implementation of ecological engineering projects. This study is helpful for studying the interaction mechanisms between terrestrial ecosystems and climate and for sustaining the ecological environment.

Distinguishing the Impacts of Human Activities and Climate Change on the Livelihood Environment of Pastoralists in the Qinghai Lake Basin

Grassland vegetation is the largest terrestrial ecosystem in the Qinghai Lake Basin (QLB), and it is also the most important means of production for herders’ livelihoods. Quantifying the impact of climate change and human activities on grassland vegetation changes is an essential task for ensuring the sustainable livelihood of pastoralists. To this end, we investigated vegetation cover changes in the QLB from 2000 to 2020 using the normalized difference vegetation index (NDVI), meteorological raster data, and digital elevation and used residual analysis of multiple linear regression to evaluate the residuals of human activities. The residual analysis of partial derivatives was used to quantify the contribution of climate change and human activities to changes in vegetation cover. The results showed that: (1) The vegetation coverage of the QLB increased significantly (0.002/a, p < 0.01), with 91.38% of the area showing a greening trend, and 8.62% of the area suffering a degrading trend. The NDVI decreased substantially along the altitude gradient (−0.02/a, p < 0.01), with the highest vegetation coverage at 3600–3700 m (0.37/a). The vegetation degraded from 3200–3300 m, vegetation greening accelerated from 3300–3500 m, and vegetation greening slowed above 3500 m. (2) The contribution of climate change, temperature (T), and precipitation (P) to vegetation cover change were 1.62/a, 0.005/a, and 1.615/a, respectively. Below 3500 m, the vegetation greening was more limited by P. Above 3500 m, the vegetation greening was mainly limited by T. (3) Residual analysis showed that the contribution of human activities to vegetation cover was −1.618/a. Regarding the altitude gradient, at 3300–3500 m, human activities had the highest negative contribution to vegetation coverage (−2.389/a), and at 3200–3300 m, they had the highest positive contribution (0.389/a). In the past 21 years, the impact of human activities on vegetation coverage changed from negative to positive. Before 2009, the annual average NDVIres value was negative; after 2010, the average yearly NDVIres value turned positive. In general, the vegetation greening of the QLB depends on climate warming and humidification. The positive impact of human activities over the past decade was also essential for vegetation greening. These findings deepen our understanding of the QLB vegetation changes under climate change and human activities.

NDVI-Based Greening of Alpine Steppe and Its Relationships with Climatic Change and Grazing Intensity in the Southwestern Tibetan Plateau

Alpine vegetation on the Southwestern Tibetan Plateau (SWTP) is sensitive and vulnerable to climate change and human activities. Climate warming and human actions (mainly ecological restoration, social-economic development, and grazing) have already caused the degradation of alpine grasslands on the Tibetan Plateau (TP) to some extent. However, it remains unclear how human activities (mainly grazing) have regulated vegetation variation under climate change and ecological restoration since 2000. This study used the normalized difference vegetation index (NDVI) and social statistic data to explore the spatiotemporal changes and the relationship between the NDVI and climatic change, human activities, and grazing intensity. The results revealed that the NDVI increased by 0.006/10a from 2000 to 2020. Significant greening, mainly distributed in Rikaze, with partial browning, has been found in the SWTP. The correlation analysis results showed that precipitation is the most critical factor affecting the spatial distribution of NDVI, and the NDVI is correlated positively with temperature and precipitation in most parts of the SWTP. We found that climate change and human activities co-affected the vegetation change in the SWTP, and human activities leading to vegetation greening since 2000. The NDVI and grazing intensity were mainly negatively correlated, and the grazing caused vegetation degradation to some extent. This study provides practical support for grassland use, grazing management, ecological restoration, and regional sustainable development for the TP and similar alpine areas.

Evaluation of Land Degradation Neutrality in Inner Mongolia Combined with Ecosystem Services

Currently, the internationally recognized land degradation neutrality (LDN) effort is evaluated using three indicators: land use/cover, land productivity, and carbon stocks. However, these three indicators may not completely capture the factors influencing LDN, and some evaluation rules are not in line with the land restoration goals of China. Therefore, this study introduces the ecosystem service value (ESV) indicator, assesses the differences in connotation and evaluation methods between ESV and LDN, and puts forward an evaluation rule that integrates their advantages, so as to carry out an evaluation of LDN in Inner Mongolia. The conclusions are as follows: (a) The ESVs of the Inner Mongolia Autonomous Region in 2000, 2005, 2010, 2015, and 2020 were USD 287.49, 286.04, 285.72, 286.38, and 287.90 billion, respectively, which presents a slight trend of decrease and then increase over time. (b) The modified LDN evaluation rule mainly includes the following changes to the LUCC evaluation rule: (1) the original degradation of cropland to grassland is considered as restoration, (2) water bodies participate in the transformation evaluation between land use types, and (3) the evaluation of transformed secondary land use types is added. The evaluation of net primary productivity (NPP) and soil organic carbon (SOC) still follow the method formulated by the United Nations Convention to Combat Desertification (UNCCD). (c) The proportion of degraded, stable, and restored land area within the LUCC were 11.31%, 77.34%, and 11.35%, respectively. The proportion of restored area is greater than the proportion of degraded land, which indicates that LDN has been achieved in Inner Mongolia according to the LUCC evaluation. The areas of degradation, stability, and restoration for NPP accounted for 0.10%, 40.52%, and 59.38% of the total area, respectively, with the restored area being much larger than the degraded area. The areas of SOC degradation, stability, and restoration accounted for 13.06%, 74.82%, and 12.11% of the total area, respectively, and the degraded area was slightly larger than the restored area. (d) The LDN evaluation results showed that the proportions of degraded, stable, and restored areas were 21.80%, 27.25%, and 50.96%, respectively. From these results, it is clear that Inner Mongolia has achieved the LDN target. Compared with the rules formulated by the UNCCD, for the LDN evaluation results implementing the modified rule, the proportion of degraded land increased by 2.44%, the proportion of stable land decreased by 1.52%, and the proportion of restored land decreased by 0.92%. In the future, Inner Mongolia should strengthen the implementation of a series of ecological restoration projects to obtain greater ecological benefits.

Biodiversity and Ecosystem Function under Simulated Gradient Warming and Grazing

Biodiversity and ecosystem functions and their relationship with environmental response constitute a major topic of ecological research. However, the changes in and impact mechanisms of multi-dimensional biodiversity and ecosystem functions in continuously changing environmental gradients and anthropogenic activities remain poorly understood. Here, we analyze the effects of multi-gradient warming and grazing on relationships between the biodiversity of plant and soil microbial with productivity/community stability through a field experiment simulating multi-gradient warming and grazing in alpine grasslands on the Tibetan Plateau. We show the following results: (i) Plant biodiversity, soil microbial diversity and community productivity in alpine grasslands show fluctuating trends with temperature gradients, and a temperature increase below approximately 1 °C is beneficial to alpine grasslands; moderate grazing only increases the fungal diversity of the soil surface layer. (ii) The warming shifted plant biomass underground in alpine grasslands to obtain more water in response to the decrease in soil moisture caused by the temperature rise. Community stability was not affected by warming or grazing. (iii) Community stability was not significantly correlated with productivity, and environmental factors, rather than biodiversity, influenced community stability and productivity.

Quantitative analysis of vegetation restoration and potential driving factors in a typical subalpine region of the Eastern Tibet Plateau

Vegetation restoration is an essential approach to re-establish the ecological balance in subalpine areas. Changes in vegetation cover represent, to some extent, vegetation growth trends and are the consequence of a complex of different natural factors and human activities. Microtopography influences vegetation growth by affecting the amount of heat and moisture reaching the ground, a role that is more pronounced in subalpine areas. However, little research is concerned with the characteristics and dynamics of vegetation restoration in different microtopography types. The respective importance of the factors driving vegetation changes in subalpine areas is also not clear yet. We used linear regression and the Hurst exponent to analyze the trends in vegetation restoration and sustainability in different microtopography types since 2000, based on Fractional Vegetation Cover (FVC) and identified potential driving factors of vegetation change and their importance by using Geographical Detector. The results show that: (1) The FVC in the region under study has shown an up-trend since 2000, and the rate of increase is 0.26/year (P = 0.028). It would be going from improvement to degradation, continuous decrease or continuous significant decrease in 47.48% of the region, in the future. (2) The mean FVC is in the following order: lower slope (cool), lower slope, lower slope (warm), valley, upper slope (warm), upper slope, valley (narrow), upper slope (cool), cliff, mountain/divide, peak/ridge (warm), peak/ridge, peak/ridge (cool). The lower slope is the microtopographic type with the best vegetation cover, and ridge peak is the most difficult to be afforested. (3) The main factors affecting vegetation restoration in subalpine areas are aspect, microtopographic type, and soil taxonomy great groups. The interaction between multiple factors has a much stronger effect on vegetation cover than single factors, with the effect of temperatures and aspects having the most significant impact on the vegetation cover changes. Natural factors have a greater impact on vegetation restoration than human factors in the study area. The results of this research can contribute a better understanding of the influence of different drivers on the change of vegetation cover, and provide appropriate references and recommendations for vegetation restoration and sustainable development in typical logging areas in subalpine areas.

Spatial Pattern and Dynamic Change of Vegetation Greenness From 2001 to 2020 in Tibet, China

Due to the cold climate and dramatically undulating altitude, the identification of dynamic vegetation trends and main drivers is essential to maintain the ecological balance in Tibet. The normalized difference vegetation index (NDVI), as the most commonly used greenness index, can effectively evaluate vegetation health and spatial patterns. MODIS-NDVI (Moderate-resolution Imaging Spectroradiometer-NDVI) data for Tibet from 2001 to 2020 were obtained and preprocessed on the Google Earth Engine (GEE) cloud platform. The Theil-Sen median method and Mann-Kendall test method were employed to investigate dynamic NDVI changes, and the Hurst exponent was used to predict future vegetation trends. In addition, the main drivers of NDVI changes were analyzed. The results indicated that (1) the vegetation NDVI in Tibet significantly increased from 2001 to 2020, and the annual average NDVI value fluctuated between 0.31 and 0.34 at an increase rate of 0.0007 year^-1; (2) the vegetation improvement area accounted for the largest share of the study area at 56.6%, followed by stable unchanged and degraded areas, with proportions of 27.5 and 15.9%, respectively. The overall variation coefficient of the NDVI in Tibet was low, with a mean value of 0.13; (3) The mean value of the Hurst exponent was 0.53, and the area of continuously improving regions accounted for 41.2% of the study area, indicating that the vegetation change trend was continuous in most areas; (4) The NDVI in Tibet indicated a high degree of spatial agglomeration. However, there existed obvious differences in the spatial distribution of NDVI aggregation areas, and the aggregation types mainly included the high-high and low-low types; and (5) Precipitation and population growth significantly contributed to vegetation cover improvement in western Tibet. In addition, the use of the GEE to obtain remote sensing data combined with time-series data analysis provides the potential to quickly obtain large-scale vegetation change trends.

Seasonal Variation of Vegetation and Its Spatiotemporal Response to Climatic Factors in the Qilian Mountains, China

The purpose of this study is to reveal the seasonal difference in vegetation variation and its seasonal response to climate factors in the Qilian Mountains (QM) under the background of global warming. Based on the MOD13 A2 normalized difference vegetation index (NDVI) data and meteorological data, this study analyzed the spatiotemporal dynamics and stability of vegetation in different seasons by using the mean value method, trend analysis and stability analysis method, and discussed their seasonal responses to climatic factors based on the correlation analysis method. The results show that the vegetation cover in the QM experienced a significant upward trend in the past 21 years, but there were obvious spatial differences in vegetation change in different seasons. The growth rate of vegetation in summer was the fastest, and summer vegetation provided the most significant contribution to the growing season vegetation. The order of vegetation stability in the QM among the seasons was growing season > summer > spring > autumn. The vegetation change was obviously affected by temperature in spring, while it was mainly controlled by precipitation in the growing season and summer. The response of vegetation to climatic factors was not significant in autumn. Our results can provide important data support for ecological protection in the QM and socioeconomic development in the Hexi Corridor.

Effects of Environmental Factors on the Changes in MODIS NPP along DEM in Global Terrestrial Ecosystems over the Last Two Decades

Global warming has exerted widespread impacts on the terrestrial ecosystem in the past three decades. Vegetation is an important part of the terrestrial ecosystem, and its net primary productivity (NPP) is an important variable in the exchange of materials and energy in the terrestrial ecosystem. However, the effect of climate variation on the spatial pattern of zonal distribution of NPP has remained unclear over the past two decades. Therefore, we analyzed the spatiotemporal patterns and trends of MODIS NPP and environmental factors (temperature, radiation, and soil moisture) derived from three sets of reanalysis data. The moving window method and digital elevation model (DEM) were used to explore their changes along elevation gradients. Finally, we explored the effect of environmental factors on the changes in NPP and its elevation distribution patterns. Results showed that nearly 60% of the global area exhibited an increase in NPP with increasing elevation. Soil moisture has the largest uncertainty either in the spatial pattern or inter-annual variation, while temperature has the smallest uncertainty among the three environmental factors. The uncertainty of environmental factors is also reflected in its impact on the elevation distribution of NPP, and temperature is still the main dominating environmental factor. Our research results imply that the carbon sequestration capability of vegetation is becoming increasingly prominent in high-elevation regions. However, the quantitative evaluation of its carbon sink (source) functions needs further research under global warming.

Detecting the Turning Points of Grassland Autumn Phenology on the Qinghai-Tibetan Plateau: Spatial Heterogeneity and Controls

Autumn phenology, commonly represented by the end of season (EOS), is considered to be the most sensitive and crucial productivity indicator of alpine and cold grassland in the Qinghai-Tibetan Plateau. Previous studies typically assumed that the rates of EOS changes remain unchanged over long time periods. However, pixel-scale analysis indicates the existence of turning points and differing EOS change rates before and after these points. The spatial heterogeneity and controls of these turning points remain unclear. In this study, the EOS turning point changes are extracted and their controls are explored by integrating long time-series remote sensing images and piecewise regression methods. The results indicate that the EOS changed over time with a delay rate of 0.08 days/year during 1982–2015. The rates of change are not consistent over different time periods, which clearly highlights the existence of turning points. The results show that temperature contributed most strongly to the EOS changes, followed by precipitation and insolation. Furthermore, the turning points of climate, human activities (e.g., grazing, economic development), and their intersections are found to jointly control the EOS turning points. This study is the first quantitative investigation into the spatial heterogeneity and controls of the EOS turning points on the Qinghai-Tibetan Plateau, and provides important insight into the growth mechanism of alpine and cold grassland.

Greening of the Qinghai–Tibet Plateau and Its Response to Climate Variations along Elevation Gradients

The vegetation of the Qinghai–Tibet Plateau (QTP) is vital to the global climate change and ecological security of China. However, the impact of climate variation on the spatial pattern and zonal distribution of vegetation in the QTP remains unclear. Accordingly, we used multisource remote-sensing vegetation indices (GIMMS-LAI, GIMMS NDVI, GLOBMAP LAI, MODIS EVI, MODIS NDVI, and MODIS NIRv), climate data, a digital elevation model, and the moving window method to investigate the changes in vegetation greenness and its response to climate variations in the QTP from 2001 to 2016. Results showed that the vegetation was greening in the QTP, which might be attributed to the increases in temperature and radiation. By contrast, the browning of vegetation may be caused by drought. Notably, the spatial patterns of vegetation greenness and its variations were linearly correlated with climate at low altitudes, and vegetation greenness was non-linearly correlated with climate at high altitudes. The Northwestern QTP needs to be focused on in regard to positive and decreased VGEG (vegetation greenness along the elevation gradient). The significantly positive VGEG was up to (34.37 ± 2.21) % of the QTP, which indicated a homogenization of vegetation greenness on elevation. This study will help us to understand the spatial distribution of vegetation greenness and VGEG in the QTP under global warming, and it will benefit ecological environment management, policymaking, and future climate and carbon sink (source) prediction.

Evaluating the Applicability of a Quantile–Quantile Adjustment Approach for Downscaling Monthly GCM Projections to Site Scale over the Qinghai-Tibet Plateau

In the context of global climate change, the Qinghai-Tibetan plateau (QTP) has experienced unprecedented changes in its local climate. While general circulation models (GCM) are able to forecast global-scale future climate change trends, further work needs to be done to develop techniques to apply GCM-predicted trends at site scale to facilitate local ecohydrological response studies. Given the QTP’s unique altitude-controlled climate pattern, the applicability of the quantile–quantile (Q-Q) adjustment approach for this purpose remains largely unknown and warrants investigation. In this study, this approach was evaluated at 36 sites to ensure the results are representative of different climatic and surface conditions on the QTP. Considering the practical needs of QTP studies, the study aims to assess its capability for downscaling monthly GCM simulations of major variables onto the site scale, including precipitation, air temperature, wind speed, relative humidity, and air pressure, based on two GCMs. The calibrated projections at the sites were verified against the observations and compared with those from two commonly used adjustment methods—the quantile-mapping method and the delta method. The results show that the general trends of most variables considered are well adjusted at all sites, with a quantile pair of 25–75% for all the variables except precipitation where 10–90% is used. The calibrated results are generally close to the observed values, with the best performance in air pressure, followed by air temperature and relative humidity. The performance is relatively limited in adjusting wind speed and precipitation. The accuracies decline as the adjustment extends into the future; a wider adjustment window may help increase the performance for the variables subject to climate changes. It is found that the performance of the adjustment is generally independent of the locations and seasons, but is strongly determined by the quality of GCM simulations. The Q-Q adjustment works better for the meteorological variables with fewer fluctuations and daily extremes. Variables with more similarities in probability density functions between the observations and GCM simulations tend to perform better in adjustment. Generally, this approach outperforms the two peer methods with broader applicability and higher accuracies for most major variables.

Spatial–Temporal Characteristics of Precipitation and Its Relationship with Land Use/Cover Change on the Qinghai-Tibet Plateau, China

The Qinghai-Tibet Plateau (QTP) is an area sensitive to global climate change, and land use/land cover change (LUCC) plays a vital role in regulating climate system at different temporal and spatial scales. In this study, we analyzed the temporal and spatial trend of precipitation and the characteristics of LUCC on the QTP. Meanwhile, we also used the normalized difference vegetation index (NDVI) as an indicator of LUCC to discuss the relationship between LUCC and precipitation. The results show the following: (1) Annual precipitation showed a fluctuant upward trend at a rate of 11.5 mm/decade in this area from 1967 to 2016; three periods (i.e., 22 years, 12 years, and 2 years) of oscillations in annual precipitation were observed, in which expectant 22 years is the main oscillation period. It was predicted that QTP will still be in the stage of increasing precipitation. (2) The LUCC of the plateau changed apparently from 1980 to 2018. The area of grassland decreased by 9.47%, and the area of unused land increased by 7.25%. From the perspective of spatial distribution, the transfer of grassland to unused land occurred in the western part of the QTP, while the reverse transfer was mainly distributed in the northwestern part of the QTP. (3) NDVI in the northern and southwestern parts of the QTP is positively correlated with precipitation, while negative correlations are mainly distributed in the southeast of the QTP, including parts of Sichuan and Yunnan Province. Our results show that precipitation in the QTP has shown a fluctuating growth trend in recent years, and precipitation and NDVI are mainly positively correlated. Furthermore, we hope that this work can provide a theoretical basis for predicting regional hydrology, climate change, and LUCC research.

Spatial and Temporal Differences in Alpine Meadow, Alpine Steppe and All Vegetation of the Qinghai-Tibetan Plateau and Their Responses to Climate Change

Alpine meadow and alpine steppe are the two most widely distributed nonzonal vegetation types in the Qinghai-Tibet Plateau. In the context of global climate change, the differences in spatial-temporal variation trends and their responses to climate change are discussed. It is of great significance to reveal the response of the Qinghai-Tibet Plateau to global climate change and the construction of ecological security barriers. This study takes alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau as the research objects. The normalized difference vegetation index (NDVI) data and meteorological data were used as the data sources between 2000 and 2018. By using the mean value method, threshold method, trend analysis method and correlation analysis method, the spatial and temporal variation trends in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau were compared and analyzed, and their differences in the responses to climate change were discussed. The results showed the following: (1) The growing season length of alpine meadow was 145~289 d, while that of alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau was 161~273 d, and their growing season lengths were significantly shorter than that of alpine meadow. (2) The annual variation trends of the growing season NDVI for the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau increased obviously, but their fluctuation range and change rate were significantly different. (3) The overall vegetation improvement in the Qinghai-Tibet Plateau was primarily dominated by alpine steppe and alpine meadow, while the degradation was primarily dominated by alpine meadow. (4) The responses between the growing season NDVI and climatic factors in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau had great spatial heterogeneity in the Qinghai-Tibet Plateau. These findings provide evidence towards understanding the characteristics of the different vegetation types in the Qinghai-Tibet Plateau and their spatial differences in response to climate change.

Response of Natural Vegetation to Climate in Dryland Ecosystems: A Comparative Study between Xinjiang and Arizona

As one of the most sensitive areas to climate change, drylands cover ~40% of the Earth’s terrestrial land surface and host more than 38% of the global population. Meanwhile, their response to climate change and variability carries large uncertainties as induced by background climate, topography, and land cover composition; but there is a lack of intercomparison of different dryland ecosystems. In this study, we compare the changing climate and corresponding responses of major natural vegetation cover types in Xinjiang and Arizona, two typical drylands with similar landscapes in Asia and North America. Long-term (2002–2019) quasi-8-day datasets of daily precipitation, daily mean temperature, and Normalized Difference Vegetation Index (NDVI) were constructed based on station observations and remote sensing products. We found that much of Xinjiang experienced warming and wetting trends (although not co-located) over the past 18 years. In contrast, Arizona was dominated by warming with insignificant wetting or drying trends. Significant greening trends were observed in most parts of both study areas, while the increasing rate of NDVI anomalies was relatively higher in Xinjiang, jointly contributed by its colder and drier conditions. Significant degradation of vegetation growth (especially for shrubland) was observed over 18.8% of Arizona due to warming. Our results suggest that responses of similar natural vegetation types under changing climate can be diversified, as controlled by temperature and moisture in areas with different aridity.