To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together with CHIRPS rainfall and MODIS LST at annual, seasonal and monthly scales for the period spanning 2000 to 2022. Additionally, MODIS Potential Evapotranspiration (PET), Ground Water Storage (GWS), Soil Moisture (SM) and nighttime light datasets were compiled to explore their spatial relationships with vegetation and other selected environmental parameters. Non-parametric statistics were applied to estimate the magnitude of trends, along with correlation and residual trend analysis to quantify the relative influence of Climate Change (CC) and Human Activities (HA) on vegetation dynamics using Google Earth Engine algorithms. The study reveals regional contrasts in trends that are evidently related to elevation. An annual increasing trend in rainfall (21.3 mm/decade, p < 0.05), together with augmented vegetation cover and slightly cooler (-0.07 degrees C/decade) LST is revealed in the high-elevation areas. Meanwhile, LST in the plain regions exhibit a warming trend (0.02 degrees C/decade) and decreased in vegetation and rainfall, accompanied by substantial reductions in GWS and SM related to increased PET. Linear regression demonstrates a strongly significant relationship between rainfall and EVI (R-2 = 0.92), although a negative relationship is apparent between LST and vegetation (R-2 = -0.83). Additionally, increased LST in the lowelevation parts of the study area impacted PET (R-2 = 0.87), which triggered EVI loss (R2 = 0.93). Moreover, increased HA resulted in losses of 25.5 mm GSW and 1.5 mm SM annually. The relative contributions of CC and HA are shown to vary with elevation. At higher elevations, CC and HA contribute respectively 85% and 15% to the increase in EVI. However, at lower elevations, reduced EVI is largely (79%) due to human activities. This needs to be considered in managing the future of vulnerable socio-ecological systems in the state of Haryana.

Soil moisture (SM), as a crucial variable in the soil-vegetation-atmosphere continuum, plays an important role in the terrestrial water cycle. Analyzing SM's variation and driver factors is crucial to maintaining ecosystem diversity on the Tibetan Plateau (TP) and ensuring food security as well as water supply balance in developing countries. Gradual wetting of the soil has been detected and attributed to precipitation in this area. However, there is still a gap in understanding the potential mechanisms. It is unclear whether the greening, glacier melting, and different vegetation degradation caused by asymmetrical climate change and intensified human activities have significantly affected the balance of SM. Here, to test the hypothesis that heterogeneous SM caused by precipitation was subject to temperatures and anthropogenic constraints, GLDAS-2.1 (Global Land Data Assimilation System-2.1) SM products combined with the statistical downscaling and Geographic detectors were applied. The results revealed that: (1) Seasonal SM gradually increased (p < 0.05), while SM deficit frequently appeared with exposure to extreme climates, such as in the summer of 2010 and 2013, and changed into a pattern of precipitation transport to western dry lands in autumn. (2) There was a synergistic reaction between greening and local moisture in autumn. SM was dominated by low temperature (TMN) in winter, warming indirectly regulated SM by exacerbating the thawing of glaciers and permafrost. The spatial coupling between the faster rising rate of TMN and the frozen soil might further aggravate the imbalance of SM. (3) The land cover's mutual transformation principally affected SM in spring and autumn, and degradation accelerated the loss of SM replenished by precipitation. (4) Land cover responses were different; SM in grassland was less affected by external disturbance, while degraded woodland and shrub performed adaptive feedback under dry environments, SM increased by 0.05 and 0.04 m(3)/(m(3) 10a), respectively. Our research provides a scientific basis for improving hydrological models and developing vegetation restoration strategies for long-term adaptation to TP-changing environments.

Understanding terrestrial water storage (TWS) dynamics and associated drivers (e.g., climate variability, vegetation change, and human activities) across climate zones is essential for designing water resources management strategies in a changing environment. This study estimated TWS anomalies (TWSAs) based on the corrected Gravity Recovery and Climate Experiment (GRACE) gravity satellite data and derived driving factors for 214 watersheds across six climate zones in China. We evaluated the long-term trends and stationarities of TWSAs from 2004 to 2014 using the Mann-Kendall trend test and Augmented Dickey-Fuller stationarity test, respectively, and identified the key driving factors for TWSAs using the partial correlation analysis. The results indicated that increased TWSAs were observed in watersheds in tropical and subtropical climate zones, while decreased TWSAs were found in alpine and warm temperate watersheds. For tropical watersheds, increases in TWS were caused by increasing water conservation capacity as a result of large-scale plantations and the implementation of natural forest protection programs. For subtropical watersheds, TWS increments were driven by increasing precipitation and forestation. The decreasing tendency in TWS in warm temperate watersheds was related to intensive human activities. In the cold temperate zone, increased precipitation and soil moisture resulting from accelerated and advanced melting of frozen soils outweigh the above-ground evapotranspiration losses, which consequently led to the upward tendency in TWS in some watersheds (e.g., Xiaoxing'anling mountains). In the alpine climate zone, significant declines in TWS were caused by declined precipitation and soil moisture and increased evapotranspiration and glacier retreats due to global warming, as well as increased agriculture activities. These findings can provide critical scientific evidence and guidance for policymakers to design adaptive strategies and plans for watershed-scale water resources and forest management in different climate zones.

Oases, as complex geographical landscapes, are strongly influenced by both natural variation and human activities. However, they have degenerated because of unplanned land use and water resource development. The research of oasis changes has mostly discussed single components, but multiple components, especially spatial changes to oasis vegetation, need further strengthening. Land use and NDVI were extracted based on Landsat 5/8 and Mod13A3, respectively, and a transfer matrix was constructed to analyze changes of land use in the Hexi Corridor during 2000-2020. The significant changes in the area of each land use were also quantified. Combined with regional temperature and precipitation, interpolated from meteorological data, the correlations between regional temperature, precipitation, and vegetation coverage were calculated, especially in the quantized areas with significant associations. The results showed that the area of bare land or desert decreased, while the areas of agricultural and residential land increased. The normalized difference NDVI of the studied oases increased at the rate of 0.021 per decade, which was positively related to precipitation (p < 0.05), rather than temperature; of which, farmland and planted grass land were 55.65% and 33.79% in the significantly increased area. In the area of significant positive relation between NDVI and precipitation, the ratio of grassland, farmland, and forest was 79.21%, 12.82%, and 4.06%, respectively. Additionally, changes in oasis vegetation were determined primarily by agricultural activities, which reflected a combination of natural and anthropic influences.

Vegetation dynamics are sensitive to climate change and human activities, as vegetation interacts with the hydrosphere, atmosphere, and biosphere. The Yarlung Zangbo River (YZR) basin, with the vulnerable ecological environment, has experienced a series of natural disasters since the new millennium. Therefore, in this study, the vegetation dynamic variations and their associated responses to environmental changes in the YZR basin were investigated based on Normalized Difference Vegetation Index (NDVI) and Global Land Data Assimilation System (GLDAS) data from 2000 to 2016. Results showed that (1) the YZR basin showed an obvious vegetation greening process with a significant increase of the growing season NDVI (Z(c) = 2.31, p < 0.05), which was mainly attributed to the wide greening tendency of the downstream region that accounted for over 50% area of the YZR basin. (2) Regions with significant greening accounted for 25.4% of the basin and were mainly concentrated in the Nyang River and Parlung Tsangpo River sub-basins. On the contrary, the browning regions accounted for <25% of the basin and were mostly distributed in the urbanized cities of the midstream, implying a significant influence of human activities on vegetation greening. (3) The elevation dependency of the vegetation in the YZR basin was significant, showing that the vegetation of the low-altitude regions was better than that of the high-altitude regions. The greening rate exhibited a significantly more complicated relationship with the elevation, which increased with elevated altitude (above 3500 m) and decreased with elevated altitude (below 3500 m). (4) Significantly positive correlations between the growing season NDVI and surface air temperature were detected, which were mainly distributed in the snow-dominated sub-basins, indicating that glaciers and snow melting processes induced by global warming play an important role in vegetation growth. Although basin-wide non-significant negative correlations were found between precipitation and growing season NDVI, positive influences of precipitation on vegetation greening occurred in the arid and semi-arid upstream region. These findings could provide important information for ecological environment protection in the YZR basin and other high mountain regions.

The Qinghai-Tibet Engineering Corridor (QTEC) in China may reflect the changes in the alpine ecosystem of the Qinghai-Tibet Plateau (QTP) that are driven by global climate change combined with intensive human activities. We used the normalized difference vegetation index (NDVI) as an indicator of alpine vegetation activity and the permafrost active layer thickness (ALT) as an indicator of permafrost dynamics to understand the impacts of climate change, human activity, or their combination on the alpine ecosystem in the QTEC. Based on the types of frozen ground, we separated the QTEC into northern, permafrost, and southern zones. The surface air temperature increased by 0.28 degrees C per decade from 1982 to 2010, and the rising trend of air temperature was most prominent in the permafrost zone (P < 0.05); the total precipitation exhibited a significant increase of 15 mm per decade (P < 0.05). The level of human activity in the QTEC rose slowly before 2000 and rapidly after 2000. The NDVI trends over the QTEC increased over the past thirty years, but the NDVI declined in some areas from 2001 to 2010, especially in the southern QTEC. The permafrost in the QTEC continued to thaw, and the ALT increased. Our results indicated that the QTEC experienced a significant warming and wetting trend. The increased precipitation improved the alpine vegetation activity across much of the QTEC, and the increased air temperature accelerated the thawing of permafrost. However, the construction and operation of the Qinghai-Tibet Railway since 2001 and 2006 promoted an influx of residents and tourists, boosted the local economy, and resulted in the deterioration of the alpine vegetation, particularly in the southern QTEC. Moreover, our results suggested that improvement of alpine vegetation cannot necessarily prevent permafrost degradation caused by warming.

The Qinghai-Tibet (QT) Plateau Engineering Corridor is located in the hinterland of the QT Plateau, which is highly sensitive to global climate change. Climate change causes permafrost degradation, which subsequently affects vegetation growth. This study focused on the vegetation dynamics and their relationships with climate change and human activities in the region surrounding the QT Plateau Engineering Corridor. The vegetation changes were inferred by applying trend analysis, the Mann-Kendall trend test and abrupt change analysis. Six key regions, each containing 40 nested quadrats that ranged in size from 500 x 500 m to 20 x 20 km, were selected to determine the spatial scales of the impacts from different factors. Cumulative growing season integrated enhanced vegetation index (CGSIEVI) values were calculated for each of the nested quadrats of different sizes to indicate the overall vegetation state over the entire year at different spatial scales. The impacts from human activities, a sudden increase in precipitation and permafrost degradation were quantified at different spatial scales using the CGSIEVI values and meteorological data based on the double mass curve method. Three conclusions were derived. First, the vegetation displayed a significant increasing trend over 23.6% of the study area. The areas displaying increases were mainly distributed in the Hoh Xil. Of the area where the vegetation displayed a significant decreasing trend, 72.4% was made up of alpine meadows. Second, more vegetation, especially the alpine meadows, has begun to degenerate or experience more rapid degradation since 2007 due to permafrost degradation and overgrazing. Finally, an active layer depth of 3 m to 3.2 m represents a limiting depth for alpine meadows.

Terrestrial water storage (TWS) change is an indicator of climate change. Therefore, it is helpful to understand how climate change impacts water systems. In this study, the influence of climate change on TWS in Central Asia over the past decade was analyzed using the Gravity Recovery and Climate Experiment satellites and Climatic Research Unit datasets. Results indicate that TWS experienced a decreasing trend in Central Asia from 2003 to 2013 at a rate of-4.44 +/- 2.2 mm/a, and that the maximum positive anomaly for TWS (46 mm) occurred in July 2005, while the minimum negative anomaly (-32.5 mm) occurred in March 2008-August 2009. The decreasing trend of TWS in northern Central Asia (-3.86 +/- 0.63 mm/a) is mainly attributed to soil moisture storage depletion, which is driven primarily by the increase in evapotranspiration. In the mountainous regions, climate change exerted an influence on TWS by affecting glaciers and snow cover change. However, human activities are now the dominant factor driving the decline of TWS in the Aral Sea region and the northern Tarim River Basin. (C) 2016 Elsevier B.V. All rights reserved.