Environmental changes, such as climate warming and higher herbivory pressure, are altering the carbon balance of Arctic ecosystems; yet, how these drivers modify the carbon balance among different habitats remains uncertain. This hampers our ability to predict changes in the carbon sink strength of tundra ecosystems. We investigated how spring goose grubbing and summer warming-two key environmental-change drivers in the Arctic-alter CO2 fluxes in three tundra habitats varying in soil moisture and plant-community composition. In a full-factorial experiment in high-Arctic Svalbard, we simulated grubbing and warming over two years and determined summer net ecosystem exchange (NEE) alongside its components: gross ecosystem productivity (GEP) and ecosystem respiration (ER). After two years, we found net CO2 uptake to be suppressed by both drivers depending on habitat. CO2 uptake was reduced by warming in mesic habitats, by warming and grubbing in moist habitats, and by grubbing in wet habitats. In mesic habitats, warming stimulated ER (+75%) more than GEP (+30%), leading to a 7.5-fold increase in their CO2 source strength. In moist habitats, grubbing decreased GEP and ER by similar to 55%, while warming increased them by similar to 35%, with no changes in summer-long NEE. Nevertheless, grubbing offset peak summer CO2 uptake and warming led to a twofold increase in late summer CO2 source strength. In wet habitats, grubbing reduced GEP (-40%) more than ER (-30%), weakening their CO2 sink strength by 70%. One-year CO2-flux responses were similar to two-year responses, and the effect of simulated grubbing was consistent with that of natural grubbing. CO2-flux rates were positively related to aboveground net primary productivity and temperature. Net ecosystem CO2 uptake started occurring above similar to 70% soil moisture content, primarily due to a decline in ER. Herein, we reveal that key environmental-change drivers-goose grubbing by decreasing GEP more than ER and warming by enhancing ER more than GEP-consistently suppress net tundra CO2 uptake, although their relative strength differs among habitats. By identifying how and where grubbing and higher temperatures alter CO2 fluxes across the heterogeneous Arctic landscape, our results have implications for predicting the tundra carbon balance under increasing numbers of geese in a warmer Arctic.

The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify the drought-vegetation interaction in this area under the influence of climate-permafrost coupling. In this study, based on the saturated vapor pressure deficit (VPD) and soil moisture (SM) that characterize atmospheric and soil drought, as well as the Normalized Differential Vegetation Index (NDVI) and solar-induced fluorescence (SIF) that characterize vegetation greenness and function, the evolution of regional vegetation productivity and drought were systematically identified. On this basis, the technical advantages of the causal discovery algorithm Peter-Clark Momentary Conditional Independence (PCMCI) were applied to distinguish the response of vegetation to VPD and SM. Furthermore, this study delves into the response mechanisms of NDVI and SIF to atmospheric and soil drought, considering different vegetation types and permafrost degradation areas. The findings indicated that low SM and high VPD were the limiting factors for vegetation growth. The positive and negative causal effects of VPD on NDVI accounted for 47.88% and 52.12% of the total area, respectively. Shrubs were the most sensitive to SM, and the response speed of grassland to SM was faster than that of forest land. The impact of SM on vegetation in the SRYY was stronger than that of VPD, and the effect in the frozen soil degradation area was more obvious. The average causal effects of NDVI and SIF on SM in the frozen soil degradation area were 0.21 and 0.41, respectively, which were twice as high as those in the whole area, and SM dominated NDVI (SIF) changes in 62.87% (76.60%) of the frozen soil degradation area. The research results can provide important scientific basis and theoretical support for the scientific assessment and adaptation of permafrost, vegetation, and climate change in the source area and provide reference for ecological protection in permafrost regions.

For the period 2001-2020, the interannual variability of the normalized difference vegetation index (NDVI) is investigated in connection to Indian summer monsoon rainfall (ISMR). According to Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data, the ISMR and the vegetative activity of the Indo-Gangetic plain (IGP) in the month of January show a significant negative association. We hypothesized that the January vegetation state affects the ISMR via a delayed hydrological response, in which the wet soil moisture anomaly formed throughout the winter to accommodate the water needs of intensive farming influences the ISMR. The soil moisture anomalies developed in the winter, particularly in the root zone, persisted throughout the summer. Evaporative cooling triggered by increasing soil moisture lowers the summer surface temperature across the IGP. The weakening of monsoon circulation as a result of the reduced intensity of land-sea temperature contrast led in rainfall suppression. Further investigation shows that moisture transport has increased significantly over the past two decades as a result of increasing westerly over the Arabian Sea, promoting rainfall over India. Agriculture activities, on the other hand, have resulted in greater vegetation in India's northwest and IGP during the last two decades, which has a detrimental impact on rainfall processes. Rainfall appears to have been trendless during the last two decades as a result of these competing influences. With a lead time of 5 months, this association between January's vegetation and ISMR could be one of the potential predictors of seasonal rainfall variability.

Understanding vegetation changes and their driving forces in global alpine areas is critical in the context of climate change. We aimed to reveal the changing trend in global alpine vegetation from 1981 to 2015 using the least squares regression method and Mann-Kendall (MK) test. The area-of-influence dominated by anthropogenic activity and natural factors was determined in an area with significant vegetation change by residual analysis; the primary driving force of vegetation change in the area-of-influence dominated by natural factors was identified using the partial correlation method. The results showed that (1) the vegetation in the global alpine area exhibited a browning trend from 1981 to 2015 on the annual scale; however, a greening trend was observed from May to July on the month scale. (2) The influence of natural factors was greater than that of anthropogenic activities, and the positive impact of natural factors was greater than the negative impact. (3) Among the factors that were often considered as the main natural factors, the contribution of albedo to significant changes in vegetation were greater than that of temperature, precipitation, soil moisture, and sunshine duration. This study provides a scientific basis for the protection of vegetation and sustainable development in alpine regions.

Little is known about the mechanism of climate-vegetation coverage coupled changes in the Tibetan Plateau (TP) region, which is the most climatically sensitive and ecologically fragile region with the highest terrain in the world. This study, using multisource datasets (including satellite data and meteorological observations and reanalysis data) revealed the mutual feedback mechanisms between changes in climate (temperature and precipitation) and vegetation coverage in recent decades in the Hengduan Mountains Area (HMA) of the southeastern TP and their influences on climate in the downstream region, the Sichuan Basin (SCB). There is mutual facilitation between rising air temperature and increasing vegetation coverage in the HMA, which is most significant during winter, and then during spring, but insignificant during summer and autumn. Rising temperature significantly enhances local vegetation coverage, and vegetation greening in turn heats the atmosphere via enhancing net heat flux from the surface to the atmosphere. The atmospheric heating anomaly over the HMA thickens the atmospheric column and increases upper air pressure. The high pressure anomaly disperses downstream via the westerly flow, expands across the SCB, and eventually increases the SCB temperature. This effect lasts from winter to the following spring, which may cause the maximum increasing trend of the SCB temperature and vegetation coverage in spring. These results are helpful for estimating future trends in climate and eco-environmental variations in the HMA and SCB under warming scenarios, as well as seasonal forecasting based on the connection between the HMA eco-environment and SCB climate.

With a typical alpine grassland ecosystem, the Tibetan Plateau (TP) is a highly representative region to observe the effects of climate change on ecosystems. Continued global warming has increased the drought risk of TP, yet the response of vegetation to drought remains unclear. To understand the spatial heterogeneity of the vegetation response to drought and identify the key control factors of vegetation response to drought in different elevation intervals on TP, we introduced three vegetation indexes (EVI, LAI, and GPP) and multi-scale drought indexes, including the Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI), to determine the spatial response of vegetation growth to drought from 2000 to 2015. Land surface temperature (LST), land cover, snow cover, population density, and soil texture were selected as potential control factors. The mean values of the maximum correlation coefficients for the six combinations indicated that 14.3%/12.0% (SPI/SPEI) of the vegetation growth on TP was significantly affected by water conditions (p < 0.05). The extent of vegetation growth responses to drought were mainly influenced by LST with the highest contribution rate of 65.8% at 3000-4500 m intervals. The response time is mainly dependent on the proportion of grassland, with the highest contribution rate of 81.7% at 4500-6000 m intervals. The results provide reasonable evidence for understanding the spatial heterogeneity of the elevation dependence of the alpine ecosystem response to drought.

The Mongolian Plateau is one of the regions most sensitive to climate change, the more obvious increase of temperature in 21st century here has been considered as one of the important causes of drought and desertification. It is very important to understand the multi-year variation and occurrence characteristics of drought in the Mongolian Plateau to explore the ecological environment and the response mechanism of surface materials to climate change. This study examines the spatio-temporal variations in drought and its frequency of occurrence in the Mongolian Plateau based on the Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) (1982-1999) and the Moderate-resolution Imaging Spectroradiometer (MODIS) (2000-2018) datasets; the Temperature Vegetation Dryness Index (TVDI) was used as a drought evaluation index. The results indicate that drought was widespread across the Mongolian Plateau between 1982 and 2018, and aridification incremented in the 21st century. Between 1982 and 2018, an area of 164.38 x 10(4) km(2)/yr suffered from drought, accounting for approximately 55.28% of the total study area. An area of approximately 150.06 x 10(4) km(2) (51.43%) was subject to more than 160 droughts during 259 months of the growing seasons between 1982 and 2018. We observed variable frequencies of drought occurrence depending on land cover/land use types. Drought predominantly occurred in bare land and grassland, both of which accounting for approximately 79.47% of the total study area. These terrains were characterized by low vegetation and scarce precipitation, which led to frequent and extreme drought events. We also noted significant differences between the areal distribution of drought, drought frequency, and degree of drought depending on the seasons. In spring, droughts were widespread, occurred with a high frequency, and were severe; in autumn, they were localized, frequent, and severe; whereas, in summer, droughts were the most widespread and frequent, but less severe. The increase in temperature, decrease in precipitation, continuous depletion of snow cover, and intensification of human activities have resulted in a water deficit. More severe droughts and aridification have affected the distribution and functioning of terrestrial ecosystems, causing changes in the composition and distribution of plants, animals, microorganisms, conversion between carbon sinks and carbon sources, and biodiversity. We conclude that regional drought events have to be accurately monitored, whereas their occurrence mechanisms need further exploration, taking into account nature, climate, society and other influencing factors.

Recent efforts have been made to monitor the seasonal metrics of plant canopy variations globally from space, using optical remote sensing. However, phenological estimations based on vegetation indices (VIs) in high-latitude regions such as the pan-Arctic remain challenging and are rarely validated. Nevertheless, pan-Arctic ecosystems are vulnerable and also crucial in the context of climate change. We reported the limitations and challenges of using MODerate-resolution Imaging Spectroradiometer (MODIS) measurements, a widely exploited set of satellite measurements, to estimate phenological transition dates in pan-Arctic regions. Four indices including normalized vegetation difference index (NDVI), enhanced vegetation index (EVI), phenology index (PI), plant phenological index (PPI) and a MODIS Land Cover Dynamics Product MCD12Q2, were evaluated and compared against eddy covariance (EC) estimates at 11 flux sites of 102 site-years during the period from 2000 to 2014. All the indices were influenced by snow cover and soil moisture during the transition dates. While relationships existed between VI-based and EC-estimated phenological transition dates, the R-2 values were generally low (0.01-0.68). Among the VIs, PPI-estimated metrics showed an inter-annual pattern that was mostly closely related to the EC-based estimations. Thus, further studies are needed to develop region-specific indices to provide more reliable estimates of phenological transition dates.

The Three-River Source Region (TRSR) of the Tibetan Plateau (TP) is regarded as the Chinese water tower. Climate warming and the associated degradation of permafrost might change the water cycle and affect the alpine vegetation growth in the TRSR. However, the quantitative changes in the water budget and their impacts on the vegetation in the TRSR are poorly understood. In this study, the spatial-temporal changes in the hydrological variables and the normalized difference vegetation index (NDVI) during 2003-2014 were investigated using multiple satellite data and a remote sensing energy balance model. The results indicated that precipitation showed an increasing trend at a rate of 14.0 mm 10 a(-1), and evapotranspiration (ET) showed a slight decreasing trend. The GRACE-derived total water storage (TWS) change presented a significant increasing trend at a rate of 35.1 mm a(-1). The change in groundwater (GW) which showed an increasing trend at a rate of 18.5 mm a(-1), was estimated by water budget. The time lag of the GRACE-TWS that was influenced by precipitation was more obviously than was the GLDAS-SM(Soil Moisture) change. The vegetation in the TRSR was greening during the study period, and the accumulation of the NDVI increased rapidly after 2008. The effect of total TWS and GLDAS-SM on vegetation was considerably more than that the effects of other factors in this region. It was concluded that the hydrological cycle had obviously changed and that more soil water was transferred into the GW since the aquiclude changed due to climate warming. The increasing area and number of lakes and the thickening of the active layer in the permafrost area led to the greater infiltration of surface water into the groundwater, which resulted in increased water storage. (C) 2018 Elsevier B.V. All rights reserved.

Mountains form distinct geographical units with complex topographic and climatic features. Mountain ecosystems, especially those in arid and semi-arid regions, are likely to be strongly influenced by climate change. The NDVI-based vegetation response to climate change was analyzed in the Tianshan Mountains in China, one of the largest mountain systems of central Asia. Datasets, including the Normalized Difference Vegetation Index (NDVI), precipitation, soil moisture, and snow cover, were used to analyze spatial patterns of NDVI during 2001-2013. A trend test and correlation analysis were used to verify the results. Results showed that: (1) Spatial patterns of NDVI in the Tianshan Mountains revealed significant differences during 2001-2013. A decreasing trend appeared mainly in the Ili River Valley (<-0.005 NDVI/year), the Kaidu River (-0.01 to -0.005 NDVI/year), and Bogda Shan (-0.005 to 0 NDVI/year). NDVI in the western Tianshan Mountains, eastern and western Bogda Shan showed an increasing trend. (2) Spring NDVI in the Tianshan Mountains decreased, while summer NDVI increased during 2001-2013. (3) Spatial variations in vegetation dynamics were attributed to the interaction of the four spheres of the earth's system, hydrosphere-pedosphere-atmosphere-biosphere. The main contributors including temperature, precipitation, and soil moisture had a notable effect on variations in vegetation. (4) The snow cover in the mountains was crucial for vegetation growth, especially in the winter half of the year. Understanding the spatial characteristics of NDVI in mountains under the effects of climate change will underpin further study in this ecological environment.