Climate change and human activities have already caused degradation in a large fraction of vegetation on the Qinghai‐Tibetan Plateau (QTP). Many studies report that climate variability instead of overgrazing has been the primary cause for large‐scale vegetation cover changes on the QTP, for example, Lehnert et al., 2016, https://doi.org/10.1038/srep24367 . However, it remains unclear how human activities (mainly livestock grazing) regulate vegetation dynamics under climate change. This paper takes the AVHRR/GIMMS Normalized Difference Vegetation Index (NDVI) as an indicator to analyze the growth status of vegetation zones in the QTP, which has highly sensitive to climate change. The spatiotemporal dynamics of vegetation growth between 1981 and 2015 were analyzed. The dual effects of climate change and human activities were examined by correlation analyses of data from 87 meteorological stations and economic statistical data of the QTP. Results show that: (a) The vegetation in central and southwestern QTP with high altitudes was improving due to the warm‐humid climate trend. An increase in temperature and a reduction in the harsh frigid climate at high altitudes due to global warming has resulted in expansions of the vegetated areas, with the NDVI showing a concordant increase. (b) The degraded areas were mainly confined to the northern and eastern QTP, which have high human and livestock population densities. In comparison to gently changing climate regimes, anthropogenic activities such as chronic concentration of population and livestock in the valleys with a less harsh climate exerts a much stronger pressure on vegetation. The study indicates that the anthropogenic pressures are much more intensive than the impact of climate change and are critical for the conservation and sustainable management of the QTP vegetation.

Energy exchanges between atmosphere and glacier surface control the net energy available for snow and ice melt. Based on the meteorological records in Urumqi River Glacier No.1 (URGN1) in the Chinese Tien Shan during the period of 2012–2015, an energy-mass balance model was run to assess the sensitivity of glacier mass balance to air temperature (T), precipitation (P), incoming shortwave radiation (S_in), relative humidity (RH), and wind speed (u) in the URGN1, respectively. The results showed that the glacier melting was mainly controlled by the net shortwave radiation. The glacier mass balance was very sensitivity to albedo for snow and the time scale determining how long the snow albedo approaches the albedo for firn after a snowfall. The net annual mass balance of URGN1 was decreased by 0.44 m w.e. when increased by 1 K in air temperature, while it was increased 0.30 m w.e. when decreased by 1 K. The net total mass balance increased by 0.55 m w.e. when increased precipitation by 10%, while it was decreased by 0.61 m w.e. when decreased precipitation by 10%. We also found that the change in glacier mass balance was non-linear when increased or decreased input condition of climate change. The sensitivity of mass balance to increase in S_in, u, and RH were at −0.015 m w.e.%⁻¹, −0.020 m w.e.%⁻¹, and −0.018 m w.e.%⁻¹, respectively, while they were at 0.012 m w.e.%⁻¹, 0.027 m w.e.%⁻¹, and 0.017 m w.e.%⁻¹ when decreasing in those conditions, respectively. In addition, the simulations of coupled perturbation for temperature and precipitation indicated that the precipitation needed to increase by 23% could justly compensate to the additional mass loss due to increase by 1 K in air temperature. We also found that the sensitivities of glacier mass balance in response to climate change were different in different mountain ranges, which were mainly resulted from the discrepancies in the ratio of snowfall to precipitation during the ablation season, the amount of melt energy during the ablation season, and precipitation seasonality in the different local regions.

Temperature is one of the primary factors influencing the climate and ecosystem, and examining its change and fluctuation could elucidate the formation of novel climate patterns and trends. In this study, we constructed a generalised temperature zone elevation model (GTEM) to assess the trends of climate change and temporal-spatial differences in the Tibetan Plateau (TP) using the annual and monthly mean temperatures from 1961–2010 at 144 meteorological stations in and near the TP. The results showed the following: (1) The TP has undergone robust warming over the study period, and the warming rate was 0.318°C/decade. The warming has accelerated during recent decades, especially in the last 20 years, and the warming has been most significant in the winter months, followed by the spring, autumn and summer seasons. (2) Spatially, the zones that became significantly smaller were the temperature zones of −6°C and −4°C, and these have decreased 499.44 and 454.26 thousand sq km from 1961 to 2010 at average rates of 25.1% and 11.7%, respectively, over every 5-year interval. These quickly shrinking zones were located in the northwestern and central TP. (3) The elevation dependency of climate warming existed in the TP during 1961–2010, but this tendency has gradually been weakening due to more rapid warming at lower elevations than in the middle and upper elevations of the TP during 1991–2010. The higher regions and some low altitude valleys of the TP were the most significantly warming regions under the same categorizing criteria. Experimental evidence shows that the GTEM is an effective method to analyse climate changes in high altitude mountainous regions.

Topographic factors are critical for influencing vegetation distribution patterns, and studying the interactions between them can enhance our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000–2019), combined with the Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Qinghai-Tibet Plateau (QTP) in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000–2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the entire basin and each sub-basin. During 2000–2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with variations in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with higher NDVI in the southern regions NDVI than those in the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation. Our results confirmed the importance of topographic factors on vegetation growth processes and have implications for understanding the sustainable development of mountain ecosystems.