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.

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.

The Three-River Source Region (TRSR) is vital to the ecological security of China. However, the impact of global warming on the dynamics of vegetation along the elevation gradient in the TRSR remains unclear. Accordingly, we used multi-source remote sensing vegetation indices (VIs) (GIMMS (Global Inventory Modeling and Mapping Studies) LAI (Leaf Area Index), GIMMS NDVI (Normalized Difference Vegetation Index), GLOBMAP (Global Mapping) LAI, MODIS (Moderate Resolution Imaging Spectroradiometer) EVI (Enhanced Vegetation Index), MODIS NDVI, and MODIS NIRv (near-infrared reflectance of vegetation)) and digital elevation model data to study the changes of VGEG (Vegetation Greenness along the Elevation Gradient) in the TRSR from 2001 to 2016. Results showed that the areas with a positive correlation of vegetation greenness and elevation accounted for 36.34 ± 5.82% of the study areas. The interannual variations of VGEG showed that the significantly changed regions were mainly observed in the elevation gradient of 4–5 km. The VGEG was strongest in the elevation gradient of 4–5 km and weakest in the elevation gradient of >5 km. Correlation analysis showed that the mean annual temperature was positively correlated with VIs, and the effect of the mean annual precipitation on VIs was more obvious at low altitude than in high altitude. This study contributes to our understanding of the VGEG variation in the TRSR under global climate variation and also helps in the prediction of future carbon cycle patterns.

Although the afforestation of former arable lands is a common global land-use conversion, its impact on soil microbial communities at the aggregate scale has not been adequately addressed. In this study, soil samples were categorized into large macroaggregates (LM, >2 mm), small macroaggregates (SM, 2–0.25 mm), and microaggregates (MI, <0.25 mm) to assess the changes in microbial composition, diversity, network complexity, and network stability within soil aggregates after the afforestation of a former dryland in northwestern China. The results revealed that afforestation enhanced the relative abundance of Actinobacteriota, Chloroflexi, Ascomycota, and Mortierellomycota within the soil aggregates, suggesting that these phyla may have greater advantages in microbial communities post-afforestation. The Shannon–Wiener and Pielou indices for bacterial communities showed no significant differences between land-use types across all aggregate fractions. However, the alpha diversity of fungal communities within the LM and SM significantly increased after afforestation. Bray–Curtis dissimilarity indices showed that afforestation altered bacterial beta diversity within the LM and MI but had a minimal impact on fungal beta diversity across all three aggregate fractions. The topological features of cross-kingdom microbial co-occurrence networks within the soil aggregates generally exhibited a decreasing trend post-afforestation, indicating a simplification of microbial community structure. The reduced robustness of microbial networks within the LM and SM fractions implies that afforestation also destabilized the structure of microbial communities within the macroaggregates. The composition of the soil microbial communities correlated closely with soil carbon and nitrogen contents, especially within the two macroaggregate fractions. The linkages suggests that improved resource conditions could be a key driver behind the shifts in microbial communities within soil aggregates following afforestation. Our findings indicate that the impact of afforestation on soil microbial ecology can be better understood by soil aggregate fractionation.