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Satellite observations show widespread increasing trends of leaf area index (LAI), known as the Earth greening. However, the biophysical impacts of this greening on land surface temperature (LST) remain unclear. Here, we quantify the biophysical impacts of Earth greening on LST from 2000 to 2014 and disentangle the contributions of different factors using a physically based attribution model. We find that 93% of the global vegetated area shows negative sensitivity of LST to LAI increase at the annual scale, especially for semiarid woody vegetation. Further considering the LAI trends ( P ≤ 0.1), 30% of the global vegetated area is cooled by these trends and 5% is warmed. Aerodynamic resistance is the dominant factor in controlling Earth greening’s biophysical impacts: The increase in LAI produces a decrease in aerodynamic resistance, thereby favoring increased turbulent heat transfer between the land and the atmosphere, especially latent heat flux. 

Warming-induced carbon loss through terrestrial ecosystem respiration ( Re ) is likely getting stronger in high latitudes and cold regions because of the more rapid warming and higher temperature sensitivity of Re ( Q 10 ). However, it is not known whether the spatial relationship between Q 10 and temperature also holds temporally under a future warmer climate. Here, we analyzed apparent Q 10 values derived from multiyear observations at 74 FLUXNET sites spanning diverse climates and biomes. We found warming-induced decline in Q 10 is stronger at colder regions than other locations, which is consistent with a meta-analysis of 54 field warming experiments across the globe. We predict future warming will shrink the global variability of Q 10 values to an average of 1.44 across the globe under a high emission trajectory (RCP 8.5) by the end of the century. Therefore, warming-induced carbon loss may be less than previously assumed because of Q 10 homogenization in a warming world. 

A wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities. 

China has increased its vegetation coverage and enhanced its terrestrial carbon sink through ecological restoration since the end of the 20th century. However, the temporal variation in vegetation carbon sequestration remains unclear, and the relative effects of climate change and ecological restoration efforts are under debate. By integrating remote sensing and machine learning with a modelling approach, we explored the biological and physical pathways by which both climate change and human activities (e.g., ecological restoration, cropland expansion, and urbanization) have altered Chinese terrestrial ecosystem structures and functions, including vegetation cover, surface heat fluxes, water flux, and vegetation carbon sequestration (defined by gross and net primary production, GPP and NPP). Our study indicated that during 2001–2018, GPP in China increased significantly at a rate of 49.1–53.1 TgC/yr², and the climatic and anthropogenic contributions to GPP gains were comparable (48%–56% and 44%–52%, respectively). Spatially, afforestation was the dominant mechanism behind forest cover expansions in the farming‐pastoral ecotone in northern China, on the Loess Plateau and in the southwest karst region, whereas climate change promoted vegetation cover in most parts of southeastern China. At the same time, the increasing trend in NPP (22.4–24.9 TgC/yr²) during 2001–2018 was highly attributed to human activities (71%–81%), particularly in southern, eastern, and northeastern China. Both GPP and NPP showed accelerated increases after 2010 because the anthropogenic NPP gains during 2001–2010 were generally offset by the climate‐induced NPP losses in southern China. However, after 2010, the climatic influence reversed, thus highlighting the vegetation carbon sequestration that occurs with ecological restoration.