Satellite data reveal widespread changes in Earth’s vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO2 fertilization, climate change, and consequent disturbances such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at the biome level that can be scaled to a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies for vegetation changes and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying causal counterfactual theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). The probabilistic attribution method clearly identifies the CO2 fertilization effect as the dominant driver in only two biomes, the temperate forests and cool grasslands, challenging the view of a dominant global-scale effect. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last 2 decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slowdown in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century.

Future socio-economic and climate changes can profoundly impact water resources, food production, bioenergy generation, and land use, leading to a broad range of societal problems. In this study, we performed future projections by using a land integrated model, MIROC-INTEG-LAND, that considers land surface physics, ecosystems, water management, crop growth, and land use, under various socio-economic scenarios (Shared Socio-economic Pathways, SSPs). Under the sustainability scenario (SSP1), demands for food and bioenergy are kept low, so that the increase in cropland areas for food and bioenergy are suppressed. On the contrary, in the middle of the road and regional rivalry scenarios (SSP2 and SSP3), cropland areas are projected to increase due to high demand for food and bioenergy. The expansion of cropland areas is projected to increase the water demand for irrigation and CO2 emissions due to land use change. MIROC-INTEG-LAND simulations indicate that the impacts of the CO2 fertilization effect and climate change on crop yields are comparable, with the latter being greater than the former under climate scenarios with high greenhouse gas concentrations. We also show that the CO2 fertilization effects and climate change play important roles in changes in food cropland area, water demand for irrigation, and CO2 emissions due to land use change. Our results underscore the importance of considering Earth-human system interactions when developing future socio-economic scenarios and studying climate change impacts.