Future greening of the Earth may not be as large as previously predicted

Abstract

Changes in global vegetation growth and its drivers during recent decades have been well studied with satellite data, ecosystem models and field experiments. However, a systematic understanding of how global vegetation will respond to projected changes in climate and atmospheric composition is still lacking. Here, we analyze changes in projected global leaf area index (LAI) from 16 Coupled Model Intercomparison Project phase 5 (CMIP5) and 17 phase 6 (CMIP6) Earth System Models (ESMs) during the 21st century under future scenarios RCP2.6, RCP4.5 and RCP8.5 and future scenarios SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5, respectively. In addition to the widely-used multi-model ensemble mean (MME) method, we employed the Reliability Ensemble Averaging (REA) strategy to integrate the modeled results. The REA integration weights were determined by combining the performance of the ESMs in simulating present-day LAI changes, which was based on a comparison with three long-term remote sensing LAI data sets, with their convergence of future predictions. The results suggest that global LAI will increase under all seven future scenarios with both integration methods. The magnitude of LAI growth is expected to increase with the forcing levels of the scenarios. The ESMs integrated with the REA weights predicted significantly smaller magnitudes and lower uncertainties in global LAI growth by the end of the 21st century than those integrated with the MME method. Both REA and MME results suggest that the growth in atmospheric CO2 concentration is the main positive driver of the projected increment of global LAI, which is partly offset by the negative effects of global warming. Our improved comprehensive prediction based on CMIP5 and CMIP6 ESMs using the REA integration strategy provides a more robust estimation of global vegetation change during the 21st century, and is expected to help better understand the state of the planet in the coming decades.