Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts

Abstract

China has made extensive afforestation efforts over the past 40 years. However, ecosystem models simulate only modest vegetation enhancement, creating a significant disparity between documented reforestation efforts and model-based simulations. This fundamental mismatch remains largely unexplored. Here, we conducted a comprehensive analysis using diverse observation data to identify the determinant within Dynamic Global Vegetation Models (DGVMs) that underestimates vegetation growth in China. By developing a high-resolution forest cover change data set, we found that LUH2-GCB, the common land use input for DGVMs, causes models to underestimate afforestation. With a neighborhood comparison analysis, we quantitively demonstrated the predominant role of underestimated afforestation in lowering leaf area index (LAI) trends. Overall, DGVMs underestimated China's afforestation area by an average of 26.88%, leading to a 29.46% underestimation in LAI increase. Our findings confirm a significant greening trend in China and highlight the need for improved land use data representation in DGVMs.