Work

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

Year: 2025

Type: article

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.

Source: Geophysical Research Letters

DOI: 10.1029/2024gl113403