Recent publications
Plain Language Summary In recent decades, China has implemented large‐scale afforestation projects, significantly contributing to global greening. However, the greening trend in China has been underestimated by Dynamic Global Vegetation Models (DGVMs). The underestimation may be from the uncertainties in plant functional types data, but solid evidence is lacking. Here, we developed a high‐resolution data set to better represent China's forest cover changes. We used this data set to figure out why DGVMs underestimate vegetation growth in China. We found that the land use data used by DGVMs leads to underestimated afforestation. By excluding other influencing factors, we further determined that underestimated afforestation is the main reason for underestimated greening trend. On average, the models underestimated China's afforestation by ∼27%, which led to a ∼30% underestimation of vegetation growth. Our results explicitly confirm that China's forests have experienced much more pronounced growth than the model's simulation, highlighting the need for better land use data in future modeling efforts.
