Abstract: The Loess Plateau is one of the regions characterized by the most serious soil erosion and land degradation in China, and also a critical area for the Grain for Green Program (GGP). This study aimed to assess the implementation effect of the GGP in the Loess Plateau and to inform ecological environment restoration for sustainable development. Ansai County of Shaanxi Province, a central area implementing the GGP in the Loess Plateau, was selected as the study area. InVEST model was used to assess the impacts of the GGP on the changes in ecosystem services (soil conservation, flood regulation, carbon storage, water yield). The tradeoffs and synergies among ecosystem services were analyzed, while ecosystem services under different implementation scenarios for the GPP were simulated. The results showed that GPP significantly changed land cover pattern of Ansai County from 2000 to 2015. The GPPrelated change in land use (conversion of farmland to woodland, shrub land, grassland, etc.) was 464.93 km2 (accounting for 15.8% of the total area), of which the conversion of farmland to grassland accounted for the largest proportion (71.8%). After the implementation of GGP, flood regulation function increased by 33.4%, carbon storage increased by 39.6%, soil conservation increased by 5.3%, and water yield decreased by 22.4%. Results of scenario analysis showed that, under the conditions that the area and proportion of farmland returned to forest and grassland remain unchanged, the priority of returning farmland to forest (grassland) in steep slope and riparian farmland would significantly enhance soil conservation, while other ecosystem services remain unchanged or decline slightly. The GPP would weaken the trade-off effect among ecosystem services when riparian (100 m distance from a river) and steep-sloped farmlands are primarily converted. This study provides a reasonable implementation scheme for program planning and improves the effect of ecological governance.

Key words: Grain for Green Program, ecosystem services, priority area, scenario simulation, InVEST model.