Policy-driven China's Grain to Green Program: Implications for ecosystem services

•The development status of the policy-driven China's Grain to Green Program (GTGP).•Constructed evaluation index system of GTGP, the ecosystem services were analyzed.•The GTGP have produced some negative consequences and demonstrated positive impacts.•Main driving factors on ecosystem services of GTGP were socio-economic factors.

The policy-driven China's Grain to Green Program (GTGP) is one of the biggest programs in the world because of its massive scales, largest investment and enormous effects. One research concern surrounding the GTGP is how to evaluate its ecological implications for ecosystem services. Taking Yangtze and Yellow river basins as the study area, we provide an overview of the development status and demand for the GTGP, construct the evaluation index system and distributed measurement methods of ecosystem services, and analyze the implications for ecosystem services of the GTGP as rigorously as possible from various sources of combined data. Although there are time lags in ecological implications, but the GTGP also have global implications because it increase vegetative cover and water conservation, enhance soil fertility and carbon sequestration, and atmosphere environmental purification by controlling soil erosion. The future implications for ecosystem services of the GTGP may be even bigger. The main driving factors on the implications changes were the policy and socioeconomic factors, such as the policy governance, the adjustment of economic structure and increased income of peasant households. By contrast, natural environment factors, such as precipitation, terrain slope, and etc., were in a secondary role. The existing problems and challenges for the GTGP were analyzed, and put forward some recommendations to overcome their shortcomings and enhance their potential. The GTGP can provide important experiences for the implementation of similar ecosystem service programs in China and many other parts of the world.