Detection and attribution of vegetation greening trend across distinct local landscapes under China's Grain to Green Program: A case study in Shaanxi Province

As one of the largest payment for ecosystem service programs in the world, China's Grain to Green Program has been proved to generate an unambiguous greening trend across the country. A critical knowledge gap still exists in the understanding of the spatial disparity of vegetation dynamics and the relative contributions of the program versus other anthropogenic and natural drivers, especially at local scale. This study took Shaanxi Province as a case study, used a panel dataset of MODIS NDVI, multi-station surface meteorological observations, and socio-economic statistics for detecting the disparity among three distinct landscapes. Meanwhile a fixed-effects model was applied for attribution. Spatial disparity in vegetation change was evident among the three distinct landscapes. Although the afforestation efforts generally produced positive and lagged effects on vegetation recovery, local conditions dominated the disparity. Growing population pressures, intensified industrial activities, and perverse strategic behaviors of affected farmers effectively deterred the success of the program. To consolidate the implementation achievements of the program, more locally adapted measures such as human resettlement, technical assistance, and creating more employment opportunities should be encouraged. Furthermore, supervision and evaluation should be strengthened.