Spatial patterns in ecosystem services supply and demand in the Jing-Jin-Ji region, China

Spatial patterns in ecosystem services (ES) supply and demand can provide useful visual information for eco-economic management policy. For assessing ES supply and demand on a regional scale, we coupled natural elements with socioeconomic factors and built an integration model involving five types of ES supply, i.e., water conservation, soil conservation, carbon fixation/oxygen release, sand fixation, and air purification, and three types of ES demand, i.e., water resource demand, carbon emission/oxygen consumption, and air pollution control demand. For the case of the Beijing-Tianjin-Hebei region, the patterns of ES supply and demand were analyzed by assessing the multi-year average of 2001, 2005, 2010, and 2017. The main results were: (1) An apparent spatial mismatch between ES supply and demand in the study area. Areas with high ES supply capacity were located in the Yanshan Mountains and the Taihang Mountains, and the eastern Bashang Plateau. Areas with high ES demand were mainly located in large and medium-sized cities in the Hebei Plain. (2) The total ES supply capacity could not meet the needs of the study area. The surplus area accounted for 32.93% of the total area and the deficit area for 67.07%. The total ES demand was 2.05 times the total ES supply in the study area. Chengde was the only region with an ES surplus per unit area, and Tianjin had the largest deficit. The ES deficit in the Jing-Jin-Ji region was severe. (3) Based on the surplus-deficit patterns of ES supply-demand, three environmental management zones were suggested, i.e., environmental conservation, restoration, and control zones, and some concrete suggestions and solutions on environmental protection or restoration were elaborated for each zone to mitigate conflicts of ES supply and demand. Key findings will provide a scientific basis for constructing regional ecological compensation mechanisms and the coordinated development of the Jing-Jin-Ji region.