Ecological Indicators (Mar 2022)
Spatial patterns of associations among ecosystem services across different spatial scales in metropolitan areas: A case study of Shanghai, China
Abstract
Understanding the spatial patterns of ecosystem service (ESs) supply and their multiscale associations are prerequisites for optimizing blue-green space planning and sustainable management in metropolitan areas. This study selected Shanghai as a typical metropolitan area in the plain river network region, and five key ESs were mapped. Based on ESs supply efficiency, an ESs cumulative curve method was proposed to identify ESs hot spots. The bivariate local Moran’s I was used to compare the trade-offs and synergies among ESs and their spatial distributions across the four grid scales and two administrative division scales. The results showed a strong spatial heterogeneity of ESs supply and a scale dependency of the associations among them. The high-value areas of the ESs supply were mainly distributed in the west, north, and south. The hot spots of each ecosystem service accumulated more than 55% of each service, but only occupied areas less than 30% of the whole area. The synergies of four of ten pairs of ESs remained consistent across all scales. At the grid scales, they were all synergistic. The synergies of nine pairs of ESs decreased as the scale increased, and the other pair showed the opposite trend. At the administrative division scales, almost all pairs exhibited the strongest synergies at the district scale, and six pairs were trade-offs at the subdistrict scale. The scale effects indicated that the district scale was appropriate for decision-making in metropolitan areas, but the subdistrict-scale results should not be directly used as a reference. Finally, hierarchical planning and conservation policies and differentiated management policies at different administrative division scales were proposed. This study contributes to creating win–win options and improving human well-being. The analytical framework can be applied to across regions and to assess the ESs supply under various planning scenarios.
