Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology

Abstract

Adequately understanding the spatial multi-scale relationships of ecosystem services (ES) is an important step for environmental management decision-making. Here, we used spatially explicit methods to estimate five critical ES (nitrogen and phosphorous purifications, crop production, water supply and soil retention) related to non-point source (NPS) pollution in the Taihu Basin region of eastern China. Then a factorial kriging analysis and stepwise multiple regression were performed to identify the spatial multi-scale relationships of ES and their dominant factors at each scale. The spatial variations in ES were characterized at the 12 km and 83 km scales and the result indicated that the relationships of these services were scale dependent. It was inferred that at the 12 km scale, ES were controlled by anthropogenic activities and their relationships were dependent on socio-economic factors. At the 83 km scale, we suggested that ES were primarily dominated by the physical environment. Moreover, the policy implications of ES relationships and their dominant factors were discussed for the multi-level governance of NPS pollution. Overall, this study presents an optimized approach to identifying ES relationships at multiple spatial scales and illustrates how appropriate information can help guide water management.

Figure 1

Spatial distribution of five ecosystem services in Taihu Basin, Jiangsu in 2010. Green indicates high value areas of ecosystem services, red and yellow indicate areas with low and moderate values, respectively, and blue represents water. Maps generated with ArcGIS 10.2.2 (http://www.esri.com/software/arcgis).

Figure 2

Spatial components of five ecosystem services at the local scale (12 km) in Taihu Basin, Jiangsu in 2010. 1 in the legend indicates high value areas of spatial component variability, −1 in the legend indicates areas with low value variability, and blue represents water. Maps were generated with ArcGIS 10.2.2 (http://www.esri.com/software/arcgis).

Figure 3

Spatial components of five ecosystem services at the regional scale (83 km) in Taihu Basin, Jiangsu in 2010. 1 in the legend indicates high value areas of spatial component variability, −1 in the legend indicates areas with low value variability, and blue represents water. Maps were generated with ArcGIS 10.2.2 (http://www.esri.com/software/arcgis).

Figure 4

Correlation circles of principle component analysis for classical, local and regional scales.