Synergies and Trade-Offs among Different Ecosystem Services through the Analyses of Spatio-Temporal Changes in Beijing, China

Abstract

Increasing global urbanization has not only resulted in economic development but it has also caused a number of ecological issues, such as haze, global warming, and storm surges, which can end up hindering the development of human society in the long term. One method of maintaining the long-term growth of human ecosystems is by considering ecosystem services (ES) when making decisions over land use. This study provides information to aid with decision making in the maintenance of Beijing’s ES provision in the long term. Firstly, three key ES, namely, carbon storage (CS), habitat quality (HQ), and water yield (WY), were evaluated by the InVEST model. Then, the spatial patterns of synergies and trade-offs among three ES at the city and grid scales were explored through the correlation coefficients analysis and geographically weighted regression (GWR). Finally, the strength of trade-offs among ES was calculated based on root mean squared error (RMSE), and the potential ecological risk areas are recognized. We discovered that (1) the total carbon storage decreases from 3.74 million tons in 2000 to 3.66 million tons in 2020, and HQ has the same trend, with its average value decreasing from 0.72 to 0.67; in contrast, water yield is more stable, increasing slightly from 8.22 × 1010 m3 in 2000 to 8.23 × 1010 m3 in 2020. (2) The synergies and trade-offs of ES are spatially heterogeneous. Among them, the correlation coefficients at the city-level indicated synergistic relationships among the three ES, but CS-WY and WY-HQ always have trade-off relationships at the grid level, where 37.88% of WY-HQ and 14.59% of CS-WY were trade-offs in 2020. (3) At the urban-rural interface, the trade-offs among ES are stronger than those in other regions. In rural-urban areas, the RMSE in CS-HQ, CS-WY and WY-HQ always had high values (>0.5), accounting for 16.72%, 9.33%, and 26.94% of the entire area, respectively; these areas are identified as potential ecological risk areas, which will be the focus area for future ES regulation. These findings provide opportunities for clear trade-offs among ES and promote positive synergies. In addition, land-use management may use the results to guide ecosystem service use, identify critical areas, and ensure regional sustainability in urban development.