Spatiotemporal pattern and multi-scenario simulation of ecological risk in mountainous cities: a case study in Chongqing, China

Environ Monit Assess. 2023 May 30;195(6):760. doi: 10.1007/s10661-023-11398-0.

Abstract

Scientific descriptions and simulations of the ecological risks in mountainous areas can promote the sustainable use of land resources in these areas and improve the reliability of decision-making for ecological risk management. Taking Chongqing, China, as an example, we constructed a landscape ecological risk (LER) evaluation model based on land use data from 1995 to 2020 and analysed the spatiotemporal evolution characteristics of the LER pattern. Moreover, we coupled the patch-generating land use simulation (PLUS) model and multi-objective programming (MOP) method and input multiple scenarios (inertial development, ID; economic priority development, ED; ecological priority development, PD; and sustainable development, SD) to simulate the ecological risk pattern in 2030. The model coupling the "top-down" and "bottom-up" processes obtained optimal land use patterns in different contexts, and it was used to perform a spatially explicit examination of LER evolutionary trends in different contexts. The results showed that LER evolution in Chongqing has had obvious stage characteristics. The high-risk area decreased significantly under various constraints, including topographic, economic, and other constraints, and the distribution showed a trend of high in the west and low in the east. The LER spatial clustering characteristics were highly coupled with the risk level pattern. The ED scenario presented the most severe risk, the PD scenario presented a moderate risk, and the SD scenario balanced the land demand for economic and ecological development and had a better land use structure and LER compared with the other scenarios. The coupled model proposed in this study helps to obtain the optimal land use structure and mitigate ecological risks, thus providing a scientific basis for future urban development.

Keywords: Ecological risk; Multi-objective programming; Multi-scenario simulation; Spatial autocorrelation.

MeSH terms

  • China
  • Cities
  • Conservation of Natural Resources*
  • Ecosystem*
  • Environmental Monitoring
  • Reproducibility of Results