Assessment of Uncertainties in Ecological Risk Based on the Prediction of Land Use Change and Ecosystem Service Evolution

Abstract

With the rapid progress in urbanization and economic development, the impact of land use change (LUC) on ecosystem services is becoming increasingly significant. However, the accuracy of ecological risk assessment faces challenges due to the presence of uncertainty factors. Using the PLUS model, this study aims to simulate and predict land use changes (LUCs), focusing on the southern hilly regions in southeastern China as a case study, conducting an in-depth assessment of ecological risk uncertainty. Firstly, a spatiotemporal simulation of LUCs in the southern hilly region from 1990 to 2030 was conducted under multiple scenarios. Subsequently, differences in the spatial and temporal distribution of ecosystem service value (ESV) across different years and forecast scenarios in the southern hilly region were revealed, followed by a detailed analysis of the impact of LUCs on ESV. Finally, by calculating the Ecological Risk Index (ERI), the study systematically analyzed the evolution trend of ecological risk in the southern hilly region of China from 1990 to 2030. The main research findings are as follows: (1) the conversion proportions of different land use types vary significantly under different scenarios. Compared to 2020, under the 2030 National Development Scenarios (NDSs), there has been a slight decrease of around 3% in the total conversion area of farmland, forest, and grassland. However, under the Ecological Protection Scenario (EPS) and Urban Development Scenario (UDS) scenarios, there has been an increase in the area of forest and grassland, with a rise of approximately 1.5% in converted built-up land. (2) Western cities (e.g., Yueyang and Yiyang), central cities (e.g., Jiujiang), and northeastern cities (e.g., Suzhou) of China exhibit a relatively high ESV distribution, while ESV significantly decreased overall from 2010 to 2020. However, under the EPS and UDS, ESV shows a significant increasing trend, suggesting that these two scenarios may play a crucial role in ecosystem restoration. (3) The conversion of forest and water bodies to farmland has the most significant inhibitory effect on ESV, especially during the period from 1990 to 2000, providing substantial data support for relevant policy formulation. (4) From 1990 to 2030, ecological risk gradually increased in western, central, and southwestern cities of the southern hilly region, with the highest ecological risk values under the EPS scenario in northern cities (e.g., Chizhou and Tongling). Under the UDS scenario, there has been a significant decrease in ecological risk, providing valuable insights for future ecological conservation and sustainable development. However, a limitation lies in the need for further enhancement of the scenario’s simulation authenticity. This study offers a new perspective for understanding the impact of LUCs on ecosystem services and the uncertainty of ecological risks, providing crucial reference points for land resource management and the formulation of ecological conservation policies.