Understanding Spatial-Temporal Interactions of Ecosystem Services and Their Drivers in a Multi-Scale Perspective of Miluo Using Multi-Source Remote Sensing Data

Abstract

In the face of rapid urbanization and global climate change, understanding the trade-offs and synergies of wetland city ecosystem services is vital for mitigating regional ecological and environmental risks, and enhancing human well-being. The Dongting Lake Basin is an ecologically fragile area of global significance. Uncontrolled resource utilization and intensive human activities have severely damaged the ecological environment, including in Miluo. Thus, it is of paramount research importance to uncover the trade-offs and synergies of ecosystem services and their driving mechanisms in Miluo. To achieve this, we classified Miluo’s land use data over the past two decades using a random forest model and Landsat imagery. We quantified the major ecosystem services in Miluo by employing ecological process models such as InVEST, RUSLE, and CASA. Additionally, we examined the trade-offs and synergies between ecosystem services at different scales and identified the driving mechanisms using multi-source remote sensing data. The results revealed that forests exhibited the highest level of ecosystem services, while urban ecosystem services experienced a significant decline. Over the past two decades, Miluo displayed notable trade-offs and synergies between ecosystem services, with synergies prevailing as the dominant pattern, particularly at the county scale. Furthermore, human activities emerged as the primary driver of changes in Miluo’s ecosystem services during the 20-year period. Therefore, it is imperative for scientists, policymakers, and civil society to develop effective and scientifically sound strategies to mitigate the ecological risks resulting from rapid urbanization and climate change in the future.