关键词: 生态系统服务, 人类活动强度, 广义加性模型, 赣南地区

Abstract: With the acceleration of urbanization and industrialization, the impact of human activities on ecosystem services has been increased. Scientifically assessing such impact has become a hot issue in ecological studies. Understanding the influence of human activities on ecosystem services is crucial for ecological management and sustainable development. By applying InVEST model, bivariate spatial autocorrelation, and generalized additive model, we explored the spatiotemporal pattern and spatial aggregation characteristics between human activities and key ecosystem services, such as water yield, soil conservation, carbon sequestration, and habitat quality in south of Jiangxi Province from 2000 to 2020, and analyzed the spatiotemporal relationships between human activities and ecosystem services. The results showed that from 2000 to 2020, the intensity of human activities in south of Jiangxi Province was generally low but showed an increasing trend, with high-intensity activity areas concentrating in the central urban districts of counties and cities. Water yield and soil conservation services initially increased then declined, while carbon sequestration and habitat quality generally decreased, with higher values in the south and lower values in the north. There was significant spatial heterogeneity of human activities and ecosystem services at the township scale. The intensity of human activities showed a significant positive correlation with water yield, while it was significantly negatively correlated with soil conservation, carbon sequestration, and habitat quality. There was a nonlinear spatiotemporal relationship between human activities and ecosystem services, especially for water yield which was particularly complex. Our findings would provide valuable insights for the scientific management and sustainable development of natural resources in south of Jiangxi Province.

Key words: ecosystem service, intensity of human activity, generalized additive model, south of Jiangxi Province