Spatio-temporal interaction and constraint effects between ecosystem services and human activity intensity in Shaanxi Province,China

Abstract

Identifying spatial heterogeneity in ecosystem services and understanding the spatial and temporal correlations between ecosystem service exploration and human activity intensity are vital for achieving regional harmony between human activities and the environment, ultimately fostering sustainable development. Previous studies primarily concentrated on the impact of human activities on ecosystem services while overlooking the intricate spatiotemporal dynamics and nonlinear relationships. In this study, which leveraged multi-source data, we found increasing trends in Human Footprint Index (HFI), most pronounced in the central region of Shaanxi Province. From 2000 to 2020, Shaanxi Province consistently exhibited an ecosystem service distribution pattern characterized by a 'high in the central-south and low in the northwest' trend. Habitat Quality (HQ) consistently maintained high values, signifying favorable habitat conditions, while Food Production (FP) remained relatively stable. Carbon Sequestration (CS) and Soil Conservation (SC) displayed diverse temporal patterns, whereas Water Yield (WY) showed noticeable fluctuations.This analysis revealed a negative correlation between HFI indicators and Total Ecosystem Services (TES). Constraint lines delineated hump-shaped relationships between TES and human activity intensity across various geomorphic areas. Notably, the differences between regions were significant, and threshold dynamics were identified. HFI negatively correlated with TES, moderate HFI growth improved services, yet exceeding ecological thresholds caused decline. Overall,this study informs necessary ecosystem management in Shaanxi, highlighting the need for balanced policies and predictive models that ensure sustainable development without crossing critical ecological thresholds. Future work should concentrate on developing predictive models that incorporate environmental, technological, and socio-economic variables, to better anticipate and mitigate the ecological impacts of human activities.