The temporal effect of urban landscape pattern on the spatiotemporal heterogeneity of water-related ecosystem services: evidence from Suzhou, China (2004–2022)

Changes in urban landscape patterns significantly influence the functioning of water-related ecosystem services (WESs). However, existing research often focuses on the spatial correlation mechanisms between landscape patterns and WES, resulting in a limited understanding of their dynamic mechanisms across the temporal dimension. This study systematically analyzed landscape pattern changes in Suzhou, China, from 2004 to 2022, quantifying multiple water-related ecosystem services, including water yield, habitat quality, soil conservation, nitrogen and phosphorus export. The Geographically and Temporally Weighted Regression (GTWR) model was employed to investigate the temporal effects of landscape pattern changes on WESs throughout the study period. Our findings revealed that: (1) WESs exhibited distinct temporal variation patterns, with habitat quality showing linear decline, nitrogen and phosphorus exports following V-shaped trajectories, and water yield and soil retention displaying M-shaped fluctuations. All landscape pattern changes slowed in magnitude after 2013. (2) Among multiple landscape indicators with significant effects ( p < 0.05), landscape connectivity emerged as the key driver for various WESs. (3) The impact intensity of landscape aggregation and fragmentation on all WESs declined sharply after 2019. Notably, the abrupt decrease in fragmentation's influence led to a shift in the dominant factor for nitrogen and phosphorus exports—from fragmentation to diversity—post-2019. (4) Landscape patterns simultaneously enhance one service while suppressing another; however, this relationship is not static and may evolve into synergistic promotion of multiple services over time. This study analyzes the temporal dynamics of landscape patterns' influence on WESs, highlighting the importance of incorporating temporal dimensions into ecosystem services research. • Landscape connectivity is a key driver of WESs change. • Instability—A brupt drop in intensity and a shift in dominant driving factors. • The positive and negative effects of individual indicators on WESs reverse over time. • The temporal effect is essential for understanding landscape-WES relationships.