Abstract: Under the dual pressures of global climate change and rapid urbanization, clarifying the evolution of urban ecosystem service patterns and their trade-off and synergy relationships under multiple scenarios is important for constructing functional zoning and spatial governance frameworks. We used land use data, meteorological data, and soil data of 2020 to simulate four ecosystem services in Shanghai, namely habitat quality, carbon storage, soil conservation, and water conservation, under three shared socioeconomic pathway scenarios (SSP126, representing a low-emission and ecological protection pathway; SSP245, representing a medium-emission and moderate development pathway; and SSP585, representing a high-emission and high-economic-growth pathway) in 2050 using the intPLUS model. Then, we analyzed the evolutionary characteristics, and identified pixel-scale trade-off and synergy relationship and conducted self-organizing map-based service cluster classification. The results showed that Shanghai's ecosystem services in 2020 showed a spatial pattern characterized by higher values in peripheral areas and lower values in the urban center. High-value areas were mainly concentrated in Chongming, western agricultural areas, and peripheral ecological spaces, whereas the central built-up area generally showed lower values. By 2050, ecosystem services under the three scenarios generally continued the spatial pattern of high at the periphery and low in the center. Compared with 2020, the spatial patterns of habitat quality and carbon storage remained generally stable, whereas soil conservation and water conservation were more sensitive to scenario changes. Soil conservation showed increases under SSP126, SSP245, and SSP585, with proportions of 56.7%, 58.8%, and 61.6%, respectively. Water conservation mainly showed decrease under SSP126, with a proportion of 83.1%, but showed increases under SSP245 and SSP585, with proportions of 72.8% and 73.9%, respectively. The trade-off/synergy analysis showed that habitat quality and carbon storage maintained a stable synergistic relationship, while habitat quality generally exhibited trade-off relationships with water conservation and soil conservation. The relationship between water conservation and soil conservation shifted from trade-off dominance under SSP126 to synergy dominance under SSP245 and SSP585. The ecosystem service cluster analysis classified the study area into four functional zones: carbon sink regulation zone, ecological conservation zone, water yield advantage zone, and soil conservation zone, providing a spatial framework for zoning management under future uncertainty. The results would help deepen the understanding of multifunctional coupling and scenario-response mechanisms of ecosystem services in megacities, and provide a scientific basis for ecological spatial optimization and differentiated governance in Shanghai and other high-density cities.

Key words: ecosystem service cluster, ecological functional zoning, multi-scenario simulation, self-organizing map, trade-off and synergy