Spatial and temporal driving mechanisms of ecosystem service trade-off/synergy in national key urban agglomerations: A case study of the Yangtze River Delta urban agglomeration in China

[Display omitted] •Assessment of supporting, regulating, provisioning, and cultural services.•The trade-off/synergy of ES changes' processes was evaluated.•The YRDUA can be divided into 4 ES trade-off and synergy bundles.•Climate drivers (TH, PRE, SRT) had the most constant effect on ES distribution.•Socio-economic and land use drivers dominated the dynamics of ES trade-off/synergy. Clarifying the ecosystem service (ES) trade-off/synergy is a prerequisite for scientific implementation and optimization of integrated ecological system management strategies, especially in highly urbanized areas with declining eco-environmental carrying capacity. This study took China's Yangtze River Delta urban agglomeration (YRDUA) as an example. First, we used a pixel-by-pixel analysis based on dynamic spatial correlation to quantify the trade-off/synergy among the 6 primary ESs' change amounts from 2005 to 2020 (habitat quality, soil retention, carbon sequestration, water yield, food production, leisure and recreation). Then, we integrated the multiple ES trade-off/synergy and explored their driving factors by spatial cluster analysis and geographically and temporally weighted regression (GTWR). The results showed synergy between supporting and regulating services predominated while regulating services were mostly trade-offs with regulating and cultural services. The trade-off/synergy of the 15 ES functional pairs within YRDUA can be downscaled into 4 ES trade-off and synergy bundles. Furthermore, the climate drivers (annual highest temperature (TH), annual total precipitation (PRE), annual total solar radiation (SRT)) significantly influenced the spatial heterogeneity of the 6 ESs in the YRDUA. The socio-economic drivers (night light index (NLI), gross domestic product (GDP)) and land use drivers (proportion of arable land (ALP), proportion of construction land (CLP), proportion of woodland (WLP)) had a more remarkable power of explanation for the ES temporal variation and ES trade-off/synergy. YRDUA and other urban agglomerations can use the study's findings to develop differentiated integrated ecological management strategies.