Investigating the heterogeneity of ecosystem services (ESs) and their interactions plays a crucial role in refining spatial management. However, little is known about the spatiotemporal heterogeneity of ES interactions. This study quantified the spatiotemporal variations in ES interactions in Northeast China. It categorized different ES bundles through self-organizing maps and ranked the importance of drivers by SHapley Additive exPlanations (SHAP), thereby proposing targeted spatial management strategies. The results indicated that between 2000 and 2020, most ES pairs exhibited synergies, whereas a few ES pairs exhibited trade-offs. And the synergistic areas for habitat quality (HQ)–net primary productivity (NPP), HQ–soil retention (SR), and NPP-SR accounted for 67.79%, 65.29%, and 75.69% of the study region, respectively. Between 2000 and 2020, the area covered by the key synergetic bundle and habitat quality bundle first increased and then decreased. SHAP analysis indicated that NPP, SR, and water retention were most influenced by biophysical indicators, while HQ was primarily influenced by anthropogenic indicators. Based on research findings regarding ES bundles and their drivers, refined strategies for ecosystem management have been proposed. This study integrated knowledge of ES interactions into spatial management, providing a basis for maximizing ES benefits and addressing future climate change.

Rapid urbanization has significantly impacted plant growth rhythms through increased surface temperatures and enhanced artificial light at night (ALAN). However, the effects of thermal environments and ALAN on urban vegetation phenology (UVP) remain unclear, limiting our knowledge of how plant growth responds to urbanization and climate change. This study employed high-resolution multi-source data to assess the changing characteristics of the start of the growing season (SOS) and the end of the growing season (EOS) along the urban–rural gradient in Shenyang City. The structural equation model (SEM) and the accumulated local effect model were employed to determine the combined effects and thresholds of thermal environments and ALAN on UVP. We found that the nighttime light duration is associated with delayed autumn vegetation phenology in urban areas. In addition to land surface temperature (standardized path effect, β = 0.41, p < 0.05), the nighttime light duration (β = 0.27, p < 0.05) and intensity (β = 0.05) were key factors influencing EOS. The impact of nighttime light duration on phenology exhibited distinct seasonal variations, with a significantly greater impact on EOS (β = 0.27, p < 0.05) than on SOS (β = 0.14, p < 0.05). This might be related to vegetation’s carbon assimilation capacity and its reaction to climate change. These drivers exhibited complex nonlinear relationships with UVP, and the same driver also displayed distinct variation patterns with SOS and EOS. Our findings indicate that nighttime light duration is an important associated factor of plant growth, with great significance for predicting vegetation dynamics under rapid urbanization.