Spatio-Temporal Evolution and Driving Mechanisms of Ecological Resilience: The Guanzhong Plain Urban Agglomeration Case

With the advancement of urbanization, the intensification of urban population agglomeration has been associated with a gradual decline in the quality of urban ecological systems in many cases. Urban ecological resilience offers a promising framework for cities to address internal pressures accumulated over long-term development as well as external uncertainties and risks, thereby playing a crucial role in sustainable urban development. This study constructs a spatial evaluation model of urban ecological resilience based on three dimensions—resistance, adaptability, and recovery—and identifies key regional driving factors through ridge regression analysis. The findings reveal the following: (1) From 2000 to 2023, urban ecological resilience in the central and western parts of the Guanzhong Plain urban agglomeration exhibited a year-by-year decline, whereas regions in the north, south, and east demonstrated a consistent upward trend. (2) Empirical analysis based on an extended STIRPAT model indicates that carbon emissions per unit of energy, energy intensity, population density, and per capita GDP exert significantly negative effects on urban ecological resilience, while the proportion of secondary industry, human capital level, education expenditure, and government investment have significantly positive impacts. (3) Phased regression results show that the proportion of secondary industry and per capita GDP were not significant in the early stage but became significant drivers in the later stage. Conversely, the positive effects of government investment and education expenditure weakened over time. Based on the study results, this paper proposes policy recommendations: the government can enhance urban ecological resilience via low-carbon pathways including energy conservation and emission reduction, clean energy application, population density regulation, human capital investment, increased education spending, and industrial ecological transformation. Regarding the spatial differentiation and driving mechanism of ecological resilience in the Guanzhong Plain Urban Agglomeration, this study proposes three strategies: differentiated spatial governance, green energy transition, and green industrial upgrading with talent cultivation to enhance regional ecological resilience. • The adaptive resistance and recovery model is established to evaluate the ecological resilience level of urban agglomerations. • Energy intensity has the strongest negative impact while human capital has the strongest positive impact. • Government investment and education expenditure exert a greater impact in the early stage. • The proportion of secondary industry and per capita GDP exert a greater impact in the later stage.