Quantifying the Rate and Extent of Urbanization Effects on Vegetation Phenology in Mainland China

Urbanization profoundly alters environmental conditions (e.g., temperature, artificial light at night (ALAN), and precipitation) that strongly influence vegetation phenology. However, the rate and extent of vegetation phenological responses to urbanization, as well as their underlying mechanisms, remain underexplored, particularly the roles of CO2 emissions and PM2.5 concentrations, as well as the interactions among environmental conditions. We first used road network density (RND) to represent urbanization effects and quantified the phenological response rate and extent across 31 cities in China (2014–2022) using slope and range metrics derived from linear regressions of phenostages (start of season (SOS), end of season (EOS), length of season (LOS)) against RND. Partial least squares structural equation modeling was applied to assess the direct and indirect effects of RND on phenology via all five key environmental factors. Our results identified substantial differences in the urban phenological responses across latitudinal, hydrothermal, and land−cover gradients. And the impact of urbanization on phenology was most pronounced during early expansion (at a RND threshold of 2.02 ± 0.41 km/km2) but diminished with continued growth. Environmental factors distinctly affected phenological response rate and extent through RND; temperature, ALAN, and CO2 emissions were the dominant drivers of slope, negatively affecting SOS (β = −0.37 to −0.69) but positively affecting EOS and LOS (β = 0.31 to 0.68). PM2.5 played a crucial role in determining the range of SOS (β = −0.31), and precipitation had the largest impact on the range of EOS (β = −0.37). Our study innovatively uses RND to quantify urbanization intensity and improve understanding of the combined effects of multiple drivers, especially PM2.5 and CO2, on phenological responses, which may offer a useful reference for future urban planning strategies that aim to balance development with ecosystem functioning.