Urban environments provide new perspectives for forecasting vegetation phenology responses under climate warming

Given that already-observed temperature increase within cities far exceeds the projected global temperature rise by the end of the century, urban environments often offer a unique opportunity for studying ecosystem response to future warming. However, the validity of thermal gradients in space serving as a substitute for those in time is rarely tested. Here, we investigated vegetation phenology dynamics in China's 343 cities and empirically test whether phenological responses to spatial temperature rise in urban settings can substitute for those to temporal temperature rise in their natural counterparts based on satellite-derived vegetation phenology and land surface temperature from 2003 to 2018. We found prevalent advancing spring phenology with "high confidence" and delaying autumn phenology with "medium confidence" under the context of widespread urban warming. Furthermore, we showed that space cannot substitute for time in predicting phenological shifts under climate warming at the national scale and for most cities. The thresholds of similar to 11 degrees C mean annual temperature and similar to 600 mm annual precipitation differentiated the magnitude of phenological sensitivity to temperature across space and through time. Below those thresholds, there existed stronger advanced spring phenology and delayed autumn phenology across the spatial urbanization gradients than through time, and vice versa. Despite the complex and diverse relationships between phenological sensitivities across space and through time, we found that the directions of the temperature changes across spatial gradients were converged (i.e., mostly increased), but divergent through temporal gradients (i.e., increased or decreased without a predominant direction). Similarly, vegetation phenology changes more uniformly over space than through time. These results suggested that the urban environments provide a real-world condition to understand vegetation phenology response under future warming.