Knowledge of nitrogen (N) and phosphorus (P) stoichiometry is essential for understanding biogeochemical cycle and ecosystem functioning. However, largeâscale patterns in soil stoichiometry are not yet fully understood along environmental gradients nor over the temporal scale. Using a comprehensive data set and artificial neural network approach, we evaluated spatial and temporal patterns in topsoil N and P concentrations and N:P ratio across China's forests. Our results revealed that soil weathering stage, climatic factors (i.e., temperature and precipitation), and forest types jointly explained approximately 34.1% and 30.4% of spatial variations in soil N and P, respectively. By contrast, only precipitation could explain the variation in N:P ratio, with soil N:P ratio exhibiting a trend of increase along the precipitation gradient. The observed spatial patterns in soil N:P ratio were consistent with previous findings derived from plants and microbes, suggesting that variation in precipitation may induce the imbalance of N:P stoichiometry in forest ecosystems. Our results also indicated that topsoil N:P ratios exhibited a significant increase from the 1980s to 2000s. However, the associations of N:P dynamics with a single element largely depended on forest type. In evergreen forests, soil N:P dynamics were caused by increasing N and decreasing P. Conversely, N:P changes in deciduous broadleaf forests were triggered only by soil N accumulation. Overall, these results demonstrated a stoichiometric shift in soil N:P both spatially and temporally, implying that nutrient imbalance between soil N and P may be accelerated under global change scenarios.