Understanding spatial patterns of species richness is a hot topic in macroecology because of its significance in biodiversity conservation. In many previous studies, current environmental variables representing energy and water availability have been considered as the main drivers of geographic diversity patterns. However, the roles of different environmental variables vary for different taxonomic groups and distinct biogeographic extents; therefore, there is no consensus among ecologists on which environmental variables are primary drivers of the spatial variation in species richness. China covers a wide range of latitudes and longitudes and has a wide range of variation in climate and vegetation (e.g., from tropical rain forest in the south to boreal forest in the northwest and desert in the north and northwest). Thus, China offers great opportunity for testing the relationships between species richness and environment. In the present study, geographic pattern of ant species richness in China and its relationships with environmental factors were investigated based on ant distribution data and environmental variables at a provincial scale. Several studies on the distribution of ants in other geographical areas show that temperature (energy) is the most important factor that determines ant species richness patterns. This conclusion might also apply to China. Therefore, four hypotheses were tested in the present study. (1) Compared to the mean annual precipitation, ant species richness pattern was more likely affected by the mean annual temperature. (2) Compared to the habitat heterogeneity associated with precipitation, ant species richness pattern was more affected by habitat heterogeneity associated with temperature. Since ants are ectotherms and their survivorship under low temperature in winter is critical for their populations and distribution, we further assumed that (3) compared to the mean annual temperature, mean temperature of the coldest month better explains the spatial differentiation of ant species richness. Given that precipitation seasonality and temperature seasonality are mainly determined by annual temperature range and annual precipitation range, we inferred that, (4) compared to precipitation seasonality, temperature seasonality can better explain spatial ant species richness pattern. To test these hypotheses, GIS was used to map ant species diversity and simple and multiple linear regressions were used to determine the relative roles of different environmental variables. The results showed that:(1) Ant species richness decreases significantly with latitude but not longitude; the species richness is higher in southern provinces of China than in northern and northwestern regions of China. (2) Simple linear regression analyses showed that, mean temperature of the coldest month (TEM_min, R_adj²=0.532), annual precipitation (PREC, R_adj²=0.376), and annual temperature range (TEM_var, R_adj²=0.539) are the variables that best fit energy, water, and seasonality, respectively. However, none of the factors reflecting habitat heterogeneity have significant effect on ant species richness when assessed independently. (3) Our results indicate that the best model based on the Akaike information criterion (AIC) includes the mean annual temperature (TEM), the range of elevation within a province (ELEV_range), and the annual temperature range (TEM_var). This model can explain 68.4% of the geographic variance in ant species richness across different provinces in China. The above four hypotheses were confirmed, and we conclude that temperature is the most important factor controlling ant distribution in China. In addition, our analysis revealed that ant fauna in Hainan, Guizhou, Jiangxi, Sichuan, Anhui, and Shanxi is poorly sampled, and these provinces are potential hot spots for new ant records.