The current study aims to: 1) Evaluate the richness pattern of conifer species; 2) Assess the relative importance of climatic, topographic, edaphic, and human factors on richness patterns; 3) Explore the dominant drivers at vulnerability and endemism levels; and 4) Identify the most important areas of conifer diversity (IPAs). We compiled 8,962 distributional records of 97 conifer species to estimate the richness at 50 km2 resolution. Generalized linear models and hierarchical partitioning were applied to evaluate the effect of drivers on the richness pattern followed by stepwise regression to select the best group of predictors. We found that topographic heterogeneity and soil nutrient-fertility were consistently the strongest drivers of richness, while seasonality, energy, water, and human drivers contributed much lower. Moreover, IPAs mostly located outside nature reserves, meanwhile inside ecoregions. Overall, our findings indicated that hypotheses of soil-topographic heterogeneity would provide great insights into conservation of conifer diversity and ecosystem-functioning.