Understanding the distribution patterns of species richness and their underlying drivers is a fundamental issue in macroecology and biogeography. While climate, soil, topography, and human activities are widely recognized as key determinants, their interactive effects on species richness patterns remain underexplored, especially for ecologically and economically valuable Pinus species. Furthermore, the role of indirect effects among variables in shaping these patterns remains incompletely clarified. Here, we integrated distribution data for 60 North American Pinus species to investigate richness patterns across different range sizes. Using Structural Equation Modeling (SEM), we quantified the relative explanatory power of hypotheses related to environmental and anthropogenic factors. We also identified diversity hotspots using the complementary algorithm and the top 5% richness approach. Our results show that topographical heterogeneity is the primary direct correlative factor explaining richness patterns for overall species. Human activities are the dominant correlative factor for both overall and wide-ranged species: their total effect on overall species is primarily derived from indirect associations through modified environmental conditions, while they exert the strongest direct effect on wide-ranged species. The Janzen hypothesis better explains the richness patterns of narrow-ranged species, emphasizing the importance of climatic stability and habitat specificity. Additionally, the complementary algorithm outperformed the top 5% richness approach in identifying priority conservation areas by efficiently capturing all species. This study elucidates the divergent associative mechanisms shaping Pinus species richness across different range sizes, highlighting that human activities and topographical heterogeneity play context-dependent roles. These findings enhance our understanding of the multi-faceted mechanisms influencing Pinus species richness patterns and provide a targeted scientific basis for biodiversity conservation planning and adaptive management strategies under global climate change.