HLM analysis for the factors driving terrestrial mammal species richness in China

Among the factors influencing terrestrial mammal species richness, macro-level variables—such as latitude, net primary productivity (NPP), temperature seasonality (TS), and elevation (Ele)—reflect large-scale variations related to energy availability, food resources, and climatic changes. In contrast, micro-level factors—including surface area coefficient (SAC), vegetation vertical habitat capacity (VVHC), and Shannon's Diversity Index (SHDI)—primarily capture intra-regional differences. These two levels of factors are not parallel but hierarchical. Therefore, Hierarchical Linear Model (HLM) was applied to analyze the interactions of factors at different levels and their effects on the dependent variable.This study considers both macro- and micro-scale factors and introduces new indices: VVHC and SAC, to capture different aspects of available habitat. The analysis, carried out from the perspective of the hierarchical roles that exist between the factors, provides a fresh insight for the interpretation of the driving factors of species richness.