Schima superba is an ecologically and economically valuable evergreen tree that plays a key role in reforestation, firebreak establishment, and urban landscaping in subtropical China. To evaluate its adaptive diversity, this study combined physiological trait assessment with SSR-based genetic analysis across eight natural populations comprising 122 individuals. Five physiological traits, including chlorophyll, malondialdehyde, proline, soluble protein, and soluble sugar, showed significant variation among and within populations ( p < 0.01), with HTHL and HBB populations exhibiting the greatest phenotypic variability. Using 20 polymorphic SSR loci, we detected high genetic diversity (He = 0.804, PIC = 0.786) and moderate differentiation (Fst = 0.111) with strong gene flow (Nm = 2.23). STRUCTURE and PCoA analyses revealed five genetic clusters, and the HBN and HTHL populations displayed distinct genotypes. Mixed linear model analysis identified 14 significant SSR–trait associations, with SS30 and SS32 strongly correlated with malondialdehyde and chlorophyll content. These results demonstrate a close relationship between genetic and physiological diversity in S. superba and provide essential molecular resources for its conservation, breeding, and adaptive improvement.
Liu et al. (2026) studied this question.