Fine‐Scale Spatial Genetic Structure and Leaf Shape Variation in Five Fagaceae Species: Insights Into Conservation and Adaptation

Fine-scale spatial genetic structure (fine-scale SGS) refers to the pattern of spatial distribution of genetic variation at the local scale, which can indirectly estimate gene flow among individuals and reveal microevolutionary processes in plant populations. Although fine-scale SGS is important in explaining dispersal patterns and adaptive variation in plants, few studies have explored its potential application in species conservation strategies. In addition, phenotypic traits, particularly leaf shape, may also exhibit specific spatial variation patterns at fine scales. In this study, we investigated the genetic and leaf shape variation of two genus <i>Quercus</i> species (<i>Quercus glauca</i> Thunb. and <i>Q</i>. <i>multinervis</i> J. Q. Li) and three genus <i>Castanopsis</i> species (<i>Castanopsis tibetana</i> Hance, <i>C</i>. <i>faberi</i> Hance, and <i>C. fargesii</i> Franch.) in Wuyishan National Park in southeastern China. Using genetic markers, we found that <i>Quercus</i> species exhibited stronger fine-scale SGS and more limited gene flow than <i>Castanopsis</i> species, suggesting greater habitat fragmentation affecting local <i>Quercus</i> species. Leaf morphological analysis revealed inter-generic differences and partial overlap in leaf shape between <i>Quercus</i> and <i>Castanopsis</i> species, with the greatest variation observed in leaf area (LA) and leaf mass (LM). In addition, all five Fagaceae species exhibited significant diminishing returns, with <i>C. fargesii</i> showing the most pronounced effect and possessing the smallest leaves, which may enhance its adaptability to the harsh environments. Despite the leaf shape overlaps blurring species boundaries between <i>Quercus</i> and <i>Castanopsis</i> species, their genetic structure is remained clearly distinct. The observed differences in the intensity of fine-scale SGS and leaf shape variation between the two genera reflect their different environmental adaptability, offering new insights into the integration of genetic and phenotypic data for conservation planning.