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Fine-Scale Spatial Genetic Structure and Leaf Shape Variation in Five Fagaceae Species: Insights Into Conservation
Rongle Wang1, Yanjun Luo1, Min Qi1
1School of Ecology and Nature Conservation Beijing Forestry University Beijing China.
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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 Quercus species (Quercus glauca Thunb. and Q. multinervis J. Q. Li) and three genus Castanopsis species (Castanopsis tibetana Hance, C. faberi Hance, and C. fargesii Franch.) in Wuyishan National Park in southeastern China. Using genetic markers, we found that Quercus species exhibited stronger fine-scale SGS and more limited gene flow than Castanopsis species, suggesting greater habitat fragmentation affecting local Quercus species. Leaf morphological analysis revealed inter-generic differences and partial overlap in leaf shape between Quercus and Castanopsis 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 C. fargesii 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 Quercus and Castanopsis 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.
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