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Hamamelidaceae is an important group that represents the origin and early evolution of angiosperms. Its plants have many uses, such as timber, medical, spice, and ornamental uses. In this study, the complete chloroplast genomes of Loropetalum chinense (R. Br.) Oliver, Corylopsis glandulifera Hemsl., and Corylopsis velutina Hand.‐Mazz. were sequenced using the Illumina NovaSeq 6000 platform. The sizes of the three chloroplast genomes were 159,402 bp (C. glandulifera), 159,414 bp (C. velutina), and 159,444 bp (L. chinense), respectively. These chloroplast genomes contained typical quadripartite structures with a pair of inverted repeat (IR) regions (26,283, 26,283, and 26,257 bp), a large single‐copy (LSC) region (88,134, 88,146, and 88,160 bp), and a small single‐copy (SSC) region (18,702, 18,702, and 18,770 bp). The chloroplast genomes encoded 132–133 genes, including 85–87 protein‐coding genes, 37–38 tRNA genes, and 8 rRNA genes. The coding regions were composed of 26,797, 26,574, and 26,415 codons, respectively, most of which ended in A/U. A total of 37–43 long repeats and 175–178 simple sequence repeats (SSRs) were identified, and the SSRs contained a higher number of A + T than G + C bases. The genome comparison showed that the IR regions were more conserved than the LSC or SSC regions, while the noncoding regions contained higher variability than the gene coding regions. Phylogenetic analyses revealed that species in the same genus tended to cluster together. Chunia Hung T. Chang, Mytilaria Lecomte, and Disanthus Maxim. may have diverged early and Corylopsis Siebold & Zucc. was closely related to Loropetalum R. Br. This study provides valuable information for further species identification, evolution, and phylogenetic studies of Hamamelidaceae plants.

Species diversity (SD) and genetic diversity (GD) are the two basic levels of biodiversity. In general, according to the consensus view, the parallel effects of environmental heterogeneity, area, and connectivity on two levels, can drive a positive correlation between GD and SD. Conversely, a negative correlation or no correlation would be expected if these effects are not parallel. Our understanding of the relationships between SD and GD among different ecosystems, sampling methods, species, and under climate change remains incomplete. In the present study, we conducted a hierarchical meta-analysis based on 295 observations from 39 studies and found a positive correlation between genetic diversity and species diversity (95% confidence interval, 7.6–22.64%). However, significant relationships were not found in some ecosystems when we conducted species–genetic diversity correlation analysis based on a single ecosystem. Moreover, the magnitudes of the correlations generally decreased with the number of sampling units and the annual average the temperature of sampling units. Our results highlight the positive correlation between GD and SD, thereby indicating that protecting SD involves protecting GD in conservation practice. Furthermore, our results also suggest that global increases in temperature during the 21st century will have significant impacts on global biodiversity.

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