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The combination of population and landscape genetics can facilitate the understanding of conservation strategy under the changing climate. Here, we focused on the two most diverse and ecologically important evergreen oaks: Quercus aquifolioides and Quercus spinosa in Qinghai–Tibetan Plateau (QTP), which is considered as world’s biodiversity hotspot. We genotyped 1,657 individuals of 106 populations at 15 nuclear microsatellite loci throughout the species distribution range. Spatial patterns of genetic diversity were identified by mapping the allelic richness (AR) and locally common alleles (LCA) according to the circular neighborhood methodology. Migration routes from QTP were detected by historical gene flow estimation. The response pattern of genetic variation to environmental gradient was assessed by the genotype–environment association (GEA) analysis. The overall genetic structure showed a high level of intra-species genetic divergence of a strong west-east pattern. The West-to-East migration route indicated the complex demographic history of two oak species. We found evidence of isolation by the environment in Q. aqu -East and Q. spi -West lineage but not in Q. aqu -West and Q. spi -East lineage. Furthermore, priority for conservation should be given to populations that retain higher spatial genetic diversity or isolated at the edge of the distribution range. Our findings indicate that knowledge of spatial diversity and migration route can provide valuable information for the conservation of existing populations. This study provides an important guide for species conservation for two oak species by the integration of population and landscape genetic methods.

Plant phenotypic characteristics, especially leaf morphology of leaves, are an important indicator for species identification. However, leaf shape can be extraordinarily complex in some species, such as oaks. The great variation in leaf morphology and difficulty of species identification in oaks have attracted the attention of scientists since Charles Darwin. Recent advances in discrimination technology have provided opportunities to understand leaf morphology variation in oaks. Here, we aimed to compare the accuracy and efficiency of species identification in two closely related deciduous oaks by geometric morphometric method (GMM) and deep learning using preliminary identification of simple sequence repeats (nSSRs) as a prior. A total of 538 Asian deciduous oak trees, 16 Q. aliena and 23 Q. dentata populations, were firstly assigned by nSSRs Bayesian clustering analysis to one of the two species or admixture and this grouping served as a priori identification of these trees. Then we analyzed the shapes of 2328 leaves from the 538 trees in terms of 13 characters (landmarks) by GMM. Finally, we trained and classified 2221 leaf‐scanned images with Xception architecture using deep learning. The two species can be identified by GMM and deep learning using genetic analysis as a priori. Deep learning is the most cost‐efficient method in terms of time‐consuming, while GMM can confirm the admixture individuals' leaf shape. These various methods provide high classification accuracy, highlight the application in plant classification research, and are ready to be applied to other morphology analysis. We conducted a comparative analysis to evaluate the accuracy and efficiency of the GMMs and deep learning methods in discriminating two closely related oaks, Q. aliena and Q. dentata, using genetics as a priori classification. We found that deep learning is the most cost‐efficient method in terms of time and cost, whereas GMMs can confirm the leaf shape of admixture individuals and demonstrate the tendency of leaf contraction and expansion. Moreover, we found that the shape of admixture individuals was close to that of Q. dentata, suggesting that oaks retain high levels of fitness variation, with Q. aliena being more favored by selection in leaf morphological traits.

Background Although allopatric speciation is viewed as the most common way in which species originate, allopatric divergence among a group of closely related species has rarely been examined at the population level through phylogeographic analysis. Here we report such a case study on eight putative cypress ( Cupressus ) species, which each have a mainly allopatric distribution in the Qinghai-Tibetan Plateau (QTP) and adjacent regions. The analysis involved sequencing three plastid DNA fragments ( trn D- trn T, trn S- trn G and trn L- trn F) in 371 individuals sampled from populations at 66 localities. Results Both phylogenetic and network analyses showed that most DNA haplotypes recovered or haplotype-clustered lineages resolved were largely species-specific. Across all species, significant phylogeographic structure ( N ST > G ST , P < 0.05) implied a high correlation between haplotypes/lineages and geographic distribution. Two species, C. duclouxiana and C. chengiana , which are distributed in the eastern QTP region, contained more haplotypes and higher diversity than five species with restricted distributions in the western highlands of the QTP. The remaining species, C. funebris , is widely cultivated and contained very little cpDNA diversity. Conclusions It is concluded that the formation of high mountain barriers separating deep valleys in the QTP and adjacent regions caused by various uplifts of the plateau since the early Miocene most likely promoted allopatric divergence in Cupressus by restricting gene flow and fixing local, species-specific haplotypes in geographically isolated populations. The low levels of intraspecific diversity present in most species might stem from population bottlenecks brought about by recurrent periods of unfavorable climate and more recently by the negative impacts of human activities on species' distributions. Our findings shed new light on the importance of geographical isolation caused by the uplift of the QTP on the development of high plant species diversity in the QTP biodiversity hotspot.