揭示气候动荡与环境异质性对森林关键类群谱系分化与种群动态的影响，有利于理解东亚物种多样性形成机制。本项目拟对第三纪孑遗植物领春木属进行广泛群体取样，基于叶绿体DNA、ITS序列与nSSR变异，利用系统发育与生物地理学方法，分析物种分化时间、历史分布区与生物地理事件、谱系地理结构。利用限制性酶切位点关联DNA测序（RAD-Seq）技术鉴定群体单核苷酸多态性（SNPs），基于整合数据，利用群体遗传学、IMa、ABC模型方法分析物种进化历史与谱系分化过程，结合生态位模型与多变量生态位方法，揭示物种与谱系分化的历史驱动因子。通过基因组扫描方法鉴定RAD中性与outlier位点，利用景观遗传学方法分析地理与景观效应、生态因子对群体\谱系分化以及遗传多样性空间分布格局的影响，解析适应性遗传变异的空间分布格局及影响因子。中性与适应性位点结合鉴定“进化重要单位”，提出领春木属遗传资源保护策略。

Elucidating the demographic effects of Quaternary climatic oscillations and environmental heterogeneity increases our understanding of the roles of climate change and niche divergence in shaping biodiversity in East Asia. In this study, we will study on the lineage divergence, geographic pattern and genetic diversity of Euptelea, one keystone genus endemic to East Asian Tertiary-relic deciduous forests. Euptelea contains two extant species, E. pleiosperma and E. polyandra.. The samples of Euptelea have been sampled from different regions across the distribution range of the genus in China, Japan and northern India. The sequence variation of both chloroplast DNA (cpDNA) and nuclear ITS as well as nuclear SSR dataset have been used to investigate the geographic distribution patterns, phylogeographic structure, and phylogenetic relationships of haplotypes. Time-calibrated phylogenetic and phylogeographic inferences will be used to trace ancestral areas and biogeographical events. Based on the patterns of lineage diversification, we will further use a genome-wide sampling of SNPs identified within restriction site–associated DNA (RAD) tags to investigate the historical forces responsible for geographic pattern and the mechanisms of speciation and lineage diversification. The population genetics methods and Bayesian and ABC models will be used to infer demorgraphic history of species and lineages. When combining with ecological niche modeling and multivariate niche method, we can address what historical processes, e.g. fragmentation, expansion, long-distance colonization, have the strongest influence on the lineage divergence and geographic pattern of Euptelea. By using genome scan methods, we can identify RAD neutral and outlier loci. Based on landscape genetics methods, we will model environmental data using nonparametric multiple regression to explain lineage divergence and genetic differentiation as a function of spatio-ecological effects. In addition, to identify patterns of adaptive genetic variation on landscapes, and quantify effects of environmental factors on patterns of adaptive genetic variation, we will test the correlations between clines in allele frequencies of individual outlier loci and environmental variation. Based on multi-loci genetic data, evolutionarily important units can be identified. This information will be useful for developing scientific conservation and appropriate management strategies for this endangered genus.