Data from: Forecasting changes in population genetic structure of alpine plants in response to global warming

Species range shifts in response to climate and land use change are commonly forecasted with species distribution models based on species occurrence or abundance data. Although appealing, these models ignore the genetic structure of species, and the fact that different populations might respond in different ways due to adaptation to their environment. Here, we introduced ancestry distribution models, i.e., statistical models of the spatial distribution of ancestry proportions, for forecasting intra-specific changes based on genetic admixture instead of species occurrence data. Using multi-locus genotypes and extensive geographic coverage of distribution data across the European Alps, we applied this approach to 20 alpine plant species considering a global increase in temperature from 0.25°C to 4°C. We forecasted the magnitudes of displacement of contact zones between plant populations potentially adapted to warmer environments and other populations. While a global trend of movement in a northeast direction was predicted, the magnitude of displacement was species-specific. For a temperature increase of 2°C, contact zones were predicted to move by 92 km on average (minimum of 5 km, maximum of 212 km), and by 188 km for an increase of 4°C (minimum of 11 km, maximum of 393 km). Intra-specific turnover – measuring the extent of change in global population genetic structure – was generally found to be moderate for 2°C of temperature warming. For 4°C of warming, however, the models indicated substantial intra-specific turnover for ten species. These results illustrate that, in spite of unavoidable simplifications, ancestry distribution models open new perspectives to forecast population genetic changes within species, and complement more traditional distribution-based approaches.为预测物种因气候与土地利用变化引发的分布范围偏移，当前学界普遍基于物种出现记录或种群丰度数据，构建物种分布模型（species distribution models）开展相关预报研究。尽管此类模型具备一定应用潜力，但它们忽略了物种的遗传结构，以及不同种群因适应各自生境而可能产生差异化响应的客观事实。为此，本研究提出了祖先成分分布模型（ancestry distribution models）——即描述祖源比例空间分布的统计模型——以基于遗传祖源混合（genetic admixture）数据，而非物种出现记录，来预测种内演化变化。本研究利用多位点基因型数据与覆盖欧洲阿尔卑斯山广泛地理范围的分布数据，针对20种高山植物开展了该方法的应用测试，同时考量全球气温从0.25℃升至4℃的不同升温情景。研究团队预测了适应温暖生境的植物种群与其他种群之间的接触带（contact zones）的位移幅度。尽管所有物种均呈现出向东北方向迁移的整体趋势，但种群接触带的位移幅度却因物种而异。当气温升高2℃时，接触带的平均位移距离为92公里（位移范围5公里至212公里）；当气温升高4℃时，平均位移距离则达到188公里（位移范围11公里至393公里）。种内遗传更替（intra-specific turnover）——即衡量全球种群遗传结构变化程度的核心指标——在气温升高2℃的情景下普遍处于中等水平。但在气温升高4℃的情景下，模型结果显示有10个物种出现了显著的种内遗传更替。上述研究结果表明，尽管祖先成分分布模型不可避免地存在简化假设，但它为预测物种种群的遗传变化提供了全新视角，同时也可作为传统基于物种分布的研究方法的有益补充。