Data from: Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American Pika.

A central goal of phylogeography is to identify and characterize the processes underlying divergence. One of the biggest impediments currently faced is how to capture the spatiotemporal dynamic under which a species evolved. Here we described an approach that couples species distribution models (SDMs), demographic and genetic models in a spatiotemporally explicit manner. Analyses of American Pika (Ochotona priniceps) from the sky islands of the central Rocky Mountains of North America are used to provide insights into key questions about integrative approaches in landscape genetics, population genetics and phylogeography. This includes (i) general issues surrounding the conversion of time-specific SDMs into simple continuous, dynamic landscapes from past to current, and (ii) the utility of SDMs to inform demographic models with deme-specific carrying capacities and migration potentials, as well as (iii) the contribution of the temporal dynamic of colonization history in shaping genetic patterns of contemporary populations. Our results support that the inclusion of a spatiotemporal dynamic is an important factor when studying the impact of distributional shifts on patterns of genetic data. Our results also demonstrate the utility of SDMs to generate species-specific predictions about patterns of genetic variation that account for varying degrees of habitat specialization and life-history characteristics of taxa. Nevertheless, the results highlight some key issues when converting SDMs for use in demographic models. Because the transformations have direct affects on the genetic consequence of population expansion by prescribing how habitat heterogeneity and spatiotemporal variation is related to the species-specific demographic model, it is important to consider alternative transformations when studying the genetic consequences of distributional shifts.系统地理学（phylogeography）的核心目标之一是识别并解析驱动物种分化的演化过程。当前该领域面临的最大挑战之一，在于如何捕捉物种演化所依托的时空动态格局。本研究提出了一种以时空显式方式整合物种分布模型（SDMs）、种群统计模型与群体遗传模型的研究方法。本研究以北美中部落基山脉天空群岛中的美洲鼠兔（Ochotona priniceps）为研究对象，为景观遗传学、群体遗传学与系统地理学领域的整合研究方法相关核心问题提供了研究视角。该研究涵盖三大核心内容：其一，围绕将特定时间尺度的SDMs转化为从古至今的连续动态景观所涉及的通用问题；其二，利用SDMs为基于同类群（deme）特有承载能力与迁移潜力的种群统计模型提供参数支撑的应用价值；其三，定殖历史的时空动态对当代种群遗传格局塑造的贡献。研究结果表明，在探究物种分布范围变化对遗传数据格局的影响时，纳入时空动态因素是关键考量因素。本研究同时证实，SDMs可用于生成针对特定物种的遗传变异格局预测，该预测可充分纳入分类群（taxa）不同程度的生境特化特征与生活史属性。尽管如此，研究结果也凸显了将SDMs转化后应用于种群统计模型时存在的若干核心问题。由于这类转化通过明确生境异质性与时空变异与特定物种种群统计模型的关联方式，直接影响种群扩张的遗传效应，因此在探究分布范围变化的遗传后果时，考虑不同的转化方案具有重要意义。