DISSERTATION RESEARCH: Lizards of the Family Teiidae: phylogeny, historical biogeography, and continental-scale species delimitation

亚马逊赛跑者（Ameiva Ameiva）分布在南美洲四个非常不同的生物群落中，覆盖的面积比美国大陆还大。该项目将对这种蜥蜴进行首次分布范围的系统地理学研究，为发现该物种的隐性多样性（即新物种）提供机会，同时也为评估热带雨林和干燥栖息地多样化的竞争性假设提供了独特的机会。为亚马逊赛跑者收集的数据也将用于解决气候变化对物种的未来风险。这项工作是与南美同事合作，研究关键的生理特征（例如，温度偏好和性能），以重建物种分布模型和评估灭绝风险。因为对历史分布的建模是基于古气候数据的，所以这些相同的模型可以用来预测温度升高对生物未来分布的影响。这项研究的结果将被开发成一个教学模块，用于向非生物学专业的学生展示在假设检验中使用的真实世界观察，这里主要关注物种形成和生物地理学。来自研究人员广泛的实地和实验室工作的真实例子将为学生提供个性化的数据，并增强他们对科学的多面性及其结论的性质的欣赏。初步结果表明，Ameiva Ameiva代表了一个物种复合体，将通过尽可能多地采样分布，并产生Sanger， NextGen和几种形态数据的组合来确定物种边界。研究人员将访问巴西的三个爬行动物收藏馆，以测量博物馆标本的形态数据。在形态学数据收集的基础上，将对200个美洲花虻个体进行100 ~ 1000s的单核苷酸多态性（ddRADseq）分析，并将其纳入新开发的物种划分（SDL）方法。最近开发的一种集成形态学和分子数据（iBPP）的SDL贝叶斯方法在各种情况下都表现良好，这将是本研究中使用的首选（但不是唯一的）方法。亚马逊河和南美洲干对角线的多样化假设将使用SNP数据与允许分析历史情景的程序进行比较，并采用总结方法来估计每个假设的强度。

The Amazon racerunner (Ameiva ameiva) is distributed across four very different South American biomes that cover an area larger than the continental US. This project will perform the first distribution-wide, phylogeographic study of this lizard species, providing opportunities to find cryptic diversity in the group (i.e., new species) as well as a unique opportunity to evaluate competing hypotheses of diversification in both rainforests and dry habitats. Data collected for the Amazon racerunner will also be used to address future risk to species due to climate change. The work is a collaboration with South American colleagues to study key physiological traits (e.g., temperature preference and performance) to reconstruct species distribution models and assess extinction risk. Because modeling historical distributions is based on paleoclimate data, these same models can be used to predict the effect that increasing temperatures will have on future distributions of organisms. Results from this research will be developed into a teaching module and used to show non-Biology major students real-world observations used in hypothesis testing, here focused on speciation and biogeography. Real examples from the researchers' extensive field and lab work will personalize the data for students and enhance their appreciation of the multi-faceted nature of science, and the nature of its conclusions.Preliminary results suggests that Ameiva ameiva represents a complex of species, which will be tested by sampling as much of the distribution as possible, and generating a combination of Sanger, NextGen, and several classes of morphological data to define species boundaries. Researchers will visit three herpetological collections in Brazil to measure morphological data from museum specimens. In addition to morphological data collection, 100s-1000s of SNPs (ddRADseq) for 200 individuals of A. ameiva will be incorporated into newly developed species delimitation (SDL) methods. A recently developed SDL Bayesian approach that integrates morphological with molecular data (iBPP) was shown to perform well under a variety of scenarios, and this will be the preferred (but not exclusive) method used in this study. Diversification hypotheses for the Amazon and Dry Diagonal of South America will be compared using SNP data with programs that allow the analysis of historical scenarios and a summary approach to estimate the strength of each hypothesis.