Collaborative Research: Extending phylogenetic comparative methods for evaluating within-species trends in a macroevolutionary context

合作研究：扩展系统发育比较方法，以评估宏观进化背景下的种内趋势

• 批准号: 1556379
• 负责人: Dean Adams
• 金额: $ 31.5万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1556379&HistoricalAwards=false
• 关键词: Collaborative; Research; Extending; phylogenetic; comparative

How do evolutionary changes within species translate into broad patterns across a group of related species? This question is at the heart of evolutionary ecology, but has been very difficult to answer. A major problem is that current analytical approaches, known as phylogenetic comparative methods, require that a single value be used to represent a trait for an entire species. As a result, valuable information on differences among individuals within a species can't be used. This limits the types of questions that these comparative methods can address. The main goal of this project is to develop new analytical software that accounts for trait variation within species, which will result in a much more powerful computational tool. The newly developed software will be tested using experimental data from salamanders and fish. This award will have multiple broader impacts. This new tool will let a whole new set of hypotheses be tested and will be widely used by scientists doing evolutionary ecology research. Undergraduate students will receive hands-on training in mathematical modeling and software development. Educational outreach activities include a research-education exchange between a regional undergraduate university and a large research university. National and international teaching workshops will help train the next generation of students and scientists from around the world.Analyses of phenotypic data tend to remain distinctly different enterprises between microevolutionary and macroevolutionary studies. Consequently, we still do not know how microevolutionary trends from ecological selection associate to macroevolutionary trends across phylogenies. Phylogenetic comparative methods (PCMs) measure the amount of phylogenetic signal in a set of data or account for the phylogenetic relatedness among observations when evaluating ecological variation, but currently work only with single values for species. Thus, large amounts of within-species data are disregarded when using PCMs, which limits their inferential capability. This project will develop an analytical solution to this problem, and provide a framework for extending PCMs to large data sets comprising microevolutionary data. The methods developed will allow scientists to evaluate the consistency of small-scale and large scale evolutionary relationships in a comparative framework. This project will incorporate both theoretical and empirical components. Statistical research will evaluate the statistical power and inferential error rates of "expanded-PCM" to varied analytical designs, phenotypic variables, tree topologies, and data balance. These methods will be applied empirically to two vertebrate systems to study the phylogenetic relatedness of intra-species morphological variation, as it is associated with intra- and interspecific ecological variation. Several educational outreach activities will also be conducted, including: a research-in-education exchange between a primarily undergraduate university and large research university, and teaching workshops in quantitative methods to train the next generation of students and scientists from around the world.

物种内部的进化变化如何转化为一组相关物种的广泛模式？这个问题是进化生态学的核心，但一直很难回答。一个主要的问题是，目前的分析方法，称为系统发育比较方法，需要一个单一的值被用来代表整个物种的特征。因此，关于物种内个体差异的有价值的信息无法使用。这就限制了这些比较方法可以解决的问题类型。该项目的主要目标是开发新的分析软件，解释物种内的性状变异，这将导致一个更强大的计算工具。新开发的软件将使用蝾螈和鱼类的实验数据进行测试。该奖项将产生广泛的影响。这一新工具将使一整套新的假设得到检验，并将被从事进化生态学研究的科学家广泛使用。本科生将接受数学建模和软件开发方面的实践培训。教育推广活动包括一所区域本科大学与一所大型研究型大学之间的研究教育交流。国家和国际教学研讨会将有助于培养来自世界各地的下一代学生和科学家。表型数据的分析往往仍然是微观进化和宏观进化研究之间明显不同的企业。因此，我们仍然不知道生态选择的微观进化趋势如何与跨物种的宏观进化趋势相关联。系统发育比较方法（PCMs）测量一组数据中的系统发育信号的量，或在评估生态变化时考虑观察结果之间的系统发育相关性，但目前仅适用于物种的单一值。因此，当使用PCM时，大量的物种内数据被忽略，这限制了它们的推理能力。这个项目将开发一个分析解决这个问题，并提供一个框架，扩展PCM的大数据集，包括微进化数据。开发的方法将使科学家能够在比较框架中评估小规模和大规模进化关系的一致性。该项目将包括理论和经验两个组成部分。 统计研究将评估“扩展PCM”对不同分析设计、表型变量、树形拓扑和数据平衡的统计功效和推断错误率。这些方法将经验性地应用到两个脊椎动物系统中，以研究种内形态变异的系统发育相关性，因为它与种内和种间生态变异相关。还将开展若干教育外联活动，包括：一所以本科为主的大学与大型研究型大学之间的教育研究交流，以及培训世界各地下一代学生和科学家的定量方法教学讲习班。