Novel Procedures for Simulating Phylogenetic Trees and Speciation

生物多样性正在下降，保护在当今社会变得越来越重要。物种形成过程，即新物种如何进化，是维持生物多样性的基础，但尚未完全理解。系统发生树显示了当今多样性的起源，精确地指出了物种进化的时间并描述了它们的亲缘关系。它们也被用于模拟不同的疾病菌株，如流感。已经进行了大量的研究，目的是通过评估各种模型来解释物种形成和系统发育树。在这个项目中，我们使用中性模型，它提出了一个有争议的假设，即所有个体都以相同的方式与系统交互，而不管他们的物种。尽管他们的假设，这些模型匹配生态数据与惊人的精度，吸引了大量的研究关注。对于系统发育树的建模，中性模型改进了许多早期的模型，因为物种灭绝的概率与代表性个体的数量成正比。点突变是这些模型中经常使用的三种物种形成模式之一。它指出，每一个新生个体都有恒定的概率成为一个新物种。一个强大的计算方法的基础上合并追溯个人的祖先在时间上。这解决了与替代远期模拟相关的等待平衡和限制性模拟大小的问题。点突变创造了许多只有一个成员的物种，这在现实中是观察不到的。因此，它生成的系统发育树似乎不切实际，许多传递突变被视为新物种。其他两种机制是随机裂变和外围孤立物种形成，新物种作为一个小的创始人口到达。这种方法是有前途的，但合并模拟不能用于这些模式的形态。这是非常严格的，并阻止详细的研究。我们将开发新的修改合并，使其适用于研究随机裂变和周边孤立模式的物种形成。自然界中的物种形成是一个渐进的过程，但现有的三种机制都假设物种形成是一个突然的事件。我们提出了一种新的物种形成机制，每个人都有一个简单的基因组，包括两个基因。这就以不同的方式解决了传递突变的问题;它们存在，但永远不会被定义为一个独特的物种，因为传递突变只会影响两个基因中的一个。这种物种形成机制是渐进的，因为第一个基因的突变和第二个基因的突变之间有时间的流逝。正是第二个基因的突变完成了物种形成过程。我们将全面调查这种模式的物种形成和它产生的系统发育树。我们有一些令人兴奋的应用程序，这些新的方法，其中每一个都需要一个不同的空间显式结构的模型。一个二维的空间显式版本的模型是适合与合作者斯蒂芬哈贝尔的经验cumbergenies进行比较。我们可以访问在降雨梯度上收集的进一步数据集。这将使我们有机会测试包含栖息地异质性的模型版本。一个不同的社区网络是一个适当的空间结构，包括群岛和疾病动态的许多应用。例如，我们的合作者Luke Harmon从淡水湖泊中收集了浮游动物数据，与中性模型进行比较将是有见地的。还存在关于生物膜的医学应用。这些是抗生素无法治疗的粘性基质和感染。最近的研究表明，这些生物膜的多样化率极高。使用三维中性模型的测试将是理解生物膜内竞争的有见地的研究。

Biodiversity is in decline and conservation is becoming increasingly important in today's society. The process of speciation, how new species evolve, is fundamental to biodiversity maintenance but is not fully understood. Phylogenetic trees show the origins of present day diversity, pinpointing when species evolved and describing their relatedness. They are also used in modeling the different strains of diseases such as flu. A lot of research has taken place with the aim of interpreting speciation and phylogenetic trees by evaluating various models. In this project, we use neutral models, which make the controversial assumption that all individuals interact with the system in an identical manner regardless of their species. Despite their assumptions, these models match ecological data with astounding precision, attracting a lot of research attention. For modeling phylogenetic trees, neutral models improve on many earlier models because the probability of a species becoming extinct becomes proportional to the number of representative individuals. Point mutation is one of three modes of speciation regularly used in these models. It states that every newborn individual has a constant probability being a new species. A powerful computational method based on coalescence traces the ancestry of individuals backwards in time. This solves the problems of waiting for equilibrium and restrictive simulation sizes associated with alternative forwards simulations. Point mutation creates a lot of species with only one member, which is not observed in reality. The phylogenetic trees it generates consequently appear unrealistic having many passing mutations counted as novel species. The other two mechanisms are random fission and peripheral isolate speciation where new species arrive as a small founding population. This approach is promising but the coalescence simulations cannot be used for these modes of speciation. This is extremely restrictive and prevents detailed studies. We will develop novel modification of coalescence to make it suitable for investigating the random fission and peripheral isolate modes of speciation. Speciation in nature is a gradual process but all three existing mechanisms assume a sudden speciation event. We propose a novel speciation mechanism where each individual has a simple genome including two genes. This solves the problem of passing mutations in a different way; they exist but would never be defined as a distinct species because the passing mutation would only influence one of the two genes. This mechanism of speciation is gradual because time passes between the mutation of the first gene and mutation of the second gene. It is mutation of the second gene that completes the speciation process. We will fully investigate this mode of speciation and the phylogenetic trees it generates. We have a number of exciting applications for these novel methods, each of which requires a different spatially explicit structure in the model. A two dimensional spatially explicit version of the model is suitable for comparison with empirical phylogenies from collaborator Stephen Hubbell. We have access to a further dataset collected across a rainfall gradient. This will give us the opportunity to test a version of the model that includes habitat heterogeneity. A network of distinct communities is an appropriate spatial structure for many applications including archipelagos and disease dynamics. For example, our collaborator Luke Harmon has zooplankton data collected from fresh water lakes, where a comparison with neutral models would be insightful. A medical application also exists regarding bioflms. These are adhesive matrices and infections that are untreatable with antibiotics. Recent research has shown an extreme rate of diversification in these biofilms. A test using a three dimensional neutral model would be insightful research in understanding within biofilm competition.