DISSERTATION RESEARCH: Integrative Taxonomy and Species Delimitation of Hakes (Merluccius, Merlucciidae)

如何认识物种之间的区别正变得越来越客观和跨学科。尽管存在大数据集的计算挑战，但新方法允许同时分析遗传和非遗传数据。这些方法为在不同进化规模上对全基因组范围内的变异进行采样提供了巨大的潜力，并为理解具有复杂进化历史的分类学群体提供了机会。目前公认的16种鳕鱼是一种有商业价值的鱼类，通常很难识别，因为它们在形态上非常相似，而且物种内有很大的差异。近年来，由于基于有限样本的物种不断分裂和聚集，以及关于形态和遗传变异性的有限数据，这种混淆有所增加。一些鳕鱼物种受到保护关注，北太平洋鳕鱼至少有一个种群被列入《濒危物种法案》。对这些鱼类分类的不了解导致渔业数据不准确，使管理和养护变得困难。这项研究试图通过同时使用遗传和解剖学信息的新方法来揭示黑线鳕的分类学。全基因组范围的偏差的可能性，例如速率异质性，强调了需要从独立的数据中进行证实，例如形态学。相比之下，形态数据包含了信息性和误导性的混合特征，这些特征能够划分一些分类群，但无法检索其他分类群。这项研究将实证测试新的整合方法的适用性，这些方法结合了全基因组单核苷酸多态(SNP)和贝叶斯框架中的形态数据来划定鳕鱼物种。我们将使用两个步骤来划分物种：物种“发现”步骤(没有先验的物种假设)，将个体分配到假定的群体，然后是“确认”步骤，测试群体的稳健性。这项研究将有助于更好地了解一组具有商业价值的鱼类的进化和分类，这些结果可以直接应用于渔业管理。

How the distinction between species is recognized is becoming increasingly objective and cross-disciplinary. Despite the computational challenges of large datasets, new methods allow genetic and non-genetic data to be analyzed together. These methods offer great potential for genome-wide sampling of variation at different evolutionary scales and an opportunity to understand taxonomic groups with complex evolutionary histories. The 16 currently recognized species of hake, a commercially valuable group of fishes, are often difficult to identify because they are very similar morphologically and there is a high level of within-species variation. This confusion has increased in recent years because there has been continuous splitting and lumping of species based on limited sampling, and limited data on morphological and genetic variability. Some hake species are of conservation concern, with at least one population of the North Pacific Hake being listed under the Endangered Species Act. The poor understanding of the taxonomy of these fishes has led to inaccuracies in fisheries data, making management and conservation difficult. This research seeks to shed new light on the taxonomy of hakes by applying the new approaches of using both genetic and anatomical information together. The possibility of genome-wide biases, such as rate heterogeneity, underscores the need for corroboration from independent data such as morphology. In contrast, morphological data contains a mixture of informative and misleading traits that are able to delimit some taxa but unable to retrieve others. This study will empirically test the applicability of new integrative methods that combine genome-wide single nucleotide polymorphisms (SNP) and morphological data in a Bayesian framework for delimiting hake species. A two-step approach to species delimitation will be used: a species 'discovery' step (without a priori species hypotheses) to assign individuals to putative groups, followed by a 'validation' step, which tests the robustness of the groups. This study will result in a better understanding of the evolution and taxonomy of a group of commercially valuable fishes, and these results can be directly applied to fisheries management.