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

物种之间的区别是如何认识越来越客观和跨学科。尽管大型数据集的计算挑战，新方法允许遗传和非遗传数据一起分析。这些方法提供了巨大的潜力，在不同的进化尺度和机会，以了解复杂的进化历史的分类群体的全基因组变异的采样。鳕鱼是一种具有商业价值的鱼类，目前公认的16种鳕鱼往往难以识别，因为它们在形态上非常相似，种内变异程度很高。近年来，这种混淆有所增加，因为根据有限的取样和有限的形态和遗传变异数据，不断将物种分开和集中。一些鳕鱼物种受到保护，至少有一个北太平洋鳕鱼种群被列入濒危物种法案。对这些鱼类的分类学缺乏了解，导致渔业数据不准确，使管理和保护变得困难。本研究旨在通过应用遗传和解剖信息相结合的新方法，为鳕鱼的分类学研究提供新的思路。全基因组偏差的可能性，如速率异质性，强调了从独立数据（如形态学）确证的必要性。相比之下，形态学数据包含信息和误导的特征，能够界定一些分类群，但不能检索其他的混合物。本研究将实证测试新的整合方法，结合联合收割机全基因组单核苷酸多态性（SNP）和形态数据的贝叶斯框架界定鳕鱼物种的适用性。将采用两步法进行物种界定：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“验证”步骤，测试群体的稳健性。这项研究将导致更好地了解一组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.