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基于谱系地理划分的物种假说产生了一套整合的穴居蟾蜍分类学(蒙氏泽蛙)。

Speciation Hypotheses from Phylogeographic Delimitation Yield an Integrative Taxonomy for Seal Salamanders (Desmognathus monticola).

机构信息

Department of Biological Sciences, The George Washington University, Washington, DC 20052USA.

Department of Vertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20560-0162, USA.

出版信息

Syst Biol. 2023 May 19;72(1):179-197. doi: 10.1093/sysbio/syac065.

Abstract

Significant advances have been made in species delimitation and numerous methods can test precisely defined models of speciation, though the synthesis of phylogeography and taxonomy is still sometimes incomplete. Emerging consensus treats distinct genealogical clusters in genome-scale data as strong initial evidence of speciation in most cases, a hypothesis that must therefore be falsified under an explicit evolutionary model. We can now test speciation hypotheses linking trait differentiation to specific mechanisms of divergence with increasingly large data sets. Integrative taxonomy can, therefore, reflect an understanding of how each axis of variation relates to underlying speciation processes, with nomenclature for distinct evolutionary lineages. We illustrate this approach here with Seal Salamanders (Desmognathus monticola) and introduce a new unsupervised machine-learning approach for species delimitation. Plethodontid salamanders are renowned for their morphological conservatism despite extensive phylogeographic divergence. We discover 2 geographic genetic clusters, for which demographic and spatial models of ecology and gene flow provide robust support for ecogeographic speciation despite limited phenotypic divergence. These data are integrated under evolutionary mechanisms (e.g., spatially localized gene flow with reduced migration) and reflected in emergent properties expected under models of reinforcement (e.g., ethological isolation and selection against hybrids). Their genetic divergence is prima facie evidence for species-level distinctiveness, supported by speciation models and divergence along axes such as behavior, geography, and climate that suggest an ecological basis with subsequent reinforcement through prezygotic isolation. As data sets grow more comprehensive, species-delimitation models can be tested, rejected, or corroborated as explicit speciation hypotheses, providing for reciprocal illumination of evolutionary processes and integrative taxonomies. [Desmognathus; integrative taxonomy; machine learning; species delimitation.].

摘要

在物种划分方面已经取得了重大进展,许多方法可以精确地检验物种形成的模型,尽管系统发生地理学和分类学的综合有时仍然不完全。新兴共识认为,在大多数情况下,基因组规模数据中明显的谱系聚类是物种形成的有力初始证据,因此,这个假设必须在明确的进化模型下被证伪。我们现在可以利用越来越大的数据集来检验将性状分化与特定的分歧机制联系起来的物种形成假设。因此,综合分类学可以反映出对每个变异轴与潜在物种形成过程之间关系的理解,以及对不同进化谱系的命名法。我们在这里用海豹蝾螈(Desmognathus monticola)来说明这种方法,并介绍了一种新的无监督机器学习物种划分方法。尽管有广泛的系统地理学分歧,蝾螈仍然以其形态保守性而闻名。我们发现了 2 个地理遗传群,对于这些群,生态和基因流的人口和空间模型为生态地理物种形成提供了强有力的支持,尽管表型分化有限。这些数据是根据进化机制(例如,具有减少迁移的空间本地化基因流)进行整合的,并反映在强化模型下预期的新兴特性中(例如,行为、地理和气候等轴上的行为隔离和对杂种的选择)。它们的遗传分化是物种水平独特性的初步证据,得到了物种形成模型和沿着行为、地理和气候等轴的分化的支持,这表明存在生态基础,并随后通过前合子隔离得到强化。随着数据集变得更加全面,可以对物种划分模型进行测试、拒绝或证实,作为明确的物种形成假设,为进化过程和综合分类学提供相互启示。[Desmognathus;综合分类学;机器学习;物种划分。]

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