Genomic data reveal deep genetic structure but no support for current taxonomic designation in a grasshopper species complex

Taxonomy has traditionally relied on morphological and ecological traits to interpret and classify biological diversity. Over the last decade, technological advances and conceptual developments in the field of molecular ecology and systematics have eased the generation of genomic data and changed the paradigm of biodiversity analysis. Here we illustrate how traditional taxonomy has led to species designations that are supported neither by high throughput sequencing data nor by the quantitative integration of genomic information with other sources of evidence. Specifically, we focus on Omocestus antigai and O. navasi, two montane grasshoppers from the Pyrenean region that were originally described based on quantitative phenotypic differences and distinct habitat associations (alpine vs. Mediterranean-montane habitats). To validate current taxonomic designations, test species boundaries, and understand the factors that have contributed to genetic divergence, we obtained phenotypic (geometric morphometrics) and genome-wide SNP data (ddRADSeq) from populations covering the entire known distribution of the two taxa. Coalescent-based phylogenetic reconstructions, integrative Bayesian model-based species delimitation, and landscape genetic analyses revealed that populations assigned to the two taxa show a spatial distribution of genetic variation that do not match with current taxonomic designations and is incompatible with ecological/environmental speciation. Our results support little phenotypic variation among populations and a marked genetic structure that is mostly explained by geographic distances and limited population connectivity across the abrupt landscapes characterizing the study region. Overall, this study highlights the importance of integrative approaches to identify taxonomic units and elucidate the evolutionary history of species.

分类学（Taxonomy）传统上依托形态学与生态学性状来阐释并划分生物多样性。近十年来，分子生态学与系统分类学领域的技术进步与概念革新，降低了基因组数据的生成门槛，同时重塑了生物多样性分析的研究范式。本文旨在阐明，传统分类学所确立的物种定名，既未得到高通量测序（high throughput sequencing）数据的支撑，也无法通过基因组信息与其他证据来源的定量整合加以验证。

具体而言，我们聚焦于比利牛斯山区的两种山地蚱蜢——Omocestus antigai与O. navasi，二者最初是基于定量表型差异与独特的生境关联（高山生境与地中海山地生境）而被正式描述的。为验证当前的分类定名、检验物种边界并解析驱动遗传分化的影响因素，我们从覆盖这两个类群全部已知分布范围的种群中，采集了表型（几何形态测量学（geometric morphometrics））与全基因组单核苷酸多态性（SNP）数据（ddRAD测序（ddRADSeq））。

基于溯祖理论的系统发育重建、基于整合贝叶斯模型的物种界定以及景观遗传学分析结果显示：被划归为这两个类群的种群，其遗传变异的空间分布与当前的分类定名并不匹配，且与生态/环境物种形成的理论相悖。本研究结果显示，种群间的表型变异微弱，而显著的遗传结构主要由地理距离以及研究区域崎岖地貌下有限的种群连通性所决定。

综上，本研究凸显了整合研究方法在界定分类单元、阐明物种演化历史方面的重要价值。