Yuan Yumei, Feng Yu, Wang Jingbo, Ulah Fazal, Yuan Meng, Gao Yundong
Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China.
University of Chinese Academy of Sciences, Beijing, China.
Mol Ecol. 2025 Apr 26:e17779. doi: 10.1111/mec.17779.
The use of morphological traits as a practical approach for delimiting taxa at various ranks has long been regarded as a reliable basis for taxonomy. However, its efficacy has been increasingly called into question in many taxonomic groups due to its inherent limitations, such as failing to account for phenotypic plasticity, ecologically driven variation (e.g., ecotypes), and parallel evolution. These factors often introduce ambiguity or misleading similarities, thereby obscuring the true evolutionary relationships among taxa, particularly in the context of species delimitation. In the present study, we employ an integrated methodology that combines quantitative morphological analyses, whole-genome data, and ecological measurements to resolve the species boundaries of two morphologically similar roses, Rosa sericea and Rosa hugonis, which have long been considered as two distinct species but lack clear morphological boundaries. Our findings reveal that the unbiased analysis of morphological data based on a large and representative sample size was insufficient to identify effective diagnostic traits. However, when complemented with genome-wide population-level sequencing data or integrated with geographic and ecological niche assessments, the delineation of species boundaries was significantly improved. Furthermore, ecological data provide additional insight into the abiotic factors driving interspecific and intraspecific divergence. By integrating multiple lines of evidence-spanning genomic (intrinsic) and phenotypic (extrinsic) traits-and incorporating the interaction between species and their environments, species boundaries can be delineated with greater confidence. A well-defined species can thus be established through the mutual corroboration of diverse datasets, thereby ensuring a more rigorous and comprehensive taxonomic framework.
长期以来,利用形态特征作为界定不同分类阶元分类群的实用方法一直被视为分类学的可靠基础。然而,由于其固有的局限性,如无法解释表型可塑性、生态驱动的变异(如生态型)和平行进化,其有效性在许多分类群中越来越受到质疑。这些因素常常导致模糊性或误导性的相似性,从而掩盖了分类群之间真正的进化关系,特别是在物种界定方面。在本研究中,我们采用了一种综合方法,将定量形态分析、全基因组数据和生态测量相结合,以解决两种形态相似的玫瑰——绢毛蔷薇(Rosa sericea)和黄刺玫(Rosa hugonis)的物种界限问题。这两种玫瑰长期以来被视为两个不同的物种,但缺乏明确的形态界限。我们的研究结果表明,基于大量且具有代表性的样本量对形态数据进行无偏分析,不足以识别有效的诊断特征。然而,当辅以全基因组群体水平的测序数据或与地理和生态位评估相结合时,物种界限的划定得到了显著改善。此外,生态数据为驱动种间和种内分化的非生物因素提供了额外的见解。通过整合跨越基因组(内在)和表型(外在)特征的多条证据线,并纳入物种与其环境之间的相互作用,可以更有信心地划定物种界限。因此,通过不同数据集的相互印证,可以建立一个定义明确的物种,从而确保一个更严谨、更全面的分类框架。