Data from: Delimiting species using single-locus data and the Generalized Mixed Yule Coalescent approach: a revised method and evaluation on simulated data sets

DNA barcoding-type studies assemble single-locus data from large samples of individuals and species, and have provided new kinds of data for evolutionary surveys of diversity. An important goal of many such studies is to delimit evolutionarily significant species units, especially in biodiversity surveys from environmental DNA samples. The Generalized Mixed Yule Coalescent (GMYC) method is a likelihood method for delimiting species by fitting within- and between-species branching models to reconstructed gene trees. Although the method has been widely used, it has not previously been described in detail or evaluated fully against simulations of alternative scenarios of true patterns of population variation and divergence between species. Here, we present important reformulations to the GMYC method as originally specified, and demonstrate its robustness to a range of departures from its simplifying assumptions. The main factor affecting the accuracy of delimitation is the mean population size of species relative to divergence times between them. Other departures from the model assumptions, such as varying population sizes among species, alternative scenarios for speciation and extinction, and population growth or subdivision within species, have relatively smaller effects. Our simulations demonstrate that support measures derived from the likelihood function provide a robust indication of when the model performs well and when it leads to inaccurate delimitations. Finally, the so-called single-threshold version of the method outperforms the multiple-threshold version of the method on simulated data: we argue that this might represent a fundamental limit due to the nature of evidence used to delimit species in this approach. Together with other studies comparing its performance relative to other methods, our findings support the robustness of GMYC as a tool for delimiting species when only single-locus information is available.

DNA条形码（DNA barcoding）类研究从大量个体与物种样本中组装单基因座数据，为生物多样性的进化调查提供了全新的数据类型。此类研究的一项重要目标是界定进化上具有显著意义的物种单元，尤其在基于环境DNA（environmental DNA）样本的生物多样性调查中。广义混合尤尔溯祖模型（Generalized Mixed Yule Coalescent, GMYC）是一种通过将物种内和物种间的分支模型拟合至重构的基因树，从而实现物种界定的似然法。尽管该方法已被广泛应用，但此前尚未对其进行详细阐述，也未完全针对种群变异和物种间分化的真实模式的各类模拟场景开展全面评估。本文对最初设定的GMYC方法进行了重要的修正与重构，并验证了其在一系列违背其简化假设情形下的稳健性。影响物种界定准确性的主要因素为物种平均种群规模与物种间分化时间的相对大小。其他违背模型假设的情形，例如不同物种间种群规模存在差异、物种形成与灭绝的不同演化场景、物种内的种群增长或细分，其影响相对较小。我们的模拟实验表明，源自似然函数的支持度指标可可靠地指示模型的表现优劣，以及何时会出现不准确的物种界定结果。最后，相较于多阈值版本，该方法的所谓单阈值版本在模拟数据集上的表现更优；我们认为，这或许是由于该方法中用于界定物种的证据本质所带来的根本性局限。结合其他对比该方法与其他方法性能的相关研究，本文的研究结果证实了GMYC作为仅依靠单基因座信息开展物种界定工具的稳健性。