Data from: The species versus subspecies conundrum: quantitative delimitation from integrating multiple data types within a single Bayesian approach in Hercules beetles

With the recent attention and focus on quantitative methods for species delimitation, an overlooked but equally important issue regards what has actually been delimited. This study investigates the apparent arbitrariness of some taxonomic distinctions, and in particular how species and subspecies are assigned. Specifically, we use a recently developed Bayesian model-based approach to show that in the Hercules beetles (genus Dynastes) there is no statistical difference in the probability that putative taxa represent different species, irrespective of whether they were given species or subspecies designations. By considering multiple data types, as opposed to relying exclusively on genetic data alone, we also show that both previously recognized species and subspecies represent a variety of points along the speciation spectrum (i.e., previously recognized species are not systematically further along the continuum than subspecies). For example, based on evolutionary models of divergence, some taxa are statistically distinguishable on more than one axis of differentiation (e.g., along both phenotypic and genetic dimensions), whereas other taxa can only be delimited statistically from a single data type. Because both phenotypic and genetic data are analyzed in a common Bayesian framework, our study provides a framework for investigating whether disagreements in species boundaries among data types reflect (i) actual discordance with the actual history of lineage splitting, or instead (ii) differences among data types in the amount of time required for differentiation to become apparent among the delimited taxa. We discuss what the answers to these questions imply about what characters are used to delimit species, as well as the diverse processes involved in the origin and maintenance of species boundaries. With this in mind, we then reflect more generally on how quantitative methods for species delimitation are used to assign taxonomic status.当前学界对物种界定的定量方法给予了高度关注，但有一个常被忽视却同等重要的问题，即我们实际界定的究竟是什么。本研究聚焦于部分分类学区分看似存在的任意性，尤其是物种与亚种的指派逻辑。具体而言，我们借助新近开发的基于贝叶斯模型的分析方法，针对犀金龟属（Dynastes）展开研究，结果显示：无论假定类群被赋予物种还是亚种的分类地位，其作为独立物种的概率均不存在统计学差异。相较于仅依赖遗传数据，我们纳入多类数据进行分析后进一步发现：已被识别的物种与亚种均处于物种形成连续体的不同节点上（即已认定的物种并未系统性地比亚种更靠近物种形成连续体的末端）。举例而言，基于分化演化模型，部分类群可在多个分化维度（如表型与遗传维度）上实现统计学区分，而另一些类群则仅能通过单一类数据实现统计学界定。由于我们在统一贝叶斯框架下同时分析了表型与遗传数据，本研究为探究不同数据间的物种边界分歧原因提供了分析框架：这些分歧要么反映了与实际谱系分化历史的真实不一致，要么源于不同数据在类群分化显现所需时长上存在差异。我们还讨论了上述问题的答案对于界定物种所采用的性状，以及物种边界起源与维持所涉及的多样演化过程的启示。基于上述分析，我们进一步从更宏观的层面反思物种界定的定量方法应如何用于指派分类学地位。