Species are fundamental to biology, conservation, and environmental legislation; yet, there is often disagreement on how and where species limits should be drawn. Even sophisticated molecular methods have limitations, particularly in the context of geographically isolated lineages or inadequate sampling of loci. With extinction rates rising, methods are needed to assess species limits rapidly but robustly. Tobias et al. devised a points-based system to compare phenotypic divergence between taxa against the level of divergence in sympatric species, establishing a threshold to guide taxonomic assessments at a global scale. The method has received a mixed reception. To evaluate its performance, we identified 397 novel taxonomic splits from 328 parent taxa made by application of the criteria (in 2014‒2016) and searched for subsequent publications investigating the same taxa with molecular and/or phenotypic data. Only 71 (18%) novel splits from 60 parent taxa have since been investigated by independent studies, suggesting that publication of splits underpinned by the criteria in 2014–2016 accelerated taxonomic decisions by at least 33 years. In the evaluated cases, independent analyses explicitly or implicitly supported species status in 62 (87.3%) of 71 splits, with the level of support increasing to 97.2% when excluding subsequent studies limited only to molecular data, and reaching 100% when the points-based criteria were applied using recommended sample sizes. Despite the fact that the training set used to calibrate the criteria was heavily weighted toward passerines, splits of passerines and non-passerines received equally strong support from independent research. We conclude that the method provides a useful tool for quantifying phenotypic divergence and fast-tracking robust taxonomic decisions at a global scale.

中文翻译：

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用于评估鸟类物种限制的基于积分的评分系统的性能

物种是生物学、保护和环境立法的基础；然而，对于应该如何以及在何处划定物种限制，经常存在分歧。即使是复杂的分子方法也有局限性，特别是在地理上孤立的谱系或基因座采样不足的情况下。随着灭绝率的上升，需要快速但稳健地评估物种限制的方法。托比亚斯等人。设计了一个基于点的系统来比较分类群之间的表型差异与同域物种的差异水平，建立一个阈值来指导全球范围内的分类评估。该方法收到了褒贬不一的评价。为了评估其性能，我们通过应用该标准（2014-2016 年）从 328 个亲本分类群中确定了 397 个新的分类分裂，并搜索了随后的出版物，该出版物使用分子和/或表型数据调查了相同的分类群。此后，独立研究对来自 60 个父类群的 71 个（18%）新分裂进行了调查，这表明 2014-2016 年以标准为基础的分裂的公布将分类决策加速了至少 33 年。在评估的案例中，独立分析明确或隐含地支持了 71 个拆分中的 62 个（87.3%）的物种状态，当排除仅限于分子数据的后续研究时，支持水平增加到 97.2%，当点-使用推荐的样本量应用了基于标准的标准。尽管用于校准标准的训练集在很大程度上偏重于雀形目，但雀形目和非雀形目的划分同样得到了独立研究的大力支持。我们得出结论，该方法为量化表型差异和在全球范围内快速跟踪稳健的分类决策提供了有用的工具。