Department of Comparative Plant and Fungal Biology, Royal Botanic Gardens Kew, Richmond, London TW9 3AE, UK.
Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, UK.
Syst Biol. 2021 Oct 13;70(6):1181-1199. doi: 10.1093/sysbio/syab021.
Phylogenies are increasingly being used as a basis to provide insight into macroevolutionary history. Here, we use simulation experiments and empirical analyses to evaluate methods that use phylogenies as a basis to make estimates of divergence times and rates of diversification. This is the first study to present a comprehensive assessment of the key variables that underpin analyses in this field-including substitution rates, speciation rates, and extinction, plus character sampling and taxon sampling. We show that in unrealistically simplistic cases (where substitution rates and speciation rates are constant, and where there is no extinction), increased character and taxon sampling lead to more accurate and precise parameter estimates. By contrast, in more complex but realistic cases (where substitution rates, speciation rates, and extinction rates vary), gains in accuracy and precision from increased character and taxon sampling are far more limited. The lack of accuracy and precision even occurs when using methods that are designed to account for more complex cases, such as relaxed clocks, fossil calibrations, and models that allow speciation rates and extinction rates to vary. The problem also persists when analyzing genomic scale data sets. These results suggest two interrelated problems that occur when the processes that generated the data are more complex. First, methodological assumptions are more likely to be violated. Second, limitations in the information content of the data become more important.[Divergence time estimation; diversification rates; macroevolution; phylogeny.].
系统发育越来越多地被用作提供宏观进化历史见解的基础。在这里，我们使用模拟实验和实证分析来评估使用系统发育作为基础来估计分歧时间和多样化率的方法。这是第一项对支持该领域分析的关键变量进行综合评估的研究，包括替代率、物种形成率和灭绝率，以及特征采样和分类群采样。我们表明，在不切实际的简单情况下（替代率和物种形成率恒定，且没有灭绝），增加特征和分类群采样会导致更准确和精确的参数估计。相比之下，在更复杂但现实的情况下（替代率、物种形成率和灭绝率变化），增加特征和分类群采样所带来的准确性和精确性的提高要有限得多。即使使用旨在解决更复杂情况的方法（如松弛时钟、化石校准和允许物种形成率和灭绝率变化的模型），也会出现缺乏准确性和精确性的情况。当分析基因组规模的数据集时，这个问题仍然存在。这些结果表明，当产生数据的过程更加复杂时，会出现两个相互关联的问题。首先，方法假设更有可能被违反。其次，数据信息含量的局限性变得更加重要。[分歧时间估计；多样化率；宏观进化；系统发育。]
