Statistical phylogeography
Statistical phylogeography
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DOI：
10.1046/j.1365-294x.2002.01637.x
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发表时间：
2002-12-01
影响因子：
4.9
通讯作者：
Maddison, WP
中科院分区：
文献类型：
--
作者：
Knowles, LL;Maddison, WP
过去，系统地理学和物种形成的研究在很大程度上侧重于记录或检测种群遗传结构的显著模式，而新兴的统计系统地理学领域旨在推断这种结构背后的历史和过程，并提供客观的而非特别设定的解释。参数估计方法现在通常用于对过去的种群动态进行推断。尽管这些方法在统计学上已经很成熟，但它们通常很少关注地理历史。相比之下，试图重建系统地理历史的方法能够考虑许多不同的地理情景，但主要是非统计学的，在没有明确参考随机得出的预期的情况下对特定的生物过程进行推断。我们主张融合这两种传统，以便统计系统地理学方法能够准确地呈现过去，考虑多种过程，并对那段历史给出统计估计。我们讨论与统计系统地理推断相关的各种概念问题，尤其考虑种群遗传过程的随机性并评估系统地理结论的可信度。为此，我们给出一些运用统计系统地理学方法的实证例子，然后通过对比基于溯祖理论的方法和坦普尔顿的嵌套分支分析（NCA）的结果，我们阐明了评估误差的重要性。因为NCA在其对历史过程或当代基因流的推断中不评估误差，我们使用模拟数据进行了一项小规模研究，以检验我们的结论可能会如何受到这种未被考虑的误差的影响。NCA没有识别出用于模拟数据的过程，混淆了确定性过程和基因谱系的随机分类。目前还没有足够的理由证明NCA能够准确推断或区分不同过程。最后，我们讨论了当前统计系统地理学方法的一些未解决的问题，并提出了需要未来发展的领域。
While studies of phylogeography and speciation in the past have largely focused on the documentation or detection of significant patterns of population genetic structure, the emerging field of statistical phylogeography aims to infer the history and processes underlying that structure, and to provide objective, rather than ad hoc explanations. Methods for parameter estimation are now commonly used to make inferences about demographic past. Although these approaches are well developed statistically, they typically pay little attention to geographical history. In contrast, methods that seek to reconstruct phylogeographic history are able to consider many alternative geographical scenarios, but are primarily nonstatistical, making inferences about particular biological processes without explicit reference to stochastically derived expectations. We advocate the merging of these two traditions so that statistical phylogeographic methods can provide an accurate representation of the past, consider a diverse array of processes, and yet yield a statistical estimate of that history. We discuss various conceptual issues associated with statistical phylogeographic inferences, considering especially the stochasticity of population genetic processes and assessing the confidence of phylogeographic conclusions. To this end, we present some empirical examples that utilize a statistical phylogeographic approach, and then by contrasting results from a coalescent-based approach to those from Templeton's nested cladistic analysis (NCA), we illustrate the importance of assessing error. Because NCA does not assess error in its inferences about historical processes or contemporary gene flow, we performed a small-scale study using simulated data to examine how our conclusions might be affected by such unconsidered errors. NCA did not identify the processes used to simulate the data, confusing among deterministic processes and the stochastic sorting of gene lineages. There is as yet insufficent justification of NCA's ability to accurately infer or distinguish among alternative processes. We close with a discussion of some unresolved problems of current statistical phylogeographic methods to propose areas in need of future development.