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关于《奥恩斯坦-乌伦贝克模型在宏观进化研究中应用的警示》一文的警示说明

A Cautionary Note on "A Cautionary Note on the Use of Ornstein Uhlenbeck Models in Macroevolutionary Studies".

机构信息

Research Centre in Evolutionary Anthropology and Palaeoecology, Liverpool John Moores University, Liverpool, UK.

Department of Biosciences, Centre for Ecological and Evolutionary Synthesis (CEES), University of Oslo, Oslo, Norway.

出版信息

Syst Biol. 2023 Aug 7;72(4):955-963. doi: 10.1093/sysbio/syad012.

Abstract

Models based on the Ornstein-Uhlenbeck process have become standard for the comparative study of adaptation. Cooper et al. (2016) have cast doubt on this practice by claiming statistical problems with fitting Ornstein-Uhlenbeck models to comparative data. Specifically, they claim that statistical tests of Brownian motion may have too high Type I error rates and that such error rates are exacerbated by measurement error. In this note, we argue that these results have little relevance to the estimation of adaptation with Ornstein-Uhlenbeck models for three reasons. First, we point out that Cooper et al. (2016) did not consider the detection of distinct optima (e.g. for different environments), and therefore did not evaluate the standard test for adaptation. Second, we show that consideration of parameter estimates, and not just statistical significance, will usually lead to correct inferences about evolutionary dynamics. Third, we show that bias due to measurement error can be corrected for by standard methods. We conclude that Cooper et al. (2016) have not identified any statistical problems specific to Ornstein-Uhlenbeck models, and that their cautions against their use in comparative analyses are unfounded and misleading. [adaptation, Ornstein-Uhlenbeck model, phylogenetic comparative method.].

摘要

基于 Ornstein-Uhlenbeck 过程的模型已成为比较适应研究的标准。库珀等人(2016 年)通过声称拟合比较数据的 Ornstein-Uhlenbeck 模型存在统计问题,对这种做法提出了质疑。具体来说,他们声称布朗运动的统计检验可能存在过高的第一类错误率,并且这种错误率会因测量误差而加剧。在本注释中,我们认为这些结果与使用 Ornstein-Uhlenbeck 模型估计适应度的关系不大,原因有三。首先,我们指出库珀等人(2016 年)没有考虑到不同的最优值(例如,对于不同的环境),因此没有评估适应度的标准检验。其次,我们表明,通常考虑参数估计而不仅仅是统计显著性,将导致关于进化动态的正确推断。第三,我们表明,测量误差引起的偏差可以通过标准方法进行校正。我们的结论是,库珀等人(2016 年)没有发现任何特定于 Ornstein-Uhlenbeck 模型的统计问题,他们对在比较分析中使用这些模型的警告是没有根据的,并且具有误导性。[适应,Ornstein-Uhlenbeck 模型,系统发生比较方法。]

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e0a/10405355/dec4a7c3122b/syad012_fig1.jpg

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