A cautionary note on: A cautionary note on the use of Ornstein-Uhlenbeck models in macroevolutionary studies
Data files
Jul 07, 2023 version files 18.17 KB
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README_file.txt
2.59 KB
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Table_S1.xlsx
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Jul 06, 2023 version files 20.51 KB
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README_file.txt
2.59 KB
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README.md
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Table_S1.xlsx
15.58 KB
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.
README: Supplementary Material associated with Grabowski et al. (2023) - A Cautionary Note on “A Cautionary Note on the Use of Ornstein Uhlenbeck Models in Macroevolutionary Studies”
Description of the data and file structure
- Table S1.xlsx - Table S1: Results of individual simulation runs summarized in Table 1 given a phylogeny with 25 tips with a relative extinction rate (d/b) of 0.75. Runs in bold are those where the Ornstein-Uhlenbeck (OU) model is preferred over the Brownian-motion (BM) model. Iteration 1 shows result for run below rejection threshold and the likelihood surface is shown in Fig. 1a. For each iteration, results show the unscaled tree height (Original TH), the rate of adaptation (⍺) and ⍺ reparametrized as the phylogenetic half-life (t1/2) from the R Package motmot (Thomas and Freckleton, 2012) in units of tree height (=1 here), the components of the "Rejection Rate" of Cooper et al. (2016) including the difference in log-likelihood of the OU model and log-likelihood of the BM model (logL OU - logL BM), and if that difference exceeds the likelihood ratio as in Cooper et al. (2016). Individual runs that were rejected were inspected using the Replicate Index column. All runs were also inspected using SLOUCH and here we show the phylogenetic half-life (t1/2) in units of tree height (=1 here) with 2-unit support interval shown in brackets. Also shown in the "Uncertain Inference Test" column - whether the half-life > 1 (BM), if the half-life < 1 and the upper limit of the 2-unit support surface is <1 (OU), if the best estimate of the half-life <1 but the 2-unit support surface from SLOUCH includes infinity (Includes BM), or if the best estimate of the half-life is <1 and the upper limit of the 2-unit support surface falls between 1 and 3 (Uncertain).
Uploaded to Zenodo
- Grabowski et al Supp Text S1.docx - Supplementary Text S1 referred to in the article - Simulation of dataset including measurement error and results of correcting for this error for various tree sizes.
Dataset citation:
Mark Grabowski and others, A Cautionary Note on “A Cautionary Note on the Use of Ornstein Uhlenbeck Models in Macroevolutionary Studies”, Systematic Biology, 2023;, syad012, https://doi.org/10.1093/sysbio/syad012
Methods
Data was simulated in R with known parameter values and analyzed using the R packages motmot, Slouch, and phylolm.
Usage notes
Microsoft Word and Microsoft Excel but Google Docs and Google Sheets can be used.