A Cautionary Note on “A Cautionary Note on the Use of Ornstein Uhlenbeck Models in Macroevolutionary Studies”

Author:

Grabowski Mark12ORCID,Pienaar Jason3,Voje Kjetil L4,Andersson Staffan5,Fuentes-González Jesualdo3,Kopperud Bjørn T67,Moen Daniel S8,Tsuboi Masahito9,Uyeda Josef10,Hansen Thomas F2

Affiliation:

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

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

3. Department of Biological Sciences and the Institutes of Environment, Florida International University Miami , Miami, FL , USA

4. Natural History Museum, University of Oslo , Oslo , Norway

5. Department of Biological and Environmental Sciences, University of Gothenburg , Göteborg , Sweden

6. GeoBio-Center LMU, Ludwig-Maximilians-Universität München , Richard-Wagner Straße 10, 80333 Munich , Germany

7. Department of Earth and Environmental Sciences, Paleontology & Geobiology, Ludwig-Maximilians-Universität München , Richard-Wagner Straße 10, 80333 Munich , Germany

8. Department of Integrative Biology, Oklahoma State University , Stillwater, OK 74078 , USA

9. Department of Biology, Lund University , Lund , Sweden

10. Department of Biological Sciences, Virginia Tech , Blacksburg, VA , USA

Abstract

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.]

Funder

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Genetics,Ecology, Evolution, Behavior and Systematics

Reference54 articles.

1. Retire statistical significance;Amrhein;Nature,2019

2. Model selection performance in phylogenetic comparative methods under multivariate Ornstein-Uhlenbeck models of trait evolution;Bartoszek;Syst. Biol,2022

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4. Inference of adaptive shifts for multivariate correlated traits;Bastide;Syst. Biol,2018

5. Modeling stabilizing selection: expanding the Ornstein-Uhlenbeck model of adaptive evolution;Beaulieu;Evolution,2012

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