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Phylogenies, the Comparative Method, and the Conflation of Tempo and Mode Antigoni Kaliontzopoulou CIBIO/Inbio, Vairão, Portugal

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Phylogenies, the Comparative Method, and the Conflation of Tempo and Mode Antigoni Kaliontzopoulou CIBIO/Inbio, Vairão, Portugal Ecology, Evolution and Organismal Biology Ecology, Evolution and Organismal Biology Publications 1-2016 Phylogenies, the Comparative Method, and the Conflation of Tempo and Mode Antigoni Kaliontzopoulou CIBIO/InBio, Vairão, Portugal Dean C. Adams Iowa State University, [email protected] Follow this and additional works at: http://lib.dr.iastate.edu/eeob_ag_pubs Part of the Evolution Commons, and the Statistical Models Commons The ompc lete bibliographic information for this item can be found at http://lib.dr.iastate.edu/ eeob_ag_pubs/208. For information on how to cite this item, please visit http://lib.dr.iastate.edu/ howtocite.html. This Article is brought to you for free and open access by the Ecology, Evolution and Organismal Biology at Iowa State University Digital Repository. It has been accepted for inclusion in Ecology, Evolution and Organismal Biology Publications by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Page 1 of 52 Systematic Biology 1 2 3 1 Running head: CONFLATION OF TEMPO AND MODE 4 5 6 7 2 8 9 10 3 Phylogenies, the Comparative Method, and the Conflation of Tempo and Mode 11 12 13 4 14 15 *,1,2 2,3 16 5 ANTIGONI KALIONTZOPOULOU AND DEAN C. ADAMS 17 18 19 20 6 21 22 1 23 7 CIBIO/InBio, Centro de Investigação em Biodiversidade e Recursos Genéticos, Campus 24 25 8 Agrario de Vairão, 4485-661 Vairão, Portugal 26 27 28 9 2 Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa 29 30 31 10 50011, USA 32 33 3 34 11 Department of Statistics, Iowa State University, Ames, Iowa 50011, USA 35 36 37 12 *Correspondence to be sent to: CIBIO/InBio, Centro de Investigação em Biodiversidade e 38 39 40 13 Recursos Genéticos, Campus Agrario de Vairão, 4485-661 Vairão, Portugal; Email: 41 42 14 [email protected] 43 44 45 15 46 47 48 49 50 51 This is a pre-copyedited, author-produced version of an article accepted for publication in 52 Systematic Biology following peer review. The version of record Antigoni Kaliontzopoulou, 53 Dean C. Adams; Phylogenies, the Comparative Method, and the Conflation of Tempo and 54 Mode. Syst Biol 2016; 65 (1): 1-15 is available online at doi: 10.1093/sysbio/syv079 55 56 57 58 59 60 1 http://mc.manuscriptcentral.com/systbiol Systematic Biology Page 2 of 52 1 2 3 16 Abstract 4 5 6 7 17 The comparison of mathematical models that represent alternative hypotheses about the tempo 8 9 18 and mode of evolutionary change is a common approach for assessing the evolutionary processes 10 11 19 underlying phenotypic diversification. However, because model parameters are estimated 12 13 14 20 simultaneously, they are inextricably linked, such that changes in tempo, the pace of evolution, 15 16 21 and mode, the manner in which evolution occurs, may be difficult to assess separately. This may 17 18 22 potentially complicate biological interpretation, but the extent to which this occurs has not yet 19 20 21 23 been determined. In this study, we examined 160 phylogeny × trait empirical datasets, and 22 23 24 conducted extensive numerical phylogenetic simulations, to investigate the efficacy of 24 25 26 25 phylogenetic comparative methods to distinguish between models that represent different 27 28 26 evolutionary processes in a phylogenetic context. We observed that, in some circumstances, a 29 30 27 high uncertainty exists when attempting to distinguish between alternative evolutionary scenarios 31 32 33 28 underlying phenotypic variation. When examining datasets simulated under known conditions, 34 35 29 we found that evolutionary inference is straightforward when phenotypic patterns are generated 36 37 30 by simple evolutionary processes that are represented by modifying a single model parameter at 38 39 40 31 a time. However, inferring the exact nature of the evolutionary process that has yielded 41 42 32 phenotypic variation when facing complex, potentially more realistic, mechanisms is more 43 44 problematic. A detailed investigation of the influence of different model parameters showed that 45 33 46 47 34 changes in evolutionary rates, marked changes in phylogenetic means, or the existence of a 48 49 35 strong selective pull on the data, are all readily recovered by phenotypic model comparison. 50 51 52 36 However, under evolutionary processes with a milder restraining pull acting on trait values, 53 54 37 alternative models representing very different evolutionary processes may exhibit similar 55 56 38 goodness-of-fit to the data, potentially leading to the conflation of interpretations that emphasize 57 58 59 60 2 http://mc.manuscriptcentral.com/systbiol Page 3 of 52 Systematic Biology 1 2 3 39 tempo and mode during empirical evolutionary inference. This is a mathematical and conceptual 4 5 6 40 property of the considered models that, while not prohibitive for studying phenotypic evolution, 7 8 41 should be taken into account and addressed when appropriate. 9 10 11 42 12 13 14 15 43 Keywords: phylogeny, comparative method, tempo, mode, phenotypic evolution, model fit 16 17 18 44 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 3 http://mc.manuscriptcentral.com/systbiol Systematic Biology Page 4 of 52 1 2 3 45 The phylogenetic comparative method, where species trait values are examined in light of 4 5 6 46 the phylogeny of the group to infer the evolutionary processes that have shaped phenotypic 7 8 47 diversity, is a major framework in evolutionary biology (Harvey and Pagel 1991). In recent 9 10 11 48 years, remarkable advances have been made by the development of new tools for investigating 12 13 49 macroevolutionary phenotypic patterns and testing hypothesis about the biological mechanisms 14 15 50 that shape them. Rooted in the approaches of phylogenetic independent contrasts (Felsenstein 16 17 18 51 1985, 1988) and phylogenetic generalized least squares (PGLS: Grafen 1989; Rohlf 2001), 19 20 52 numerous methods have been developed to investigate how phenotypes diversify over 21 22 53 evolutionary time. Testing for diversifying selection and adaptation (Butler and King 2004) or 23 24 25 54 for adaptive radiation (Harvey and Rambaut 2000; Glor 2010; Harmon et al. 2010); 26 27 55 understanding whether morphological disparity is coupled to cladogenesis (Harmon et al. 2003; 28 29 56 Ricklefs 2004; Rabosky and Adams 2012) or species diversification (Bokma 2002; Adams et al. 30 31 32 57 2009; Rabosky and Adams 2012); identifying phenotypic convergence and parallelism (Harmon 33 34 58 et al. 2005; Stayton 2006; Revell et al. 2007; Adams 2010); and examining the correlation 35 36 37 59 among traits through evolutionary history (Martins and Garland 1991; Pagel 1998; Revell and 38 39 60 Collar 2009) are only some examples of how the study of phenotypic traits on phylogenies have 40 41 61 aided biologists in understanding the processes driving diversification. 42 43 44 Common to all these approaches is the use of mathematical models that aim at 45 62 46 47 63 approximating the tempo and mode of evolutionary change (Simpson 1944; Fitch and Ayala 48 49 64 1994). These models are rooted in similar methods first developed in paleontology to explore 50 51 52 65 how phenotypes evolve. Researchers in this field have long been concerned with evolutionary 53 54 66 tempo and mode, which they study by using data from the fossil record to infer these 55 56 67 evolutionary parameters (Gingerich 1976; Gould and Eldredge 1977; Gould 1980; Fitch and 57 58 59 60 4 http://mc.manuscriptcentral.com/systbiol Page 5 of 52 Systematic Biology 1 2 3 68 Ayala 1994). Paleontological studies were profoundly influenced by the hallmark contribution of 4 5 6 69 George Gaylord Simpson (1944) in which he used the word “tempo” to define the pace at which 7 8 70 phenotypic evolution proceeds. Likewise, he defined “mode” as “…the study of the way, 9 10 11 71 manner, or pattern of evolution, a study in which tempo is a basic factor…” (Simpson, 1944). In 12 13 72 his definitions, Simpson inextricably linked tempo and mode together: the self-contained 14 15 73 description of how fast evolutionary changes occurs (tempo) was a basic component for 16 17 18 74 describing the way in which these changes are attained (mode). Indeed, a recent investigation of 19 20 75 the paleontological methods used to estimate and compare evolutionary rates shows that different 21 22 76 rate metrics perform better depending on the mode of evolution (Hunt, 2012). Thus, in 23 24 25 77 paleontological studies, it is clear that tempo and mode are intimately related and can often not 26 27 78 be accurately characterized independently (Hunt, 2012). This observation raises an important 28 29 79 question: is this also the case when using phylogenetic comparative approaches to assess 30 31 32 80 phenotypic evolution of extant taxa? 33 34 35 81 In modern phylogenetic comparative methods, the tempo and mode of evolution are 36 37 82 approached through mathematical models that describe extant phenotypic variation given a 38 39 40 83 phylogenetic hypothesis for the group of interest. The first breakthrough towards modeling how 41 42 84 continuous phenotypic traits evolve on phylogenies was the introduction of a random-walk 43 44 model (Brownian Motion, BM; Edwards and Cavalli-Sforza 1964; Felsenstein 1973, 1985, 1988; 45 85 46 47 86 Harvey and Pagel 1991). Under BM, phenotypic variation accumulates linearly over time and the 48 49 87 amount of change in the value of a phenotypic trait (X) over a small time interval (t) can be 50 51 52 88 modeled as: 53 54 89 (1) 55 ͒͘ʚͨʛ = ̼͘ʚͨʛ 56 57 58 59 60 5 http://mc.manuscriptcentral.com/systbiol Systematic Biology Page 6 of 52 1 2 3 90 In equation (1), dB(t) represents independent, normally distributed, random perturbations 4 5 6 91 and σ is the evolutionary rate or variance.
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