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77
GEIGER: investigating evolutionary radiations
"... doi:10.1093/bioinformatics/btm538 ..."
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Phylogenetic approaches in comparative physiology
, 2005
"... Over the past two decades, comparative biological analyses have undergone profound changes with the incorporation of rigorous evolutionary perspectives and phylogenetic information. This change followed in large part from the realization that traditional methods of statistical analysis tacitly assum ..."
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Cited by 67 (7 self)
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Over the past two decades, comparative biological analyses have undergone profound changes with the incorporation of rigorous evolutionary perspectives and phylogenetic information. This change followed in large part from the realization that traditional methods of statistical analysis tacitly assumed independence of all observations, when in fact biological groups such as species are differentially related to each other according to their evolutionary history. New phylogenetically based analytical methods were then rapidly developed, incorporated into ‘the comparative method’, and applied to many physiological, biochemical, morphological and behavioral investigations. We now review the rationale for including phylogenetic information in comparative studies and briefly discuss three methods for doing this (independent contrasts, generalized leastsquares models, Summary and Monte Carlo computer simulations). We discuss when and how to use phylogenetic information in comparative studies and provide several examples in which it has been helpful, or even crucial, to a comparative analysis. We also consider some difficulties with phylogenetically based statistical methods, and of comparative approaches in general, both practical and theoretical. It is our personal opinion that the incorporation of phylogeny information into comparative studies has been highly beneficial, not only because it can improve the reliability of statistical inferences, but also because it continually emphasizes the potential importance of past evolutionary history in determining current form and function.
WithinSpecies Variation and Measurement Error in Phylogenetic Comparative Methods
, 2007
"... Most phylogenetically based statistical methods for the analysis of quantitative or continuously varying phenotypic traits assume that variation within species is absent or at least negligible, which is unrealistic for many traits. Withinspecies variation has several components. Differences among p ..."
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Cited by 38 (2 self)
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Most phylogenetically based statistical methods for the analysis of quantitative or continuously varying phenotypic traits assume that variation within species is absent or at least negligible, which is unrealistic for many traits. Withinspecies variation has several components. Differences among populations of the same species may represent either phylogenetic divergence or direct effects of environmental factors that differ among populations (phenotypic plasticity). Withinpopulation variation also contributes to withinspecies variation and includes sampling variation, instrumentrelated error, low repeatability caused by fluctuations in behavioral or physiological state, variation related to age, sex, season, or time of day, and individual variation within such categories. Here we develop techniques for analyzing phylogenetically correlated data to include withinspecies variation, or “measurement error ” as it is often termed in the statistical literature. We derive methods for (i) univariate analyses, including measurement of “phylogenetic signal, ” (ii) correlation and principal components analysis for multiple traits, (iii) multiple regression, and (iv) inference of “functional relations, ” such as reduced major axis (RMA) regression. The methods are capable of incorporating measurement error that differs for each data point (mean value for a species or population), but they can be modified for special cases in which less is known about measurement error (e.g., when one is willing to assume something about the ratio of measurement error in two traits). We show that failure to incorporate measurement error can lead to both biased and imprecise (unduly uncertain) parameter estimates. Even previous methods that are thought to account for measurement error, such as conventional RMA regression,
Phylogenetic signal and linear regression on species data
 Methods in Ecology and Evolution
, 2010
"... 1. A common procedure in the regression analysis of interspecies data is to first test the independent and dependent variables X and Y for phylogenetic signal, and then use the presence of signal in one or both traits to justify regression analysis using phylogenetic methods such as independent con ..."
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Cited by 26 (1 self)
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1. A common procedure in the regression analysis of interspecies data is to first test the independent and dependent variables X and Y for phylogenetic signal, and then use the presence of signal in one or both traits to justify regression analysis using phylogenetic methods such as independent contrasts or phylogenetic generalized least squares. 2. This is incorrect, because phylogenetic regression assumes that the residual error in the regression model (not in the original traits) is distributed according to a multivariate normal distribution with variances and covariances proportional to the historical relations of the species in the sample. 3. Here, I examine the consequences of justifying and applying the phylogenetic regression incorrectly. I find that when used improperly the phylogenetic regression can have poor statistical performance, even under some circumstances in which the type I error rate of the method is not inflated over its nominal level. 4. I also find, however, that when tests of phylogenetic signal in phylogenetic regression are applied properly, and in particular when phylogenetic signal in the residual error is simultaneously estimated with the regression parameters, the phylogenetic regression outperforms equivalent nonphylogenetic procedures. Keywords: comparative method, interspecific data, least squares, type I error
Resolving the paradox of stasis: Models with stabilizing selection explain evolutionary divergence on all timescales.
 Am Nat
, 2007
"... abstract: We tested the ability of six quantitative genetic models to explain the evolution of phenotypic means using an extensive database compiled by Gingerich. Our approach differs from past efforts in that we use explicit models of evolutionary process, with parameters estimated from contempora ..."
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Cited by 25 (2 self)
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abstract: We tested the ability of six quantitative genetic models to explain the evolution of phenotypic means using an extensive database compiled by Gingerich. Our approach differs from past efforts in that we use explicit models of evolutionary process, with parameters estimated from contemporary populations, to analyze a large sample of divergence data on many different timescales. We show that one quantitative genetic model yields a good fit to data on phenotypic divergence across timescales ranging from a few generations to 10 million generations. The key feature of this model is a fitness optimum that moves within fixed limits. Conversely, a model of neutral evolution, models with a stationary optimum that undergoes Brownian or white noise motion, a model with a moving optimum, and a peak shift model all fail to account for the data on most or all timescales. We discuss our results within the framework of Simpson's concept of adaptive landscapes and zones. Our analysis suggests that the underlying process causing phenotypic stasis is adaptation to an optimum that moves within an adaptive zone with stable boundaries. We discuss the implication of our results for comparative studies and phylogeny inference based on phenotypic characters. Keywords: adaptive landscape, macroevolution, microevolution, phenotypic evolution, quantitative genetic models, comparative methods. The common observation of evolutionary stasis (persis tence of morphospecies over geological time) seems a paradox when juxtaposed with the observation that abundant genetic variation is available for most traits in contemporary populations . The existence of prolonged stasis has been appreciated since *
Phylogenetic Logistic Regression for Binary Dependent Variables
"... Abstract.—We develop statistical methods for phylogenetic logistic regression in which the dependent variable is binary (0 or 1) and values are nonindependent among species, with phylogenetically related species tending to have the same value of the dependent variable. The methods are based on an ev ..."
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Cited by 13 (1 self)
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Abstract.—We develop statistical methods for phylogenetic logistic regression in which the dependent variable is binary (0 or 1) and values are nonindependent among species, with phylogenetically related species tending to have the same value of the dependent variable. The methods are based on an evolutionary model of binary traits in which trait values switch between 0 and 1 as species evolve up a phylogenetic tree. The more frequently the trait values switch (i.e., the higher the rate of evolution), the more rapidly correlations between trait values for phylogenetically related species break down. Therefore, the statistical methods also give a way to estimate the phylogenetic signal of binary traits. More generally, the methods can be applied with continuous and/or discretevalued independent variables. Using simulations, we assess the statistical properties of the methods, including bias in the estimates of the logistic regression coefficients and the parameter that estimates the strength of phylogenetic signal in the dependent variable. These analyses show that, as with the case for continuousvalued dependent variables, phylogenetic logistic regression should be used rather than standard logistic regression when there is the possibility of phylogenetic correlations among species. Standard logistic regression does not properly account for the loss of information caused by resemblance of relatives and as a result is likely to give inflated type I error rates, incorrectly identifying regression parameters as statistically significantly different from zero when they are not.
ANALYSIS OF COMPARATIVE DATA WITH HIERARCHICAL AUTOCORRELATION
, 2008
"... The asymptotic behavior of estimates and information criteria in linear models are studied in the context of hierarchically correlated sampling units. The work is motivated by biological data collected on species where autocorrelation is based on the species ’ genealogical tree. Hierarchical autocor ..."
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Cited by 10 (0 self)
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The asymptotic behavior of estimates and information criteria in linear models are studied in the context of hierarchically correlated sampling units. The work is motivated by biological data collected on species where autocorrelation is based on the species ’ genealogical tree. Hierarchical autocorrelation is also found in many other kinds of data, such as from microarray experiments or human languages. Similar correlation also arises in ANOVA models with nested effects. I show that the best linear unbiased estimators are almost surely convergent but may not be consistent for some parameters such as the intercept and lineage effects, in the context of Brownian motion evolution on the genealogical tree. For the purpose of model selection I show that the usual BIC does not provide an appropriate approximation to the posterior probability of a model. To correct for this, an effective sample size is introduced for parameters that are inconsistently estimated. For biological studies, this work implies that treeaware sampling design is desirable; adding more sampling units may not help ancestral reconstruction and only strong lineage effects may be detected with high power.
Is there room for punctuated equilibrium in macroevolution? Trends in Ecology and Evolution Http://dx.doi.org/10.1016/j.tree.2013.07.004
, 2013
"... The longcontroversial theory of punctuated equilibrium (PE) asserts that speciation causes rapid evolution against a backdrop of stasis. PE is currently undergoing a resurgence driven by new developments in statistical methods. However, we argue that PE is actually a tangle of four unnecessarily c ..."
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Cited by 6 (2 self)
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The longcontroversial theory of punctuated equilibrium (PE) asserts that speciation causes rapid evolution against a backdrop of stasis. PE is currently undergoing a resurgence driven by new developments in statistical methods. However, we argue that PE is actually a tangle of four unnecessarily conflated questions: (i) is evolution gradualistic or pulsed? (ii) does trait evolution occur mainly at speciation or within a lineage? (iii) are changes at speciation adaptive or neutral? and (iv) how important is species selection in shaping patterns of diversity? We discuss progress towards answering these four questions but argue that combining these conceptually distinct ideas under the single framework of PE is distracting and confusing, and more likely to hinder progress than to spur it. The resurgence of punctuated equilibrium The following three quotations were all drawn from abstracts of recent papers purporting to use statistical models to empirically evaluate punctuated equilibrium (PE): 'A longstanding debate in evolutionary biology concerns whether species diverge gradually through time or by punctuational episodes at the time of speciation. We found that approximately 22% of substitutional changes at the DNA level can be attributed to punctuational evolution, and the remainder accumulates from background gradual divergence' 'This controversy, widely known as the 'punctuated equilibrium' debate, remained unresolved, largely owing to the difficulty of distinguishing biological species from fossil remains. We analyzed body masses of 2143 existing mammal species on a phylogeny comprising 4510 (i.e., nearly all) extant species to estimate rates of gradual (anagenetic) and speciational (cladogenetic) evolution' ([2], p. 2195). 'Under such processes, observations at the tips of a phylogenetic 40 tree have a multivariate Gaussian distribution, which may lead to suboptimal model specification under certain evolutionary conditions, as supposed in models of punctuated equilibrium or adaptive radiation' ([3], p. 193). These three papers are representative of a substantial number of other recent highprofile studies that have discussed their findings in the context of PE 01695347/$ see front matter ß
Rates of phenotypic evolution of ecological characters and sexual
"... traits during the Tanganyikan cichlid adaptive radiation ..."
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Cited by 4 (1 self)
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traits during the Tanganyikan cichlid adaptive radiation
Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution. Systematic Biology 63:293–308
, 2014
"... Abstract.—A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade’s history and subsequently slowdown in rate as niches become saturated—a socalled “Early Burst.” Although a common pattern in the fossil record, evidence for ..."
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Cited by 4 (1 self)
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Abstract.—A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade’s history and subsequently slowdown in rate as niches become saturated—a socalled “Early Burst.” Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst—the rate at which phenotypic evolution declines—is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows