On Comparing Comparative Methods

Gittleman, John L.; Luh, Hang‐Kwang

doi:10.1146/annurev.es.23.110192.002123

Cited by 149 publications

(66 citation statements)

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“…The impact of common ancestry is removed by considering only the variation across the daughter lineages at each internal node in a phylogeny (figure 2), summarized for each trait of interest as a form of weighted mean called a linear contrast ( [34,43]; for worked examples, see also [28,44]). To reveal the evolutionary relationship between traits, independent contrasts in one trait are regressed against the corresponding contrasts in another trait for the (4).…”

Section: Coping With Phylogenetic Non-independence In Cross-species Cmentioning

confidence: 99%

“…Methods have been developed that allow uncertainty in the topology of the working phylogeny to be incorporated into comparative analyses, either by repeating the analysis on a set of trees generated by bootstrapping [61] or by using Bayesian methods [62]. Assuming that the working phylogeny is accurate, calculation of appropriate contrasts will then depend on the fit between real evolutionary processes and the assumptions of the evolutionary model [37,44,51,52,63,64]. Again assuming that the working phylogeny is accurate, it is possible to quantify the extent to which trait values are phylogenetically correlated, and so assess whether phylogenetic non-independence needs to be controlled for [37,64 -67].…”

Section: Coping With Phylogenetic Non-independence In Cross-species Cmentioning

confidence: 99%

“…Fitting of the autoregression model requires estimation of r and a by maximum likelihood (for example, using the software COMPARE [72]). Evolutionary correlations between traits can be estimated by fitting separate autoregression models for each trait, and testing the correlation between the specific components of each trait using standard statistical approaches (see [44] for a worked example). See main text for potential drawbacks of this approach.…”

Section: Coping With Phylogenetic Non-independence In Cross-species Cmentioning

confidence: 99%

“…Autoregression approaches are, however, less sensitive than PIC methods to errors in identifying the relationships between taxa [44,48,56]. This is important because although contrast/GLS methods can perform better than autocorrelation approaches when the working phylogeny is estimated accurately [48], the performance of contrast-based methods falls substantially when the working phylogeny is significantly wrong [44,48,56]. This is a potential advantage of autocorrelation approaches when the precise relationships linking taxa being compared are either hard to estimate or not tree-like at all [39,70] (see below).…”

Section: Coping With Phylogenetic Non-independence In Cross-species Cmentioning

confidence: 99%

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Controlling for non-independence in comparative analysis of patterns across populations within species

Stone¹,

Nee²,

Felsenstein

2011

Phil. Trans. R. Soc. B

135

127

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How do we quantify patterns (such as responses to local selection) sampled across multiple populations within a single species? Key to this question is the extent to which populations within species represent statistically independent data points in our analysis. Comparative analyses across species and higher taxa have long recognized the need to control for the non-independence of species data that arises through patterns of shared common ancestry among them (phylogenetic non-independence), as have quantitative genetic studies of individuals linked by a pedigree. Analyses across populations lacking pedigree information fall in the middle, and not only have to deal with shared common ancestry, but also the impact of exchange of migrants between populations (gene flow). As a result, phenotypes measured in one population are influenced by processes acting on others, and may not be a good guide to either the strength or direction of local selection. Although many studies examine patterns across populations within species, few consider such non-independence. Here, we discuss the sources of non-independence in comparative analysis, and show why the phylogeny-based approaches widely used in cross-species analyses are unlikely to be useful in analyses across populations within species. We outline the approaches (intraspecific contrasts, generalized least squares, generalized linear mixed models and autoregression) that have been used in this context, and explain their specific assumptions. We highlight the power of 'mixed models' in many contexts where problems of non-independence arise, and show that these allow incorporation of both shared common ancestry and gene flow. We suggest what can be done when ideal solutions are inaccessible, highlight the need for incorporation of a wider range of population models in intraspecific comparative methods and call for simulation studies of the error rates associated with alternative approaches.

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Section: Coping With Phylogenetic Non-independence In Cross-species Cmentioning

confidence: 99%

Section: Coping With Phylogenetic Non-independence In Cross-species Cmentioning

confidence: 99%

Section: Coping With Phylogenetic Non-independence In Cross-species Cmentioning

confidence: 99%

Section: Coping With Phylogenetic Non-independence In Cross-species Cmentioning

confidence: 99%

See 2 more Smart Citations

Controlling for non-independence in comparative analysis of patterns across populations within species

Stone¹,

Nee²,

Felsenstein

2011

Phil. Trans. R. Soc. B

135

127

View full text Add to dashboard Cite

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“…A principal implicação desses padrões é que o teste das correlações entre as variáveis torna-se mais complexo, pois é necessário corrigir os efeitos da inércia filogenética. A probabilidade de erro Tipo I (aceitar a correlação quando ela de fato não existe) passa a ser consideravelmente maior nos casos de forte inér-cia filogenética, pois a correlação entre os caracteres pode indicar apenas covariação de ambos com a filogenia (Felsenstein, 1985;Cheverud et al, 1985;Gittleman & Luh, 1992;Martins, 1996).…”

Section: Introductionunclassified

Padrões e processos na evolução do tamanho do corpo em carnívoros (Mammalia) da América do Sul

Diniz‐Filho

Vieira

1998

Rev. Bras. Biol.

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Patterns and processes in body size evolution of south american carnivoresIn the last few years, many models have been proposed to link microevolutionary processes to macroevolutionary patterns, defined by comparative data analysis. Among these, Brownian motion and Ornstein-Uhlenbeck (O-U) processes have been used to model, respectively, genetic drift and stabilizing selection.Since these models produce different curves of pairwise variance between species against time since divergence, different profiles in phylogenetic correlograms must appear. In this paper, we analyzed variation in body weight among 17 species of South American carnivores by means of phylogenetic correlograms, constructed using Moran's I coefficients in four distance classes. Phylogeny among species was based on molecular data.The observed correlogram was then compared with 400 simulated correlograms of Brownian motion and O-U over the same phylogeny. The observed correlogram indicates a phylogenetic gradient up to 8 mya, when coefficients tend to stabilize, and autoregressive model indicates that around 74% of the interspecific variance in body size can be explained by phylogenetic inertia. This is expected by considering that body size is usually correlated with many ecological and lifehistory traits, being subjected to many constraints that can be modeled by O-U process expressing stabilizing selection.Key words: carnivores, body size, phylogeny, autocorrelation, correlograms, stabilizing selection. RESUMONos últimos anos, muitos modelos têm sido propostos a fim de ligar os processos microevolutivos aos padrões macroevolutivos. Dentre estes, o movimento Browniano e o processo Ornstein-Uhlenbeck (O-U) têm sido utilizados, respectivamente, para modelar a evolução de um caráter quantitativo sob efeito de deriva genética e seleção estabilizadora.Uma vez que esses processos produzem curvas diferentes de relação entre variância interespecífica e tempo de divergência, eles podem ser distinguidos através de correlogramas filogenéticos. Neste trabalho, padrões no tamanho do corpo de 17 espécies de Carnívora sul-americanos foram analisados através de correlogramas filogenéticos, construídos com índices I de Moran em quatro classes de distância no tempo.O correlograma observado foi comparado a 400 correlogramas obtidos através de simulações dos dois processos (movimento Browniano e O-U) sobre a filogenia das espécies analisadas (obtida

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References

2000

Pattern and Process in Macroecology

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On Comparing Comparative Methods

Cited by 149 publications

References 70 publications

Controlling for non-independence in comparative analysis of patterns across populations within species

Controlling for non-independence in comparative analysis of patterns across populations within species

Padrões e processos na evolução do tamanho do corpo em carnívoros (Mammalia) da América do Sul

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