Phylogenetic comparative analysis: a modeling approach for adaptive evolution

Multioptima OU models have been widely used to test for shifts in evolutionary regimes.

“Multioptima OU models have been widely used to test for the presence of shifts in evolutionary regimes (i.e., parts of the phylogeny with their own optima, or less commonly, their own strength of selection parameters).”

Most continuous trait models are Gaussian and do not accommodate abrupt, discontinuous shifts in phenotypes.

“While today we have a much wider range of comparative models to choose from including some that allow for adaptive shifts, most continuous trait models are Gaussian (e.g., Pagel 1999;Blomberg et al. 2003;Butler and King 2004;O'Meara et al. 2006;Eastman et al. 2011;Beaulieu et al. 2012;Uyeda and Harmon 2014) and do not accommodate abrupt, discontinuous shifts in phenotypes.”

Tests of adaptive evolution come in two flavors: those with an a priori hypothesis about which lineages belong to which regimes, and those where the locations of regime changes are estimated along with the parameters of the OU process.

“Tests of adaptive evolution come in two flavors: those with an a priori hypothesis (or hypotheses) regarding which lineages belong to which distinct regimes based on ancestral state reconstruction of explanatory factors (Butler and King 2004;Beaulieu et al. 2012) and those where the locations of regime changes are themselves estimated along with the parameters of the OU process (Ingram and Mahler”

Depending on the Bayesian network structure, the appropriate method of analysis can range from a nonphylogenetic regression, to commonly used comparative methods such as PGLS, to methods that require modeling both the evolutionary history of interaction of both trait X and trait Y.

“Depending on the Bayesian network structure, the appropriate method of analysis can range from a nonphylogenetic regression (Fig. 7A), to commonly used comparative methods such as PGLS (Fig. 7B), to methods that require modeling both the evolutionary history of interaction of both trait X and trait Y (Fig. 7C) (Hansen 1997;Butler and King 2004;Hansen et al. 2008;Revell 2010;Hansen and Bartoszek 20”