The inclusion of fossil phenotypes as ancestral character values at nodes in phylogenetic trees is known to increase both the power and reliability of phylogenetic comparative methods (PCMs) applications. We implemented the R function RRphylo as to integrate fossil phenotypic information as ancestral character values. We tested the new implementation, named RRphylo-noder (which is available as part of the RRphylo R package) on tree and data generated according to evolutionary processes of differing complexity and under variable sampling conditions. We compared RRphylo-noder performance to other available methods for ancestral state estimation, including Bayesian approaches and methods allowing rate variation between the tree branches. We additionally applied RRphylo-noder to two real cases studies, the evolution of body size in baleen whales and in caniform carnivores. Variable-rate methods proved to be more accurate than single-rate methods in estimating ancestral states when the pattern of phenotypic evolution changes across the tree. RRphylo-noder proved to be slightly more accurate and sensibly faster than Bayesian approaches, and the least sensitive to the kind of phenotypic pattern simulated. The use of fossil phenotypes as ancestral character values noticeably increases the probability to find a phenotypic trend through time when it applies to either the entire tree or just to specific clades within it. We found Cope’s rule to apply to both mysticete cetaceans and caniform carnivores. The RRphylo-noder implementation is particularly appropriate to study phenotypic evolution in the presence of complex phenotypes generated by different processes acting in different parts the tree, and when suitable information about fossil phenotypes is at hand. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Ancestral State Estimation with Phylogenetic Ridge Regression / Castiglione, S.; Serio, C.; Mondanaro, A.; Melchionna, M.; Carotenuto, F.; Di, Febbraro; Profico, A.; Tamagnini, D.; Raia, P.. - In: EVOLUTIONARY BIOLOGY. - ISSN 0071-3260. - (2020). [10.1007/s11692-020-09505-x]
Ancestral State Estimation with Phylogenetic Ridge Regression
Castiglione S.;Serio C.;Melchionna M.;Carotenuto F.;Raia P.
2020
Abstract
The inclusion of fossil phenotypes as ancestral character values at nodes in phylogenetic trees is known to increase both the power and reliability of phylogenetic comparative methods (PCMs) applications. We implemented the R function RRphylo as to integrate fossil phenotypic information as ancestral character values. We tested the new implementation, named RRphylo-noder (which is available as part of the RRphylo R package) on tree and data generated according to evolutionary processes of differing complexity and under variable sampling conditions. We compared RRphylo-noder performance to other available methods for ancestral state estimation, including Bayesian approaches and methods allowing rate variation between the tree branches. We additionally applied RRphylo-noder to two real cases studies, the evolution of body size in baleen whales and in caniform carnivores. Variable-rate methods proved to be more accurate than single-rate methods in estimating ancestral states when the pattern of phenotypic evolution changes across the tree. RRphylo-noder proved to be slightly more accurate and sensibly faster than Bayesian approaches, and the least sensitive to the kind of phenotypic pattern simulated. The use of fossil phenotypes as ancestral character values noticeably increases the probability to find a phenotypic trend through time when it applies to either the entire tree or just to specific clades within it. We found Cope’s rule to apply to both mysticete cetaceans and caniform carnivores. The RRphylo-noder implementation is particularly appropriate to study phenotypic evolution in the presence of complex phenotypes generated by different processes acting in different parts the tree, and when suitable information about fossil phenotypes is at hand. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.