To celebrate our 10th Anniversary, we are highlighting a key article from each of our volumes. For Volume 8, we selected ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data by Yu et al. (2016).

In this post, our Associate Editors Samantha Price and Francisco Balao share their favourite MEE papers in the field of phylogenetics.

Samantha Price, Clemson University USA

It is such a difficult task to pick just a few studies on phylogenies and their use in comparative evolutionary and ecological analyses to highlight, as MEE has published so many that have had a significant impact on our field. As an Applications editor I feel I must acknowledge several important R packages that have made our analytical pipelines richer and our lives easier. I doubt few, if any, researchers have conducted phylogenetic comparative analyses recently without at least using one function in the perennially useful PHYTOOLS (Revell 2012). Analyses of lineage diversification have been facilitated by DIVERSITREE (FitzJohn 2012), which enabled many studies into trait-dependent diversification, and RPANDA (Morlon et al. 2016), which allowed model-free analysis of phylogenetic trees using their Laplacian spectrum.

The analysis of multivariate trait data was catalyzed by SURFACE (Ingram & Mahler 2013), which permitted researchers to identify potential phenotypic convergence, and MvMORPH (Clavel 2015), which provided many handy functions for analyzing multivariate data in a phylogenetic framework. Looking to the future, I am excited to see the impact that the tools provided in the recently published PHYR (Li et al. 2020), will have on the ongoing integration of phylogenetic and community ecology data. Other valuable papers have improved the ‘best practices’ of our field, either by making it easier to implement the correct procedures, such the R package SENSIPHY (Paterno et al. 2018), which simplified the execution of sensitivity analyses in phylogenetic comparative method, or by demonstrating methodological limitations. My personal favorite is Ho & Ane (2014), who carefully detailed the challenges of investigating trait evolution using Ornstein-Uhlenbeck models and then provided much needed recommendations to help empiricists like me!

Francisco Balao, University of Seville

Visualizing trees is an important task in evolutionary biology to assist in drawing conclusions from phylogenetic methods. The featured article for this Methods in Ecology and Evolution volume, Yu et al. 2017, introduce the ggtree R package which allows the integration of data from different sources embedded within phylogenetic tree views. ggtree is an excellent companion tool for phylogenetic comparative methods (PCM) in which a phylogeny is often combined with phenotypic data for the species in a phylogenetic tree to test hypotheses about macroevolution.

Two of my favourite related MEE papers adding new methods of analyses and visualization on PCM are Revell (2012) and Revell (2013). The phytools R package (Revell, 2012) makes available most of the current phylogenetic comparative methods within the R environment. This article describes, through two examples, several methods in PCM implemented in phytools, including ancestral character reconstruction, likelihood- and Bayesian-based methods for trait evolution, trait-evolution simulation and different graph methods.

One of these graph methods is the projection of a phylogenetic tree into bivariate morphospace, which improves the visualization of trait evolution. In addition, Revell (2013) develops two new creative methods for visualization. The densityMap allows visualizing the aggregate result of stochastic binary trait mapping translating the trait state probability to colours on the phylogeny branches. The second graph method (traitgram) uses ancestral character estimation to visualize historical character states (and its uncertainty) for a continuous trait along the branches of a phylogenetic tree. However, all these graph methods are not just useful for visualization purposes; they should also be used as complement of statistical tests to check for spurious results (Revel et al. 2018).

Lastly, I recommend the reading of the most recent paper from Gaboriau et al. (2020), which introduces new tools (the BITE R package) to study the dynamics of intraspecific phenotypic variation at the macroevolutionary scale. This R package implements the JIVE model (Joint Inter and intraspecific Variance Evolution), a hierarchical Bayesian framework to jointly estimate the evolutionary rates for both the means and variances of phenotypic traits. Gaboriau et al. also implement the JIVE model in the renowned BEAST2 framework. Unquestionably, Methods in Ecology and Evolution is an excellent journal to look to for fresh ideas on phylogenetic comparative methods and visualization tools.

Read about the article selected to highlight Volume 8: ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data

Find out more about the MEE papers selected to celebrate the other volumes, and our editors’ favourite related articles in this collection of 10th Anniversary blog posts