The babette R Package: How to Sooth the Phylogenetic BEAST2

Post provided by Richel Bilderbeek

 What is babette?

‘babette‘ is an R package that works with the popular phylogenetic tool BEAST2. BEAST2 uses one or more alignments and a model setup to create a Bayesian posterior of jointly estimated model parameters and phylogenies.

babette lets you call BEAST2 from an R script. This makes it easier to explore models and/or alignments than using the graphical user interface programs that BEAST2 provides. It will also help you to improve the reproducibility of your work with BEAST2.

babette Tutorial Videos

If you’re new to phylogentic analyses, the video ‘babette demo‘ demonstrates the package. It has all of the information that you need to be able to start using the package

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Phylogenies, Trait Evolution and Fancy Glasses

Post provided by Daniel S. Caetano

Phylogenetic trees represent the evolutionary relationships among different lineages. These trees give us two crucial pieces of information:

  1. the relationships between lineages (which we can tell from the pattern of the branches (i.e., topology))
  2. the point when lineages separated from a common ancestor (which we can tell from the length of the branches, when estimated from genetic sequences and fossils).
Phylogeny of insects inferred from genetic sequences showing the time of divergence between ants and bees.

Phylogeny of insects inferred from genetic sequences showing the time of divergence between ants and bees.

As systematic biologists, we are interested in the evolutionary history of life. We use phylogenetic trees to uncover the past, understand the present, and predict the future of biodiversity on the planet. Among the tools for this thrilling job are the comparative methods, a broad set of statistical tools built to help us understand and interpret the tree of life.

Here’s a Tree, Now Tell Me Something

The comparative methods we use to study the evolution of traits are mainly based on the idea that since species share a common evolutionary history, the traits observed on these lineages will share this same history. In the light of phylogenetics, we can always make a good bet about how a species will look if we know how closely related it is to another species or group. Comparative models aim to quantify the likelihood of our bet being right and use the same principle to estimate how fast evolutionary changes accumulate over time. Continue reading

RPANDA: A Time Machine for Evolutionary Biologists

Post provided by HÉLÈNE MORLON

Yesterday saw the start of this year’s annual Evolution meeting and to celebrate Hélène Morlon has written a blog post discussing the amazingly versatile RPANDA package that she is developing with her research group. A description of RPANDA was published in the journal earlier this year and, like all our Applications papers, is freely available to read in full.

If you are attending Evolution, as well as attending the fabulous talks mentioned by Hélène below, do stop by booth 125 to see our BES colleague Simon Hoggart. Simon is the Assistant Editor of Journal of Animal Ecology and would be happy to answer your questions about any of our journals or any of the other work we do here at the BES.

RPANDA: a time machine for evolutionary biologists

Imagine “Doc”, Marty’s friend in Back to the Future, trying to travel back millions of years in an attempt to understand the history of life. Instead of building a time machine from a DeLorean sports car powered by plutonium, he could dig fossils, or more likely, he would use molecular phylogenies.

Molecular phylogenies are family trees of species that can be built from data collected today: the genes (molecules) of present-day species (Fig 1). They are often thought of as trees, in reference to Darwin’s tree of life. The leaves represent the present: species that can be found on Earth today. The branches represent the past: ancestral species, which from time to time split, giving rise to two independent species. The structure of the tree tells us which species descend from which ancestors, and when their divergence happened.

birds_phylog

Fig 1: The phylogenetic tree of all birds (adapted from Jetz et al. 2012). Each bird order is represented by a single bird silloutter and a specific colour (the most abundant order of Passeriformes, for example is represented in dark orange). Each terminal leaf represents a present-day bird species, while internal branches represent the evolutionary relationships among these species.

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Introducing Biodiverse: Phylodiversity Made Easy

Post provided by SHAWN LAFFAN and ANDREW THORNHILL

© Shawn Laffan

© Shawn Laffan

Phylodiversity indices are increasingly used in spatial analyses of biodiversity, driven largely by the increased availability of phylogenetic trees and the tools to analyse them. Such analyses are integral to understanding evolutionary history and deciding where to allocate conservation resources.

Phylogenetic Indices: The Current Favourites

The most commonly used phylogenetic index is Faith’s Phylogenetic Diversity (PD; Faith 1992). PD is the phylogenetic analogue of taxon richness and is expressed as the number of tree units which are found in a sample.

More recently developed phylodiversity indices adapt the calculation of PD by adjusting the branch lengths of a sample using the local lineage range sizes and abundances, for example Phylogenetic Endemism (PE) and Abundance weighted Evolutionary Diversity (AEDt). In PE the length of each branch in a sample is multiplied by the fraction of its total geographic range found in that sample. The AEDt index uses the same general approach, but weights each branch by the fraction of total abundances found in the sample. The weighting process is generic, so one can scale the branch lengths by any relevant factor, for example the threat status (Faith 2015). Continue reading

What method has transformed your field the most, during your career?

In the 4th and final installment of Barb Anderson’s INTECOL 2013 podcasts, she asks a number of delegates: What method has transformed your field the most, during your career?

The answers in this podcast are given by the following people:

  1. Steve Hubbell, University of California, Los Angeles, USA (00.21)
  2. Georgina Mace, University College London, UK (00.44)
  3. Carsten Dormann, University of Freiburg, Germany (01.07)
  4. Continue reading

New Video – SURFACE: Detecting convergence with stepwise AIC

SURFACEIn Methods’ latest video, Travis Ingram gives a brief introduction to the new phylogenetic comparative method SURFACE. This method uses stepwise AIC to fit a series of stabilizing selection models to a phylogenetic tree and trait data, and to quantify the extent of convergent evolution toward the same selective regimes. The tutorial explains how SURFACE works, and then shows an example analysis in R.

You can view the video here, read the accompanying article here, download the R package from CRAN here, and download a tutorial with worked R examples here.

Diversitree video – starring Mr Blueberry and Fairly-Small-Yellow-Bird

Method’s latest video, “Diversitree”, is now available to view on our YouTube channel. In this quirky demonstration, Mr Blueberry and Fairly-Small-Yellow-Bird disagree on how colour affects the diversification of birds. Rich FitzJohn shows them how to
test their hypotheses using the comparative phylogenetic methods
implemented in the R package “diversitree”, recently described in the Methods paper “Diversitree: comparative phylogenetic analyses of diversification in R“. This article is one of Method’s freely available applications, which aim to provide a source of citable descriptions of new methods and techniques in ecology and evolution.

Related:

Volume 3 Issue 1: Now online

It seems that from the number of submissions we receive at the journal, Methods in Ecology and Evolution has filled an important niche. As our editor-in-chief, Rob Freckleton, wrote to introduce our second volume: “those doing science need to be kept up to date on new approaches, and those developing new methods need a place to publish, as well as be supported in getting their methods used”. The journal appears to have done just that: not only have we published some very popular articles (see our recent posts on 2011 top cited papers part 1, part 2 and part 3) but we have also seen a keen interest from our authors in utilising the online extras that we offer to disseminate their work.

As always, in issue 3.1 we cover a very broad range of articles – the scope includes everything from statistics, to ecophysiology and stable isotope methods. The applications of the methods are as varied as reconstructing snow depth surfaces, tracking migratory songbirds, estimating immigration in neutral communities and assessing the effects of watershed and reach characteristics on riverine assemblages. Being the first issue of the year all content is free to access.

One of our big aims is to promote the uptake of methods. On our video and podcast page, we have support for the papers in this issue, including:

Our first Open Access article by Erica Spotswood and colleagues, How safe is mist netting? Evaluating the risk of injury and mortality to birds, attracted a lot media attention. You can read the press coverage for this article on our News and Highlights page.

This issue also contains a free phylogenetic application: MOTMOT, a model of trait macroevolution on trees by Gavin Thomas and Rob Freckleton. Check out our Applications page describing the latest software tools. It’s worth remembering that all Applications are free.

Finally, Mitch Eaton and William Link provided the catchy photograph that make this issue’s front cover. You can read more about the cover on a separate post, available tomorrow!

We hope you enjoy reading this issue!

Methods Digest – November 2009

Here is a round-up of interesting methods and methods-related papers published in the past few weeks. Please do pass on any interesting-looking papers / links and I will include them.

In Heredity Blanya et al. review the use of Drosophila subobscura as a tool in research on the  microevolutionary consequences of climate change.

There are several methods-relevant papers in the latest issue of Evolution: Céline Becquet and Molly Przeworski look at the problem of estimating the mode of speciation, specifically whether speciation occurs with gene flow; Calsbeek & Goodnight criticially examine methods for estimating G-test statistics; Craig White et al. revisit the issue of the scaling of BMR with body size in mammals, and show that the estimate of the scaling coefficient depends on the method.

A really nice paper by FitzJohn et al. has just appeared online in Systematic Biology that deals with the tricky problem of estimating trait-dependent speciation and extinction rates in the face of phylogenetic uncertainty. Another really interesting early online publication is the study by Kress et al. in PNAS who use barcoding methods for the first time to construct a phylogeny for a whole community.

A study by Guoke Chen and colleagues in Journal of Ecology presents an analysis of the factors that might influence detection probability in plant surveys.

In Journal of Applied Ecology Fieborg et al. present an overview of regression modelling of correlated data; Chetkiewicz & Boyce apply resource selection functions to identify conservation corridors;  Lemke et al. revisit the use of fluorescent markers in studying seed dispersal. Satu Ramula and colleages present a comparison of integral projection models and matrix population models, and show that the former perform better with small datasets. On a related note, in Ecological Monographs Mark Rees and Steve Ellner present integral projection models for populations in temporally varying environments.

Thomas Cornulier and colleagues present in Ecology Letters a method for estimating the number of annual breeding attempts, and apply this to look at reasons for the decline of yellowhammers.

In the latest issue of Conservation Letters, Bruce Kendall looks at the use of diffusion approximations in Population Viability Analysis.

In a paper in Oikos Scott Forbes applies investment theory to understand how birds manage risk.

Finally for this month, for matrix population modellers Peter Zuidema et al. introudce in the American Naturalist a new tool for analysing how faster growing individuals contribute to population growth rates.

Methods Digest, October 2009

Here is a round-up of some interesting methods papers published in the past few weeks. If you see any more papers that you would like to see flagged up, leave a comment below or email me.

In PLoS Biology Wayne Getz presents a thoughtful review of the models and modelling approaches that might be useful in predicting the consequences of multiple threats to ecosystems from a food web / ecosystem perspective.

Ecology has several interesting methods papers: Murray Efford and colleagues show how it is possible to use likelihood methods to estimate densities of animals from arrays of passive detectors (such as arrays of microphones). Michael Neubert et al. present a new method for estimating the rate of growth of perturbations in transient dynamics. Jessica Metcalf et al. apply integral projection models to the problem of estimating flux of individuals in tropical forests. And Grosbois et al. demonstrate a new approach for estimating individual survival / mortality rates from mult-population data.

In Conservation Biology Berlund et al. show how Bayesian methods can be used to understand habitat association of trees from presence records and environmental data. Finn et al. compare methods for estimating population size variability with a view to priortising populations that are more risk to extinction from variability. And Christopher Grouios & Lisa Manne ask whether occupancy or abundance data are more useful in predicting population persistence and how this impacts on reserve design.

Ecology Letters has a paper by Paul Murtaugh comparing model selection methods that is likely to be of general interest. Mosser et al argue that density may not be a generally good measure of habitat quality (in terms of food/ resources), particularly if low quality habitat provides a refuge for non-reproductive  individuals.

Finally, in Systematic Biology Sennblad & Lagergren show how probabilistic orthology analysis can be used to overcome some of the problems in identifying orthologous genes and gene products. And there is some debate about the use of barcodes in taxonomy centring on the effects of sampling error on the model used to delimit species.