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


Issue 8.8

Issue 8.10 is now online!

The October issue of Methods is now online!

This double-sized issue contains three Applications articles and two Open Access articles. These five papers are freely available to everyone, no subscription required.

 Phylogenetic TreesThe fields of phylogenetic tree and network inference have advanced independently, with only a few attempts to bridge them. Schliep et al. provide a framework, implemented in R, to transfer information between trees and networks.

 Emon: Studies, surveys and monitoring are often costly, so small investments in preliminary data collection and systematic planning of these activities can help to make best use of resources. To meet recognised needs for accessible tools to plan some aspects of studies, surveys and monitoring, Barry et al. developed the R package emon, which includes routines for study design through power analysis and feature detection.

 Haplostrips: A tool to visualise polymorphisms of a given region of the genome in the form of independently clustered and sorted haplotypes. Haplostrips is a command-line tool written in Python and R, that uses variant call format files as input and generates a heatmap view.

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Issue 8.9

Issue 8.9 is now online!

The September issue of Methods is now online!

This issue contains two Applications articles and three Open Access articles. These five papers are freely available to everyone, no subscription required.

 qfasar: A new R package for diet estimation using quantitative fatty acid signature analysis methods. It also provides functionality to evaluate and potentially improve the performance of a library of prey signature data, compute goodness-of-fit diagnostics, and support simulation-based research.

 biomass: An r package designed to compute both AGB/AGC estimate and its associated uncertainty from forest plot datasets, using a Bayesian inference procedure. The package builds upon previous work on pantropical and regional biomass allometric equations and published datasets by default, but it can also integrate unpublished or complementary datasets in many steps.

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Issue 8.8

Issue 8.8 is now online!

The August issue of Methods is now online!

This issue contains two Applications articles and two Open Access articles. These four papers are freely available to everyone, no subscription required.

 Paco: An R package that assesses the phylogenetic congruence, or evolutionary dependence, of two groups of interacting species using both ecological interaction networks and their phylogenetic history.

 Open MEE: Open Meta-analyst for Ecology and Evolution (Open MEE) addresses the need for advanced, easy-to-use software for meta-analysis and meta-regression.It offers a suite of advanced meta-analysis and meta-regression methods for synthesizing continuous and categorical data, including meta-regression with multiple covariates and their interactions, phylogenetic analyses, and simple missing data imputation.

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Issue 8.6: How to Measure Natural Selection

Issue 8.6 is now online!

The April issue of Methods, which includes our latest Special Feature – ‘How to Measure Natural Selection – is now online!

Understanding how and why some individuals survive and reproduce better than others, the traits that allow them to do so, the genetic basis of those traits, and the signatures of past and present selection in patterns of variation in the genome remain at the top of the research agenda for evolutionary biology. This Special Feature – Guest Edited by Jeff Conner, John Stinchcombe and Joanna Kelley – draws together a collection of seven papers that highlight new methodological and conceptual approaches to meeting this agenda.

Three of the ‘How to Measure Natural Selection’ papers – Franklin and Morrissey, Thomson and Hadfield, and Hadfield and Thomson – clarify unresolved aspects of the literature in meaningful and important ways. Following on from this Hermisson and Pennings; Lotterhos et al.; and Villanueva‐Cañas et al. tackle the genomic results of evolution by natural selection: namely, how we can detect natural selection from genomic data? Finally, Wadgymar et al. address the issue of how much we know about the underlying loci or agents of selection.

To use the Editors’ own words, the articles in this issue “deal with how we can detect selection in a way that can be used to predict evolutionary responses, how selection affects the genome, and how selection and genetics underlie adaptive differentiation.”

All of the articles in the ‘How to Measure Natural Selection‘ Special Feature will be freely available for a limited time.
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Fast-Moving Biodiversity Assessment: Are We Already in the Future?

Post provided by Carola Gómez-Rodríguez & Alfried P. Vogler

Time flies… in the blink of an eye! And even more so in science. The molecular lab work we were used to two decades ago seems like ancient history to today’s PhD students. The speed of change in sequencing technology is so overwhelming that imagination usually fails to foresee how our daily work will be in 10 years’ time. But in the field of biodiversity assessment, we have very good clues. Next Generation Sequencing is quickly becoming our workhorse for ambitious projects of species and genetic inventories.

One by One Approach to Studying Biodiversity

For decades, most initiatives measured biodiversity in the same way: collect a sample of many individuals in the field, sort the specimens, identify them to a Linnaean species one at a time (if there was a good taxonomist in the group which, unfortunately, it is kind of lucky these days!), and count them. Or, if identification was based on molecular data, the specimen was subject to DNA extraction, to sequence one (or several) short DNA markers. This involved countless hours of work that could be saved if, instead of inventorying biodiversity specimen-by-specimen, we followed a sample-by-sample approach. To do this now, we just have to make a “biodiversity soup”.

Biodiversity assessment based on morphological identification and/or Sanger sequencing (“The one-by-one approach”)

Biodiversity assessment based on morphological identification and/or Sanger sequencing (“The one-by-one approach”)

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Decoupling Functional and Phylogenetic Dissimilarity between Organisms

Francesco de Bello describes the main elements of the method he has recently published in Methods in Ecology and Evolution. The method aims at decoupling and combining functional trait and phylogenetic dissimilarities between organisms. This allows for a more effective combination of non-overlapping information between phylogeny and functional traits. Decoupling trait and phylogenetic information can also uncover otherwise hidden signals underlying species coexistence and turnover, by revealing the importance of functional differentiation between phylogenetically related species.

In the video Francesco visually represents what the authors think their tool is doing with the data so you can see its potential. This method can provide an avenue for connecting macro-evolutionary and local factors affecting coexistence and for understanding how complex species differences affect multiple ecosystem functions.

This video is based on the article ‘Decoupling phylogenetic and functional diversity to reveal hidden signals in community assembly‘ by de Bello et al.


Issue 8.1

Issue 8.1 is now online!

The January issue of Methods is now online!

All of the articles in this month’s issue of Methods in Ecology and Evolution are free for the whole year. You will not need a subscription to access or download any of them throughout 2017.

Our first issue of this year contains three Applications articles and two Open Access articles. These five papers will be freely available permanently.

– CDMetaPOP: Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

– Rphylopars: An R implementation of PhyloPars, a tool for phylogenetic imputation of missing data and estimation of trait covariance across species (phylogenetic covariance) and within species (phenotypic covariance). Rphylopars provides expanded capabilities over the original PhyloPars interface including a fast linear-time algorithm, thus allowing for extremely large data sets (which were previously computationally infeasible) to be analysed in seconds or minutes rather than hours.

– ggtree: An R package that provides programmable visualisation and annotation of phylogenetic trees. ggtree can read more tree file formats than other software and allows colouring and annotation of a tree by numerical/categorical node attributes, manipulating a tree by rotating, collapsing and zooming out clades, highlighting user selected clades or operational taxonomic units and exploration of a large tree by zooming into a selected portion.

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Conifers for Christmas: Evolution above the level of species

Post provided by  Aelys Humphreys

Conifers for Christmas

It’s somehow fitting that the centre piece of an ancient midwinter tradition in Europe – that of decorating and worshipping an evergreen tree – is an ancient seed plant, a conifer. In Europe, we tend to think of conifers as “Christmas trees” – evergreen trees with needles and dry cones, restricted to cold and dry environments – but conifers are much more diverse and widespread than that. There are broad-leaved, tropical conifers with fleshy cones and even a parasitic species that is thought to parasitise on members of its own family!

Conifer diversity. Classic Christmas tree style conifers in the snow; a broadleaved, tropical podocarp (© Ming-I Weng); the only parasitic gymnosperm, Parasitaxus usta (©W. Baker).

Conifer diversity. Classic Christmas tree style conifers in the snow; a broadleaved, tropical podocarp (© Ming-I Weng); the only parasitic gymnosperm, Parasitaxus usta (©W. Baker).

However, while today’s distribution of conifers is global – spanning tropical, temperate and boreal zones – it is fragmented. The conifer fossil record extends well into the Carboniferous and bears witness to a lineage that was once much more abundant, widespread and diverse. So we can tell that today’s diversity and distribution have been shaped by hundreds of millions of years of speciation, extinction and migration. Continue reading

Issue 7.9

Issue 7.9 is now online!

The September issue of Methods is now online!

This month’s issue contains two Applications articles and three Open Access articles, all of which are freely available.

– Arborist Throw-Line Launcher: A cost-effective and simple alternative for collecting leaves and seeds from tall trees. The authors have also provided some tutorial videos on YouTube.

– ctmm: An R package which implements all of the continuous-time stochastic processes currently in use in the ecological literature and couples them with powerful statistical methods for autocorrelated data adapted from geostatistics and signal processing.

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