What the Past Can Tell Us About the Future: Notes from Crossing the Palaeontological – Ecological Gap

Post provided by Karen Bacon

I had the pleasure of delivering one of the plenary talks at the first (hopefully of many) Crossing the Palaeontological – Ecological Gap meeting held in the University of Leeds on August 30th and 31st. I’m a geologist and a botanist, so this is a topic that’s close to my heart and my professional interests.

How Palaeoecology Can Help Us Today

©Gail Hampshire

©Gail Hampshire

As we move into an ecologically uncertain future with pressures of climate change, land-use change and resource limitations, the fossil record offers the only truly long-term record of how Earth’s ecosystems respond to major environmental upheaval driven by climate change events. The fossil record is, of course, not without its problems – there are gaps, not everything fossilises in the same way or numbers, and comparisons to today’s ecology are extremely difficult.  It’s these difficulties (and other challenges) that make the uniting of palaeontology and ecology essential to fully address how plants, animals and other organisms have responded to major changes in the past. Perhaps uniting them could give us an idea of what to expect in our near-term future, as carbon dioxide levels return to those not previously experienced on Earth since the Pliocene, over 2 million years ago. Continue reading

Integrating Evolution and Ecology

©H. Zell

©H. Zell

The latest Methods in Ecology and Evolution Virtual Issue – ‘Integrating Evolution and Ecology‘ – is in honour of the late Isabelle Olivieri (1957-2016): an international, interdisciplinary and ground-breaking biologist. It was edited by Louise Johnson and James Bullock and features papers on topics she researched, and in many cases pioneered. But it might perhaps have been more difficult to find 15 Methods papers on areas outside of Isabelle’s research interests!

Isabelle was the first Professor of Population Genetics at Montpellier, a past President of the European Society for Evolutionary Biology (2007-2009), and a member of the European Molecular Biology Organization. She spanned subject boundaries as easily as she collaborated across geographical borders. Her publications range through metapopulation and dispersal ecology, host-parasite coevolution, life history, invasive species and conservation ecology. In keeping with this breadth of interests, she also combined theory easily with experiment, and worked with a wide range of study systems from mites to Medicago. Continue reading

How Strong is Natural Selection? Stitching Together Linear and Nonlinear Selection on a Single Scale

Post provided by Robert May Prize Winner Jonathan Henshaw

Some individuals survive and reproduce better than others. Traits that help them do so may be passed on to the next generation, leading to evolutionary change. Because of this, evolutionary biologists are interested in what differentiates the winners from the losers – how do their traits differ, and by how much? These differences are known as natural selection.

Linear and Nonlinear Selection

Traditionally, natural selection is separated into linear selection (differences in average trait values) and nonlinear selection (any other differences in trait distributions between winners and the rest). For example, successful individuals might be unusually close to average: this is known as stabilizing selection. Alternatively, winners might split into two camps, some with unusually high trait values, and others with unusually low trait values. This is disruptive selection (famously thought to explain the ur-origin of sperm and eggs). Stabilizing and disruptive selection are important types of nonlinear selection. In general, though, the trait distribution of successful individuals can differ from the general population in arbitrarily complicated ways.

When individuals with larger trait values have higher fitness on average (left panel), the trait distribution of successful individuals is shifted towards the right (right panel, orange curve). The difference in mean trait values between the winners and the general population is called linear selection.

When individuals with larger trait values have higher fitness on average (left panel), the trait distribution of successful individuals is shifted towards the right (right panel, orange curve). The difference in mean trait values between the winners and the general population is called linear selection.

Continue reading

A New Method for Computing Evolutionary Rates and Rate Shifts

Post provided by Pasquale Raia

Phylogenetic Effects

Today, everyone knows about the importance of accounting for phylogenetic effects when it comes to understanding trait evolution. How to account for phylogenetic effects is another matter though.

A couple of years ago, I was having a discussion on the R-sig-phylo blog and dared to define the Brownian Motion (BM) as kind of a null hypothesis that more realistic scenarios should be compared to. Maybe I crossed a line or made too simplistic a statement (see Adams and Collyer’s article in Systematic Biology for an explanation of why this matter is far trickier and more complicated than my reply suggested). The point is, my comment was hotly contested and a colleague ‘put the onus on me’ to do something better than the almighty (emphasis mine) BM.

The RRphylo method was my attempt to do just that. It may not be better than BM, but it is different. Often, that can be exactly what you need. Continue reading

Exploring Coevolutionary History: Do Entire Communities Shape the Evolution of Individual Species?

Post provided by Laura Russo, Katriona Shea, and Adam Miller

Diffuse Coevolution

Interactions between plants and pollinators tend to be highly generalized.

Interactions between plants and pollinators tend to be highly generalized.

In 1980, Janzen published an article titled “When is it coevolution?” where he explained the concept of diffuse coevolution: the idea that evolution of interacting species is shaped by entire communities, rather than simple paired interactions. This idea, though compelling, remains poorly understood, and strong evidence of diffuse coevolution acting on a community is lacking. Perhaps this is because there’s a lack of consensus on what would constitute evidence in support of the concept of diffuse coevolution, or, indeed, coevolution in general (Nuismer et al 2010). Continue reading

Sticking Together or Drifting Apart? Quantifying the Strength of Migratory Connectivity

Post provided by Emily Cohen

Red Knot migratory connectivity is studied with tracking technologies and color band resighting. © Tim Romano

Red Knot migratory connectivity is studied with tracking technologies and colour band resighting. © Tim Romano

The seasonal long-distance migration of all kinds of animals – from whales to dragonflies to amphibians to birds – is as astonishing a feat as it is mysterious and this is an especially exciting time to study migratory animals. In the past 20 years, rapidly advancing technologies  – from tracking devices, to stable isotopes in tissues, to genomics and analytical techniques for the analysis of ring re-encounter databases – mean that it’s now possible to follow many animals throughout the year and solve many of the mysteries of migration.

What is Migratory Connectivity?

One of the many important things we’re now able to measure is migratory connectivity, the connections of migratory individuals and populations between seasons. There are really two components of migratory connectivity:

  1. Linking the geography of where individuals and populations occur between seasons.
  2. The extent, or strength, of co-occurrence of individuals and populations between seasons.

Continue reading

The Power of Infinity: Using 3D Fractal Geometry to Study Irregular Organisms

Post provided by Jessica Reichert, André R. Backes, Patrick Schubert and Thomas Wilke

The Problem with the Shape

More than anything else, the phenotype of an organism determines how it interacts with the environment. It’s subject to natural selection, and may help to unravel the underlying evolutionary processes. So shape traits are key elements in many ecological and biological studies.

The growth form of corals is highly variable. ©Jessica Reichert

The growth form of corals is highly variable. ©Jessica Reichert

Commonly, basic parameters like distances, areas, angles, or derived ratios are used to describe and compare the shapes of organisms. These parameters usually work well in organisms with a regular body plan. The shape of irregular organisms – such as many plants, fungi, sponges or corals – is mainly determined by environmental factors and often lacks the distinct landmarks needed for traditional morphometric methods. The application of these methods is problematic and shapes are more often categorised than actually measured.

As scientists though, we favour independent statistical analyses, and there’s an urgent need for reliable shape characterisation based on numerical approaches. So, scientists often determine complexity parameters such as surface/volume ratios, rugosity, or the level of branching. However, these parameters all share the same drawback: they are delineated to a univariate number, taking information from one or few spatial scales and because of this essential information is lost. Continue reading

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

Getting Serious About Transposable Elements

Post Provided by: Gabriel Rech and José Luis Villanueva-Cañas

So Simple yet so Complex

A long standing research topic in evolutionary biology is the genetic basis of adaptation. In other words, how does a novel trait appear (or spread) in response to an environmental change? Despite the rapid advances in sequencing over the last two decades, we have only been able to fully characterize a few adaptations.

As stated by Richard Dawkins in Climbing Mount Improbable, while natural selection is a very simple process, modeling natural selection and determining its causes, effects and consequences is an extremely difficult task. Also, most of our efforts so far have been focused on just one type of genetic variation: single nucleotide polymorphisms (SNPs). Other types of variations such as transposable element (TE) insertions have received much less attention. Paradoxically, some great examples of the role of TEs in adaptation have been right under our noses the whole time, in basic biology textbooks. Continue reading

Evolutionary Quantitative Genetics: Virtual Issue

Post provided by Michael Morrissey

©Dr. Jane Ogilvie, Rocky Mountain Biological Laboratory

Evolutionary quantitative genetics provides formal theoretical frameworks for quantitatively linking natural selection, genetic variation, and the rate and direction of adaptive evolution. This strong theoretical foundation has been key to guiding empirical work for a long time. For example, rather than generally understanding selection to be merely an association of traits and fitness in some general way, theory tells us that specific quantities, such as the change in mean phenotype within generations (the selection differential; Lush 1937), or the partial regressions of relative fitness on traits (direct selection gradients; Lande 1979, Lande and Arnold 1983) will relate to genetic variation and evolution in specific, informative ways.

These specific examples highlight the importance of the theoretical foundation of evolutionary quantitative genetics for informing the study of natural selection. However, this foundation also supports the study other critical (quantification of genetic variation and evolution) and complimentary (e.g., interpretation when environments, change, the role of plasticity and genetic variation in plasticity) aspects of understanding the nuts and bolts of evolutionary change. Continue reading