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.
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 →
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 →
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:
Linking the geography of where individuals and populations occur between seasons.
The extent, or strength, of co-occurrence of individuals and populations between seasons.
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.
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 →
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 →
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 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) aspectsof understanding the nuts and bolts of evolutionary change.Continue reading →
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!
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 →
By charting the slopes and crags on animals’ teeth as if they were mountain ranges, scientists at the Smithsonian’s National Museum of Natural History have created a powerful new way to learn about the diets of extinct animals from the fossil record.
Understanding the diets of animals that lived long ago can tell researchers about the environments they lived in and help them piece together a picture of how the planet has changed over deep time. The new quantitative approach to analysing dentition, reported on 21 November in the journal Methods in Ecology and Evolution, will also give researchers a clearer picture of how animals evolve in response to changes in their environment.
A 3D reconstruction of the teeth of a western gorilla (Gorilla gorilla).