The space for species: how spatial aspects influence speciation

Spatial and temporal factors of speciation

The processes driving genetic differentiation, and the progressive development of populations along the speciation continuum, are complex in nature and influenced by a number of factors. Generally, on The G-CAT we have considered the temporal aspects of these factors: how time much time is needed for genetic differentiation, how this might not be consistent across different populations or taxa, and how a history of environmental changes affect the evolution of populations and species. We’ve also touched on the spatial aspects of speciation and genetic differentiation before, but in significantly less detail.

To expand on this, we’re going to look at a few different models of how the spatial distribution of populations influences their divergence, and particularly how these factor into different processes of speciation.

What comes first, ecological or genetic divergence?

One key paradigm in understanding speciation is somewhat an analogy to the “chicken and the egg scenario”, albeit with ecological vs. genetic divergence. This concept is based on the idea that two aspects are key for determining the formation of new species: genetic differentiation of the populations in question, and ecological (or adaptive) changes that provide new ecological niches for species to inhabit. Without both, we might have new morphotypes or ecotypes of a singular species (in the case of ecological divergence without strong genetic divergence) or cryptic species (genetically distinct but ecologically identical species).

The order of these two processes have been in debate for some time, and different aspects of species and the environment can influence how (or if) these processes occur.

Different spatial models of speciation

Generally, when we consider the spatial models for speciation we divide these into distinct categories based on the physical distance of populations from one another. Although there is naturally a lot of grey area (as there is with almost everything in biological science), these broad concepts help us to define and determine how speciation is occurring in the wild.

Allopatric speciation

The simplest model is one we have described before called “allopatry”. In allopatry, populations are distributed distantly from one another, so that there are separated and isolated. A common way to imagine this is islands of populations separated by ocean of unsuitable habitat.

Allopatric speciation is considered one of the simplest and oldest models of speciation as the process is relatively straightforward. Geographic isolation of populations separates them from one another, meaning that gene flow is completely stopped and each population can evolve independently. Small changes in the genes of each population over time (e.g. due to different natural selection pressures) cause these populations to gradually diverge: eventually, this divergence will reach a point where the two populations would not be compatible (i.e. are reproductively isolated) and thus considered separate species.

Allopatry_example
The standard model of allopatric speciation, following an island model. 1) We start with a single population occupying a single island.  2) A rare dispersal event pushes some individuals onto a new island, forming a second population. Note that this doesn’t happen often enough to allow for consistent gene flow (i.e. the island was only colonised once). 3) Over time, these populations may accumulate independent genetic and ecological changes due to both natural selection and drift, and when they become so different that they are reproductively isolated they can be considered separate species.

Although relatively straightforward, one complex issue of allopatric speciation is providing evidence that hybridisation couldn’t happen if they reconnected, or if populations could be considered separate species if they could hybridise, but only under forced conditions (i.e. it is highly unlikely that the two ‘species’ would interact outside of experimental conditions).

Parapatric and peripatric speciation

A step closer in bringing populations geographically together in speciation is “parapatry” and “peripatry”. Parapatric populations are often geographically close together but not overlapping: generally, the edges of their distributions are touching but do not overlap one another. A good analogy would be to think of countries that share a common border. Parapatry can occur when a species is distributed across a broad area, but some form of narrow barrier cleaves the distribution in two: this can be the case across particular environmental gradients where two extremes are preferred over the middle.

The main difference between paraptry and allopatry is the allowance of a ‘hybrid zone’. This is the region between the two populations which may not be a complete isolating barrier (unlike the space between allopatric populations). The strength of the barrier (and thus the amount of hybridisation and gene flow across the two populations) is often determined by the strength of the selective pressure (e.g. how unfit hybrids are). Paraptry is expected to reduce the rate and likelihood of speciation occurring as some (even if reduced) gene flow across populations is reduces the amount of genetic differentiation between those populations: however, speciation can still occur.

Parapatric speciation across a thermocline.jpg
An example of parapatric species across an environment gradient (in this case, a temperature gradient along the ocean coastline). Left: We have two main species (red and green fish) which are adapted to either hotter or colder temperatures (red and green in the gradient), respectively. A small zone of overlap exists where hybrid fish (yellow) occur due to intermediate temperature. Right: How the temperature varies across the system, forming a steep gradient between hot and cold waters.

Related to this are peripatric populations. This differs from parapatry only slightly in that one population is an original ‘source’ population and the other is a ‘peripheral’ population. This can happen from a new population becoming founded from the source by a rare dispersal event, generating a new (but isolated) population which may diverge independently of the source. Alternatively, peripatric populations can be formed when the broad, original distribution of the species is reduced during a population contraction, and a remnant piece of the distribution becomes fragmented and ‘left behind’ in the process, isolated from the main body. Speciation can occur following similar processes of allopatric speciation if gene flow is entirely interrupted or paraptric if it is significantly reduced but still present.

Peripatric distributions.jpg
The two main ways peripatric species can form. Left: The dispersal method. In this example, there is a central ‘source’ population (orange birds on the main island), which holds most of the distribution. However, occasionally (more frequently than in the allopatric example above) birds can disperse over to the smaller island, forming a (mostly) independent secondary population. If the gene flow between this population and the central population doesn’t overwhelm the divergence between the two populations (due to selection and drift), then a new species (blue birds) can form despite the gene flow. Right: The range contraction method. In this example, we start with a single widespread population (blue lizards) which has a rapid reduction in its range. However, during this contraction one population is separated from the main body (i.e. as a refugia), which may also be a precursor of peripatric speciation.

Sympatric (ecological) speciation

On the other end of the distribution spectrum, the two diverging populations undergoing speciation may actually have completely overlapping distributions. In this case, we refer to these populations as “sympatric”, and the possibility of sympatric speciation has been a highly debated topic in evolutionary biology for some time. One central argument rears its head against the possibility of sympatric speciation, in that if populations are co-occurring but not yet independent species, then gene flow should (theoretically) occur across the populations and prevent divergence.

It is in sympatric speciation that we see the opposite order of ecological and genetic divergence happen. Because of this, the process is often referred to as “ecological speciation”, where individual populations adapt to different niches within the same area, isolating themselves from one another by limiting their occurrence and tolerances. As the two populations are restricted from one another by some kind of ecological constraint, they genetically diverge over time and speciation can occur.

This can be tricky to visualise, so let’s invent an example. Say we have a tropical island, which is occupied by one bird species. This bird prefers to eat the large native fruit of the island, although there is another fruit tree which produces smaller fruits. However, there’s only so much space and eventually there are too many birds for the number of large fruit trees available. So, some birds are pushed to eat the smaller fruit, and adapt to a different diet, changing physiology over time to better acquire their new food and obtain nutrients. This shift in ecological niche causes the two populations to become genetically separated as small-fruit-eating-birds interact more with other small-fruit-eating-birds than large-fruit-eating-birds. Over time, these divergences in genetics and ecology causes the two populations to form reproductively isolated species despite occupying the same island.

Ecological sympatric speciation
A diagram of the ecological speciation example given above. Note that ecological divergence occurs first, with some birds of the original species shifting to the new food source (‘ecological niche’) which then leads to speciation. An important requirement for this is that gene flow is somehow (even if not totally) impeded by the ecological divergence: this could be due to birds preferring to mate exclusively with other birds that share the same food type; different breeding seasons associated with food resources; or other isolating mechanisms.

Although this might sound like a simplified example (and it is, no doubt) of sympatric speciation, it’s a basic summary of how we ended up with so many species of Darwin’s finches (and why they are a great model for the process of evolution by natural selection).

The complexity of speciation

As you can see, the processes and context driving speciation are complex to unravel and many factors play a role in the transition from population to species. Understanding the factors that drive the formation of new species is critical to understanding not just how evolution works, but also in how new diversity is generated and maintained across the globe (and how that might change in the future).

 

What’s the (allele) frequency, Kenneth?

Allele frequency

A number of times before on The G-CAT, we’ve discussed the idea of using the frequency of different genetic variants (alleles) within a particular population or species to test a number of different questions about evolution, ecology and conservation. These are all based on the central notion that certain forces of nature will alter the distribution and frequency of alleles within and across populations, and that these patterns are somewhat predictable in how they change.

One particular distinction we need to make early here is the difference between allele frequency and allele identity. In these analyses, often we are working with the same alleles (i.e. particular variants) across our populations, it’s just that each of these populations may possess these particular alleles in different frequencies. For example, one population may have an allele (let’s call it Allele A) very rarely – maybe only 10% of individuals in that population possess it – but in another population it’s very common and perhaps 80% of individuals have it. This is a different level of differentiation than comparing how different alleles mutate (as in the coalescent) or how these mutations accumulate over time (like in many phylogenetic-based analyses).

Allele freq vs identity figure.jpg
An example of the difference between allele frequency and identity. In this example (and many of the figures that follow in this post), the circle denote different populations, within which there are individuals which possess either an A gene (blue) or a B gene. Left: If we compared Populations 1 and 2, we can see that they both have A and B alleles. However, these alleles vary in their frequency within each population, with an equal balance of A and B in Pop 1 and a much higher frequency of B in Pop 2. Right: However, when we compared Pop 3 and 4, we can see that not only do they vary in frequencies, they vary in the presence of alleles, with one allele in each population but not the other.

Non-adaptive (neutral) uses

Testing neutral structure

Arguably one of the most standard uses of allele frequency data is the determination of population structure, one which more avid The G-CAT readers will be familiar with. This is based on the idea that populations that are isolated from one another are less likely to share alleles (and thus have similar frequencies of those alleles) than populations that are connected. This is because gene flow across two populations helps to homogenise the frequency of alleles within those populations, by either diluting common alleles or spreading rarer ones (in general). There are a number of programs that use allele frequency data to assess population structure, but one of the most common ones is STRUCTURE.

Gene flow homogeneity figure
An example of how gene flow across populations homogenises allele frequencies. We start with two initial populations (and from above), which have very different allele frequencies. Hybridising individuals across the two populations means some alleles move from Pop 1 and Pop 2 into the hybrid population: which alleles moves is random (the smaller circles). Because of this, the resultant hybrid population has an allele frequency somewhere in between the two source populations: think of like mixing red and blue cordial and getting a purple drink.

 

Simple YPP structure figure.jpg
An example of a Structure plot which long-term The G-CAT readers may be familiar with. This is taken from Brauer et al. (2013), where the authors studied the population structure of the Yarra pygmy perch. Each small column represents a single individual, with the colours representing how well the alleles of that individual fit a particular genetic population (each population has one colour). The numbers and broader columns refer to different ‘localities’ (different from populations) where individuals were sourced. This shows clear strong population structure across the 4 main groups, except for in Locality 6 where there is a mixture of Eastern and Merri/Curdies alleles.

Determining genetic bottlenecks and demographic change

Other neutral aspects of population identity and history can be studied using allele frequency data. One big component of understanding population history in particular is determining how the population size has changed over time, and relating this to bottleneck events or expansion periods. Although there are a number of different approaches to this, which span many types of analyses (e.g. also coalescent methods), allele frequency data is particularly suited to determining changes in the recent past (hundreds of generations, as opposed to thousands of generations ago). This is because we expect that, during a bottleneck event, it is statistically more likely for rare alleles (i.e. those with low frequency) in the population to be lost due to strong genetic drift: because of this, the population coming out of the bottleneck event should have an excess of more frequent alleles compared to a non-bottlenecked population. We can determine if this is the case with tests such as the heterozygosity excess, M-ratio or mode shift tests.

Genetic drift and allele freq figure
A diagram of how allele frequencies change in genetic bottlenecks due to genetic drift. Left: Large circles again denote a population (although across different sequential times), with smaller circle denoting which alleles survive into the next generation (indicated by the coloured arrows). We start with an initial ‘large’ population of 8, which is reduced down to 4 and 2 in respective future times. Each time the population contracts, only a select number of alleles (or individuals) ‘survive’: assuming no natural selection is in process, this is totally random from the available gene pool. Right: We can see that over time, the frequencies of alleles A and B shift dramatically, leading to the ‘extinction’ of Allele B due to genetic drift. This is because it is the less frequent allele of the two, and in the smaller population size has much less chance of randomly ‘surviving’ the purge of the genetic bottleneck. 

Adaptive (selective) uses

Testing different types of selection

We’ve also discussed previously about how different types of natural selection can alter the distribution of allele frequency within a population. There are a number of different predictions we can make based on the selective force and the overall population. For understanding particular alleles that are under strong selective pressure (i.e. are either strongly adaptive or maladaptive), we often test for alleles which have a frequency that strongly deviates from the ‘neutral’ background pattern of the population. These are called ‘outlier loci’, and the fact that their frequency is much more different from the average across the genome is attributed to natural selection placing strong pressure on either maintaining or removing that allele.

Other selective tests are based on the idea of correlating the frequency of alleles with a particular selective environmental pressure, such as temperature or precipitation. In this case, we expect that alleles under selection will vary in relation to the environmental variable. For example, if a particular allele confers a selective benefit under hotter temperatures, we would expect that allele to be more common in populations that occur in hotter climates and rarer in populations that occur in colder climates. This is referred to as a ‘genotype-environment association test’ and is a good way to detect polymorphic selection (i.e. when multiple alleles contribute to a change in a single phenotypic trait).

Genotype by environment figure.jpg
An example of how the frequency of alleles might vary under natural selection in correlation to the environment. In this example, the blue allele A is adaptive and under positive selection in the more intense environment, and thus increases in frequency at higher values. Contrastingly, the red allele B is maladaptive in these environments and decreases in frequency. For comparison, the black allele shows how the frequency of a neutral (non-adaptive or maladaptive) allele doesn’t vary with the environment, as it plays no role in natural selection.

Taxonomic (species identity) uses

At one end of the spectrum of allele frequencies, we can also test for what we call ‘fixed differences’ between populations. An allele is considered ‘fixed’ it is the only allele for that locus in the population (i.e. has a frequency of 1), whilst the alternative allele (which may exist in other populations) has a frequency of 0. Expanding on this, ‘fixed differences’ occur when one population has Allele A fixed and another population has Allele B fixed: thus, the two populations have as different allele frequencies (for that one locus, anyway) as possible.

Fixed differences are sometimes used as a type of diagnostic trait for species. This means that each ‘species’ has genetic variants that are not shared at all with its closest relative species, and that these variants are so strongly under selection that there is no diversity at those loci. Often, fixed differences are considered a level above populations that differ by allelic frequency only as these alleles are considered ‘diagnostic’ for each species.

Fixed differences figure.jpg
An example of the difference between fixed differences and allelic frequency differences. In this example, we have 5 cats from 3 different species, sequencing a particular target gene. Within this gene, there are three possible alleles: T, A or G respectively. You’ll quickly notice that the allele is both unique to Species A and is present in all cats of that species (i.e. is fixed). This is a fixed difference between Species A and the other two. Alleles and G, however, are present in both Species B and C, and thus are not fixed differences even if they have different frequencies.

Intrapopulation (relatedness) uses

Allele frequency-based methods are even used in determining relatedness between individuals. While it might seem intuitive to just check whether individuals share the same alleles (and are thus related), it can be hard to distinguish between whether they are genetically similar due to direct inheritance or whether the entire population is just ‘naturally’ similar, especially at a particular locus. This is the distinction between ‘identical-by-descent’, where alleles that are similar across individuals have recently been inherited from a similar ancestor (e.g. a parent or grandparent) or ‘identical-by-state’, where alleles are similar just by chance. The latter doesn’t contribute or determine relatedness as all individuals (whether they are directly related or not) within a population may be similar.

To distinguish between the two, we often use the overall frequency of alleles in a population as a basis for determining how likely two individuals share an allele by random chance. If alleles which are relatively rare in the overall population are shared by two individuals, we expect that this similarity is due to family structure rather than population history. By factoring this into our relatedness estimates we can get a more accurate overview of how likely two individuals are to be related using genetic information.

The wild world of allele frequency

Despite appearances, this is just a brief foray into the many applications of allele frequency data in evolution, ecology and conservation studies. There are a plethora of different programs and methods that can utilise this information to address a variety of scientific questions and refine our investigations.

Notes from the Field: Cliff racer

Scientific name

Cinis descendens

Meaning: Cinis: from [ash] in Latin; descendens from [descends] in Latin.

Translation: descending from the ash; describes hunting behaviour in ash mountains of Vvardenfell.

Common name

Cliff racer

cliff racer
A cliff racer hovering above a precipice on Vvardenfell.

Taxonomic status

Kingdom Animalia; Phylum Chordata; Class Aves; Subclass Archaeornithes; Family Vvardidae; Genus Cinis; Species descendens

Conservation status

Least Concern [circa 3E 427]

Threatened [circa 4E 433]

Distribution

Once widespread throughout the north eastern region of Tamriel, occupying regions from the island of Vvardenfell to mainland Morrowind and Solstheim. Despite their name, the cliff racer is found across nearly all geographic regions of Vvardenfell, although the species is found in greatest densities in the rocky interior region of Stonefalls.

Following a purge of the species as part of pest control management, the cliff racer was effectively exterminated from parts of its range, including local extinction on the island of Solstheim. Since the cull the cliff racer is much less abundant throughout its range although still distributed throughout much of Vvardenfell and mainland Morrowind.

Morrowind
The province of Morrowind, which largely contains the distribution of the cliff racer. The island of Solstheim is found to the northwest of the map (the lower half of the island can be seen in brown).

Habitat

Although, much as the name suggests, the cliff racer prefers rocky outcroppings and mountainous regions in which it can build its nest, the species is frequently seen in lowland swamp and plains regions of Morrowind.

Behaviour and ecology

The cliff racer is a highly aggressive ambush predator, using height and range to descend on unsuspecting victims and lashing at them with its long, sharp tail. Although preferring to predate on small rodents and insects (such as kwama), cliff racers have been known to attack much larger beasts such as agouti and guar if provoked or desperate. The highly territorial nature of cliff racer means that they often attack travellers, even if they pose no immediate threat or have done nothing to provoke the animal.

Cliff_Racer_(Online).png
A cliff racer descends upon its prey.

Despite the territoriality of cliff racers, large flocks of them can often be found in the higher altitude regions of Vvardenfell, perhaps facilitated by an abundance of food (reducing competition) or communal breeding grounds. Attempts by researchers to study these aggregations have been limited due to constant attacks and damage to equipment by the flock.

Demography

Prior to the purging of cliff racers in the early 4E by Saint Jiub, the cliff racer was overly abundant throughout its range and considered a pest species by native peoples. Although formal studies on the population structure of the species was never conducted due to their aggressive nature, suppositions of migratory rates, distances and geographies suggested that potentially three major (ESUs) populations existed; one of Solstheim, one of Vvardenfell, and another of mainland Morrowind.

Following the control measures implemented, the population size of these populations of cliff racers declined severely; however, given the survival of the majority of the population it does not appear this bottleneck has severely impacted the longevity of the species. The extirpation of the Solstheim population of cliff racers likely removed a unique ESU from the species, given the relative isolation of the island. Whether the island will be recolonised in time by Vvardenfell cliff racers is unknown, although the presence of any cliff racers back onto Solstheim would likely be met with strong opposition from the local peoples.

Adaptive traits

The broad wings, dorsal sail and long tail allow the cliff racer to travel large distances in the air, serving them well in hunting behaviour. The drawback of this is that, if hunting during the middle hours of the day, the cliff racer leaves an imposing shadow on the ground and silhouette in the sky, often alerting aware prey to their presence. That said, the speed of descent and disorienting cry of the animal often startles prey long enough for the cliff racer to attack.

The plumes of the cliff racer are a well-sought-after commodity by local peoples, used in the creation of garments and household items. Whether these plumes serve any adaptive purpose (such as sexual selection through mate signalling) is unknown, given the difficulties with studying wild cliff racer behaviour.

Management actions

Although suffering from a strong population bottleneck after the purge, the cliff racer is still relatively abundant across much of its range and maintains somewhat stable size. Management and population control of the cliff racer is necessary across the full distribution of the species to prevent strong recovery and maintain public safety and ecosystem balance. Breeding or rescuing cliff racers is strictly forbidden and the species has been widely declared as ‘native pest’, despite the somewhat oxymoron nature of the phrase.

Moving right along: dispersal and population structure

The impact of species traits on evolution

Although we often focus on the genetic traits of species in molecular ecology studies, the physiological (or phenotypic) traits are equally as important in shaping their evolution. These different traits are not only the result themselves of evolutionary forces but may further drive and shape evolution into the future by changing how an organism interacts with the environment.

There are a massive number of potential traits we could focus on, each of which could have a large number of different (and interacting) impacts on evolution. One that is often considered, and highly relevant for genetic studies, is the influence of dispersal capability.

Dispersal

Dispersal is essentially the process of an organism migrating to a new habitat, to the point of the two being used almost interchangeably. Often, however, we regard dispersal as a migration event that actually has genetic consequences; particularly, if new populations are formed or if organisms move from one population to another. This can differ from straight migration in that animals that migrate might not necessarily breed (and thus pass on genes) into a new region during their migration; thus, evidence of those organisms will not genetically proliferate into the future through offspring.

Naturally, the ability of organisms to disperse is highly variable across the tree of life and reliant on a number of other physiological factors. Marine mammals, for example, can disperse extremely far throughout their lifetimes, whereas some very localised species like some insects may not move very far within their lifetime at all. The movement of organisms directly facilitates the movement of genetic material, and thus has significant impacts on the evolution and genetic diversity of species and populations.

Dispersal vs pop structure
The (simplistic) relationship between dispersal capability and one aspect of population genetics, population structure (measured as Fst). As organisms are more capable of dispersing longer distance (or more frequently), the barriers between populations become weaker.

Highly dispersive species

At one end of the dispersal spectrum, we have highly dispersive species. These can move extremely long distances and thus mix genetic material from a wide range of habitats and places into one mostly-cohesive population. Because of this, highly dispersive species often have strong colonising abilities and can migrate into a range of different habitats by tolerating a wide range of conditions. For example, a single whale might hang around Antarctica for part of the year but move to the tropics during other times. Thus, this single whale must be able to tolerate both ends of the temperature spectrum.

As these individuals occupy large ranges, localised impacts are unlikely to critically affect their full distribution. Individual organisms that are occupying an unpleasant space can easily move to a more favourable habitat (provided that one exists). Furthermore, with a large population (which is more likely with highly dispersive species), genetic drift is substantially weaker and natural selection (generally) has a higher amount of genetic diversity to work with. This is, of course, assuming that dispersal leads to a large overall population, which might not be the case for species that are critically endangered (such as the cheetah).

Highly dispersive animals often fit the “island model” of Wright, where individual subpopulations all have equal proportions of migrants from all other subpopulations. In reality, this is rare (or unreasonable) due to environmental or physiological limitations of species; distance, for example, is not implicitly factored into the basic island model.

Island model
The Wright island model of population structure. In this example, different independent populations are labelled in the bold letters, with dispersal pathways demonstrated by the different arrows. In the island model, dispersal is equally likely between all populations (including from BD in this example, even though there aren’t any arrows showing it). Naturally, this is not overly realistic and so the island model is used mostly as a neutral, base model.

Intermediately dispersing species

A large number of species, however, are likely to occupy a more intermediate range of dispersal ability. These species might be able to migrate to neighbouring populations, or across a large proportion of their geographic range, but individuals from one end of the range are still somewhat isolated from individuals at the other end.

This often leads to some effect of population structure; different portions of the geographic range are genetically segregated from one another depending on how much gene flow (i.e. dispersal) occurs between populations. In the most simplest scenario, this can lead to what we call isolation-by-distance. Rather than forming totally independent populations, gene flow occurs across short ranges between adjacent ‘populations’. This causes a gradient of genetic differentiation, with one end of the range being clearly genetically different to the other end, with a gradual slope throughout the range. We see this often in marine invertebrates, for example, which might have somewhat localised dispersal but still occupy a large range by following oceanographic currents.

River IDB network
An example of how an isolation-by-distance population network might come about. In this example, we have a series of populations (the different pie charts) spread throughout a river system (that blue thing). The different pie charts represent how much of the genetics of that population matches one end of the river: either the blue end (left) or red end (right). Populations can easily disperse into adjacent populations (the green arrows) but less so to further populations. This leads to gradual changes across the length of the river, with the far ends of the river clearly genetically distinct from the opposite end but relatively similar to neighbouring populations.
River IDB pop structure.jpg
The genetic representation of the above isolation-by-distance example. Each column represents a single population (in the previous figure, a pie chart), with the different colours also representing the relative genetic identity of that population. As you can see, moving from Population 1 to 10 leads to a gradient (decreasing) in blue genes but increase in red genes. The inverse can be said moving in the opposite direction. That said, comparing Population 1 and Population 10 shows that they’re clearly different, although there is no clear cut-off point across the range of other populations.

Medium dispersal capabilities are also often a requirement for forming ‘metapopulations’. In this population arrangement, several semi-independent populations are present within the geographic range of the species. Each of these are subject to their own local environmental pressures and demographic dynamics, and because of this may go locally extinct at any given time. However, dispersal connections between many of these populations leads to recolonization and gene flow patterns, allowing for extinction-dispersal dynamics to sustain the overall metapopulation. Generally, this would require greater levels of dispersal than those typically found within metapopulation species, as individuals must traverse uninhabitable regions relatively frequently to recolonise locally extinct habitat.

Metapopulation structure.jpg
An example of metapopulation dynamics. Different subpopulations (lettered circles) are connected via dispersal (arrows). These different subpopulations can be different sizes and are mostly independent of one another, meaning that a single subpopulation can go locally extinct (the red X) without collapsing the entire system. The different dispersal pathways mean that one population can recolonise extinct habitat and essentially ‘rebirth’ other subpopulations (the green arrows).

Weakly dispersing species

At the far opposite end of the dispersal ability spectrum, we have low dispersal species. These are often localised, endemic species that for various reasons might be unable to travel very far at all; for some, they may spend their entire adult life in a sedentary form. The lack of dispersal lends to very strong levels of population structure, and individual populations often accumulate genetic differences relatively quickly due to genetic drift or local adaptation.

Species with low dispersal capabilities are often at risk of local extinction and are unable to easily recolonise these habitats after the event has ended. Their movement is often restricted to rare environmental events such as flooding that carry individuals long distances despite their physiological limitations. Because of this, low dispersal species are often at greater risk of total extinction and extinction vertices than their higher dispersing counterparts.

Accounting for dispersal in population genetics

Incorporating biological and physiological aspects of our study taxa is important for interpreting the evolutionary context of species. Dispersal ability is but one of many characteristics that can influence the ability of species to respond to selective pressures, and the context in which this natural selection occurs. Thus, understanding all aspects of an organism is important in building the full picture of their evolution and future prospects.

The direction of selection

The nature of adaptation

One of the most fundamental aspects of natural selection and evolution is, of course, the underlying genetic traits that shape the physical, selected traits. Most commonly, this involves trying to understand how changes in the distribution and frequencies of particular genetic variants (alleles) occur in nature and what forces of natural election are shaping them. Remember that natural selection acts directly on the physical characteristics of species; if these characteristics are genetically-determined (which many are), then we can observe the flow-on effects on the genetic diversity of the target species.

Although we might expect that natural selection is a fairly predictable force, there are a myriad of ways it can shape, reduce or maintain genetic diversity and identity of populations and species. In the following examples, we’re going to assume that the mentioned traits are coded for by a single gene with two different alleles for simplicity. Thus, one allele = one version of the trait (and can be used interchangeably). With that in mind, let’s take a look at the three main broad types of changes we observe in nature.

Directional selection

Arguably the most traditional perspective of natural selection is referred to as ‘directional selection’. In this example, nature selection causes one allele to be favoured more than another, which causes it to increase dramatically in frequency compared to the alternative allele. The reverse effect (natural selection pushing against a maladaptive allele) is still covered by directional selection, except that it functions in the opposite way (the allele under negative selection has reduced frequency, shifting towards the alternative allele).

Directional selection diagram
An example of directional selection. In this instance, we have one population of cats and a single phenotypic trait (colour) which ranges from 0 (yellow) to 1 (red). Red colour is selected for above all other colours; the original population has a pretty diverse mix of colours to start. Over time, we can see the average colour of the entire population moves towards more red colours whilst yellow colours start to disappear. Note that although the final population is predominantly red, there is still some (minor) variation in colours. These changes are reflected in the distribution of the colour-coding alleles (right), as it moves towards the red end of the spectrum.

Balancing selection

Natural selection doesn’t always push allele frequencies into different directions however, and sometimes maintains the diversity of alleles in the population. This is what happens in ‘balancing selection’ (sometimes also referred to as ‘stabilising selection’). In this example, natural selection favours non-extreme allele frequencies, and pushes the distribution of allele frequencies more to the centre. This may happen if deviations from the original gene, regardless of the specific change, can have strongly negative effects on the fitness of an organism, or in genes that are most fit when there is a decent amount of variation within them in the population (such as the MHC region, which contributes to immune response). There are a couple other reasons balancing selection may occur, though.

Heterozygote advantage

One example is known as ‘heterozygote advantage’. This is when an organism with two different alleles of a particular gene has greater fitness than an organism with two identical copies of either allele. A seemingly bizarre example of heterozygote advantage is related to sickle cell anaemia in African people. Sickle cell anaemia is a serious genetic disorder which is encoded for by recessive alleles of a haemoglobin gene; thus, a person has to carry two copies of the disease allele to show damaging symptoms. While this trait would ordinarily be strongly selected against in many population, it is maintained in some African populations by the presence of malaria. This seems counterintuitive; why does the presence of one disease maintain another?

Well, it turns out that malaria is not very good at infecting sickle cells; there are a few suggested mechanisms for why but no clear single answer. Naturally, suffering from either sickle cell anaemia or malaria is unlikely to convey fitness benefits. In this circumstance, natural selection actually favours having one sickle cell anaemia allele; while being a carrier isn’t ordinarily as healthy as having no sickle cell alleles, it does actually make the person somewhat resistant to malaria. Thus, in populations where there is a selective pressure from malaria, there is a heterozygote advantage for sickle cell anaemia. For those African populations without likely exposure to malaria, sickle cell anaemia is strongly selected against and less prevalent.

Malaria and sickle diagram
A diagram of how heterozygote advantage works in sickle cell anaemia and malaria resistance. On the top we have our two main traits: the blood cell shape (which has two different alleles; normal and sickle celled) and malaria infection by mosquitoes. Blue circles indicate that the trait has good fitness, whilst red crosses indicate the trait has bad fitness. For the left hand person, having two sickle cell alleles (ss) means they are symptomatic of sickle cell anaemia and is unlikely to have a good quality of life. On the right, having two normal blood cell alleles (SS) means that he is susceptible to malaria infection. The middle person, however, having only one sickle cell allele (Ss) means they are asymptomatic but still resistant to malaria. Thus, being heterozygous for sickle cell is actually beneficial over being homozygous in either direction: this is reflected in the distribution of alleles (bottom). The left side is pushed down by sickle cell anaemia whilst the right side is pushed down by malaria, thus causing both blood cell alleles (s and S) to be maintained at an intermediate frequency (i.e. balanced). 

Frequency-dependent selection

Another form of balancing selection is called ‘frequency-dependent selection’, where the fitness of an allele is inversely proportional to its frequency. Thus, once the allele has become common due to selection, the fitness of that allele is reduced and selection will start to favour the alternative allele (which is at much lower frequency). The constant back-and-forth tipping of the selective scales results in both alleles being maintained at an equilibrium.

This can happen in a number of different ways, but often the rarer trait/allele is fundamentally more fit because of its rarity. For example, if one allele allows an individual to use a new food source, it will be very selectively fit due to the lack of competition with others. However, as that allele accumulates within the population and more individuals start to feed on that food source, the lack of ‘uniqueness’ will mean that it’s not particularly better than the original food source. A balance between the two food sources (and thus alleles) will be maintained over time as shifts towards one will make the other more fit, and natural selection will compensate.

Frequency dependent selection diagram
An example of frequency-dependent selection. The colour of the cat indicates both their genotype and their food sources: black cats eat red apples whilst green cats eat green apples (this species has apparently developed herbivory, okay?) To start with, the incredibly low frequency of green cats mean that the one green cat can exploit a huge food source compared to black cats. Because of this, natural selection favours green cats. However, in the next generation evolution overcompensates and produces way too many green cats, and now black cats are getting much more food. Natural selection bounces back to favour black cats. Eventually, this causes and equilibrium balance of the two cat types (as shifts one way will cause a shift back the other way immediately after). These changes are reflected in the overall frequency of the two types over time (top right), which eventually evens out. The bottom right figure demonstrates that for both cat types, the frequency of that colour is inversely proportional to the overall fitness (measured as a proxy by amount of food per cat).

Disruptive selection

A third category of selection (although not as frequently mentioned) is known as ‘disruptive selection’, which is essentially the direct opposite of balancing selection. In this case, both extremes of allele frequencies are favoured (e.g. 1 for one allele or 1 for the other) but intermediate frequencies are not. This can be difficult to untangle in natural populations since it could technically be attributed to two different cases of directional selection. Each allele of the same gene is directionally selected for, but in opposite populations and directions so that overall pattern shows very little intermediates.

In direct contrast to balancing selection, disruptive selection can often be a case of heterozygote disadvantage (although it’s rarely called that). In these examples, it may be that individuals which are not genetically committed to one end or the other of the frequency spectrum are maladapted since they don’t fit in anywhere. An example would be a species that occupies both the desert and a forested area, with little grassland-type habitat in the middle. For the relevant traits, strongly desert-adapted genes would be selected for in the desert and strongly forest-adapted genes would be selected for in the forest. However, the lack of gradient between the two habitats means that individuals that are half-and-half are less adaptive in both the desert and the forest. A case of jack-of-all-trades, master of none.

Disruptive selection diagram
The above example of disruptive selection. Bird colour is coded for by a single gene; green birds have a HH genotype, orange birds have a hh genotype, and yellow birds are heterozygotes (Hh). Habitats where the two homozygote colours are most adaptive are found; green birds do well in the forest whereas orange birds do well in the desert. However, there’s no intermediate habitat between the two and so yellow birds don’t really fit well anywhere; they’re outcompeted in the forest and desert by the respective other colours. This means selection favours either extreme (homozygotes), shown in the top right. If we split up the two alleles of the genotype though, we can see that this disruptive selection is really the product of two directionally selective traits working in inverse directions: H is favoured at one end and h at the other.

Direction of selection

Although it would be convenient if natural selection was entirely predictable, it often catches up by surprise in how it acts and changes species and populations in the wild. Careful analysis and understanding of the different processes and outcomes of adaptation can feed our overall understanding of evolution, and aid in at least pointing in the right direction for our predictions.