What is a species, anyway?

This is Part 1 of a four part miniseries on the process of speciation; how we get new species, how we can see this in action, and the end results of the process. This week, we’ll start with a seemingly obvious question: what is a species?

The definition of a ‘species’

‘Species’ are a human definition of the diversity of life. When we talk about the diversity of life, and the myriad of creatures and plants on Earth, we often talk about species diversity. This might seem glaringly obvious, but there’s one key issue: what is a species, anyway? While we might like to think of them as discrete and obvious groups (a dog is definitely not the same species as a cat, for example), the concept of a singular “species” is actually the result of human categorisation.

In reality, the diversity of life is spread across a huge spectrum of differentiation: from things which are closely related but still different to us (like chimps), to more different again (other mammals), to hardly relatable at all (bacteria and plants). So, what is the cut-off for calling something a species, and not a different genus, family, or kingdom? Or alternatively, at what point do we call a specific sub-group of a species as a sub-species, or another species entirely?

This might seem like a simple question: we look at two things, and they look different, so they must be different species, right? Well, of course, nature is never simple, and the line between “different” and “not different” is very blurry. Here’s an example: consider that you knew nothing about the history, behaviour or genetics of dogs. If you simply looked at all the different breeds of dogs on Earth, you might suggest that there are hundreds of species of domestic dogs. That seems a little excessive though, right? In fact, the domestic dog, Eurasian wolf, and the Australian dingo are all the same species (but different subspecies, along with about 38 others…but that’s another issue altogether).

Dogs
Morphology can be misleading for identifying species. In this example, we have A) a dog, B) also a dog, C) still a dog, D) yet another dog, and E) not a dog. For the record, A-D are all Canis lupus of some variety; and are domestic dogs (Canis lupus familiaris), C is a dingo (Canis lupus dingo) and is a grey wolf (Canis lupus lupus). E, however, is the Ethiopian wolf, Canis simensis.

How do we describe species?

This method of describing species based on how they look (their morphology) is the very traditional approach to taxonomy. And for a long time, it seemed to work…until we get to more complex scenarios like the domestic dog. Or scenarios where two species look fairly similar, but in reality have evolved entirely differently for a very, very long time. Or groups which look close to more than one other species. So how do we describe them instead?

Cats and foxes
A), a fox. B), a cat. C), a foxy cat? A catty fox? A cat-fox hybrid? Something unrelated to cat or a fox?

 

Believe it or not, there are dozens of ways of deciding what is a species and what isn’t. In Speciation (2004), Coyne & Orr count at least 25 different reported Species Concepts that had been suggested within science, based on different requirements such as evolutionary history, genetic identity, or ecological traits. These different concepts can often contradict one another about where to draw the line between species…so what do we use?

The Biological Species Concept (BSC)

The most commonly used species concept is called the Biological Species Concept (BSC), which denotes that “species are groups of interbreeding natural populations that are reproductively isolated from other such groups” (Mayr, 1942). In short, a population is considered a different species to another population if an individual from one cannot reliably breed to form fertile, viable offspring with an individual from the other. We often refer to this as “reproductive isolation.” It’s important to note that reproductive isolation doesn’t mean they can’t breed at all: just that the hybrid offspring will not live a healthy life and produce its own healthy offspring.

For example, a horse and zebra can breed to produce a zorse, however zorse are fundamentally infertile (due to the different number of chromosomes between a horse and a zebra) and thus a horse is a different species to a zebra. However, a German Shepherd and a chihuahua can breed and make a hybrid mutt, so they are the same species.

zorse
A zorse, which shows its hybrid nature through zebra stripes and horse colouring. These two are still separate species since zorses are infertile, and thus are not a singular stable entity.

You might naturally ask why reproductive isolation is apparently so important for deciding species. Most directly, this means that groups don’t share gene pools at all (since genetic information is introduced and maintained over time through breeding events), which causes them to be genetically independent of one another. Thus, changes in the genetic make-up of one species shouldn’t (theoretically) transfer into the gene pool of another species through hybrids. This is an important concept as the gene pool of a species is the basis upon which natural selection and evolution act: thus, reproductively isolated species may evolve in very different manners over time.

RI example
An example of how reproductive isolation maintains genetic and evolutionary independence of species. In A), our cat groups are robust species, reproductively isolated from one another (as shown by the black box). When each species undergoes natural selection and their genetic variation changes (colour changes on the cats and DNA), these changes are kept within each lineage. This contrasts to B), where genetic changes can be transferred between species. Without reproductive isolation, evolution in the orange lineage and the blue lineage can combine within hybrids, sharing the evolutionary pathways of both ancestral species.

Pitfalls of the BSC

Just because the BSC is the most used concept doesn’t make it infallible, however. Many species on Earth don’t easily demonstrate reproductive isolation from one another, nor does the concept even make sense for asexually reproducing species. If an individual reproduced solely asexually (like many bacteria, or even some lizards), then by the BSC definition every individual is an entirely different species…which seems a little excessive. Even in sexually reproducing organisms, it can be hard to establish reproductive isolation, possibly because the species never come into contact physically.

This raises the debate of whether two species could, let alone will, hybridise in nature, which can be difficult to determine. And if two species do produce hybrid offspring, assessing their fertility or viability can be difficult to detect without many generations of breeding and measurements of fitness (hybrids may not be sustainable in nature if they are not well adapted to their environment and thus the two species are maintained as separate identities).

Hybrid birds
An example of unfit hybrids causing effective reproductive isolation. In this example, we have two different bird species adapted to very different habitats; a smaller, long-tailed bird (left) adapted to moving through dense forest, and a large, longer-legged bird (right) adapted to traversing arid deserts. When (or if) these two species hybridised, the resultant offspring would be middle of the road, possessing too few traits to be adaptive in either the forest or the desert and no fitting intermediate environment available. Measuring exactly how unfit this hybrid would be is a difficult task in establishing species boundaries.

 

Integrative taxonomy

To try and account for the issues with the BSC, taxonomists try to push for the usage of “integrative taxonomy”. This means that species should be defined by multiple different agreeing concepts, such as reproductive isolation, genetic differentiation, behavioural differences, and/or ecological traits. The more traits that can separate the two, the greater support there is for the species to be separated: if they disagree, then more information is needed to determine exactly whether or not that should be called different species. Debates about taxonomy are ongoing and are likely going to be relevant for years to come, but form critical components of understanding biodiversity, patterns of evolution, and creating effective conservation legislation to protect endangered or threatened species (for whichever groups we decide are species).

 

The direction of evolution: divergence vs. convergence

Direction of evolution

We’ve talked previously on The G-CAT about how the genetic underpinning of certain evolutionary traits can change in different directions depending on the selective pressure it is under. Particularly, we can see how the frequency of different alleles might change in one direction or another, or stabilise somewhere in the middle, depending on its encoded trait. But thinking bigger picture than just the genetics of one trait, we can actually see that evolution as an entire process works rather similarly.

Divergent evolution

The classic view of the direction of evolution is based on divergent evolution. This is simply the idea that a particular species possess some ancestral trait. The species (or population) then splits into two (for one reason or another), and each one of these resultant species and populations evolves in a different way to the other. Over time, this means that their traits are changing in different directions, but ultimately originate from the same ancestral source.

Evidence for divergent evolution is rife throughout nature, and is a fundamental component of all of our understanding of evolution. Divergent evolution means that, by comparing similar traits in two species (called homologous traits), we can trace back species histories to common ancestors. Some impressive examples of this exist in nature, such as the number of bones in most mammalian species. Humans have the same number of neck bones as giraffes; thus, we can suggest that the ancestor of both species (and all mammals) probably had a similar number of neck bones. It’s just that the giraffe lineage evolved longer bones whereas other lineages did not.

Homology figure
A diagrammatic example of homologous structures in ‘hand’ bones. The coloured bones demonstrate how the same original bone structures have diverged into different forms. Source: BiologyWise.

Convergent evolution

But of course, evolution never works as simply as you want it to, and sometimes we can get the direct opposite pattern. This is called convergent evolution, and occurs when two completely different species independently evolve very similar (sometimes practically identical) traits. This is often caused by a limitation of the environment; some extreme demand of the environment requires a particular physiological solution, and thus all species must develop that trait in order to survive. An example of this would be the physiology of carnivorous marsupials like Tasmanian devils or thylacines: despite being in another Class, their body shapes closely resemble something more canid. Likely, the carnivorous diet places some constraints on physiology, particularly jaw structure and strength.

Convergent evol intelligence
A surprising example of convergent evolution is cognitive ability in apes and some bird groups (e.g. corvids). There’s plenty of other animal groups more related to each of these that don’t demonstrate the same level of cognitive reasoning (based on the traits listed in the centre): thus, we can conclude that cognition has evolved twice in very, very different lineages. Source: Emery & Clayton, 2004.

A more dramatic (and potentially obvious) example of convergent evolution would be wings and the power of flight. Despite the fact that butterflies, bees, birds and bats all have wings and can fly, most of them are pretty unrelated to one another. It seems much more likely that flight evolved independently multiple times, rather than the other 99% of species that shared the same ancestor lost the capacity of flight.

Parallel evolution

Sometimes convergent evolution can work between two species that are pretty closely related, but still evolved independently of one another. This is distinguished from other categories of evolution as parallel evolution: the main difference is that while both species may have shared the same start and end point, evolution has acted on each one independent of the other. This can make it very difficult to diagnose from convergent evolution, and is usually determined by the exact history of the trait in question.

Parallel evolution is an interesting field of research for a few reasons. Firstly, it provides a scenario in which we can more rigorously test expectations and outcomes of evolution in a particular environment. For example, if we find traits that are parallel in a whole bunch of fish species in a particular region, we can start to look at how that particular environment drives evolution across all fish species, as opposed to one species case studies.

Marsupial handedness.jpg
Here’s another weird example; different populations of marsupials (particularly kangaroos and wallabies) show preferential handedness depending on where the population is. That is, different populations of different species of marsupials shows parallel evolution of handedness, since they’re related to one another but have evolved it independently of the other species. Source: Giljov et al. (2015).

Following from that logic, it is then important to question the mechanisms of parallelism. From a genetic point of view, do these various species use the same genes (and genetic variants) to produce the same identical trait? Or are there many solutions to the selective question in nature? While these questions are rather complicated, and there has been plenty of evidence both for and against parallel genetic underpinning of parallel traits, it seems surprisingly often that many different genetic combinations can be used to get the same result. This gives interesting insight into how complex genetic coding of traits can be, and how creative and diverse evolution can be in the real world.

Where is evolution going?

Cat phylogeny
An example of all three types of evolutionary trajectory in a single phylogeny of cats (you know how we do it here at The G-CAT). This phylogeny consists of two distinct genera; one with one species (P. aliquam) and another of three species (the red box indicates their distance). Our species have three main physical traits: coat colour, ear tufts and tail shape. At the ancestral nodes of the tree, we can see what the ancestor of these species looked like for these three traits. Each of these traits has undergone a different type of evolution. The tufts on the ears are the result of divergent evolution, since F. tuftus evolved the trait differently to its nearest relative, F. griseo. Contrastingly, the orange coat colour of F. tuftus and P. aliquam are the result of convergent evolution: neither of these species are very closely related (remembering the red box) and evolved orange coats independently of one another (since their ancestors are grey). And finally, the fluffy tails of F. hispida and F. griseo can be considered parallel evolution, since they’re similar evolutionarily (same genus) but still each evolved tail fluff independently (not in the ancestor). This example is a little convoluted, but if you trace the history of each trait in the phylogeny you can more easily see these different patterns.

So, where is evolution going for nature? Well, the answer is probably all over the place, but steered by the current environmental circumstances. Predicting the evolutionary impacts of particular environmental change (e.g. climate change) is exceedingly difficult but a critical component of understanding the process of evolution and the future of species. Evolution continually surprises us with creative solution to complex problems and I have no doubt new mysteries will continue to be thrown at us as we delve deeper.

All the world in the palm of your hand: whole genome sequencing for evolution and conservation

Building an entire genome

If bigger is better, then biggest is best. Having the genome of a particular study species fully sequenced allows us to potentially look at all of the genetic variation in the entire gene pool: but how do we sequence the entirety of the genome? And what are the benefits of having a whole genome to refer to?

Whole genome assembly
A very, very simplified overview of whole genome sequencing. Similar to other genomic technologies, we start by fragmenting the genome into much smaller, easier to sequence parts (reads). We then use a computer algorithm which pieces these reads together into a consecutive sequence based on overlapping DNA sequence (like building a chain out of Lego blocks). From this assembled genome, we can then attach annotations using information from other species’ genomes or genetic studies, which can correlate a particular sequence to a gene, a function of that gene, and the resultant protein from these gene (although not always are all of these aspects included).

Well, assembling the whole genome of an organism for the first time is a very tricky process. It involves taking DNA sequence from only a few individuals, breaking them down into smaller fragments and multiplying these fragments into the billions (moreorless the same process used in other genomics technologies: the real difference is that we need the full breadth of the genome so that we don’t miss any spaces). From these fragments, we use a complex computer algorithm which builds up a consensus sequence like a Lego tower; by finding parts of sequences which overlap, the software figures out which pieces connect to one another. Hopefully, we eventually end up with one very long continuous sequence; the genome! Sometimes, we might end with a few very large blocks (called contigs), but this is also useful for analyses (correlated with how many/big blocks there are). With this full genome, we use information from other more completed genomes (such as those from model species like humans, mice or even worms) to figure out which sections of the genome relate to specific genes. We can then annotate these sections by labelling them as clear genes, complete with start and end point, and attach a particular physical function of that gene.

The benefits of whole genomes

Having an entire genome as a reference is an extremely helpful tool in conservation and evolutionary studies. The first, and perhaps most obvious benefit, is the sheer scale of the data we can use. By having the entirety of the genome available, we can use potentially billions of base pairs of sequence in our genetic analyses (for reference, the human genome is >3 billion base pairs long). Even if we don’t sequence the full genome for all of our samples, having a reference genome as basis for assembly our reduced datasets significantly improves the quantity and quality of sequences we can use.

Another very important benefit is the ability to prescribe function in our studies. Many of our processes for obtaining data, even for genomic technologies, use random and anonymous fragments of the genome. Although this is a cost-effective way to obtain a very large amount of data, it unfortunately means that we often have no idea which part of the genome our sequences came from. This means that we don’t know which sequences relate to specific genes, and even if we did we would have no idea what those genes are or do! But with an annotated genome, we can take even our fragmented sequence and check it against the genome and find out what genes are present.

Understanding adaptation

Based on that, it seems pretty obvious about exactly how having an annotated genome can help us in studies of adaptation. Knowing the functional aspect of our genetic data allows us to more directly determine how evolution is happening in nature; instead of only being able to say that two species are evolving differently from one another, for example, we can explicitly look at how they are evolving. Is one evolving tolerance to hotter temperatures? Are they evolving different genes to handle different diets? Are they evolving in response to an external influence, like a viral outbreak or changing climate? What are the physiological consequences of these changes? These questions are critical in understanding past and future evolution, and full genome analysis allows us to delve into them much deeper.

Manhattan plot example
A (slightly edited) figure of full genome comparisons between domestic dogs and wild wolves by Axelsson et al. (2013), with the aim of understanding the evolutionary changes associated with domestication. For avid readers, this figure probably looks familiar. This figure compares the genetic differentiation across the entire genome between dogs and wolves, with some sections of the genome (circled) showing clear differences. As there is an annotated dog genome, the authors then delved into these genes to understand the functional differences between the two. By comparing their genetic differences to functional genes, the authors can more explicitly suggest mechanisms or changes associated with the domestication process (such as adaptation to a starch-heavy and human-influenced diet).

 

 

This includes allowing us to better understand how adaptation actually works in nature. As we’ve discussed before, more traditional studies often assumed that single, or very few, genes were responsible for allowing a species to adapt and change, and that these genes had very strong effects on their physiology. But what we see far more often is polygenic adaptation; small changes in a very large number of genes which, combined together, allow the species to adapt and evolve. By having the entirety of the genome available, we are much more likely to capture all of the genes that are under natural selection in a particular population or species, painting a clearer picture of their evolutionary trajectory.

Understanding demography

The much larger dataset of full genomes is also important for understanding the non-adaptive parts of evolution; the demographic history. Given that selectively neutral impacts (e.g. reductions in population size) are likely to impact all of the genes in the gene pool somewhat equally, having a full genome allows us to more accurately infer the demographic state and historical patterns of species.

For both adaptive and non-adaptive variation, it is also important to consider what we call linkage disequilibrium. Genetic sequences that are physically close to each other in the genome will often be inherited together due to the imprecision of recombination (a fairly technical process, so I won’t delve into this): what this can mean is that if a gene is under very strong selection, then sequences around this gene will also look like they’re under selection too. This can give falsely positive adaptive genes (i.e. sequences that look like genes under selection but are just linked to a gene that is) or can interfere with demographic analyses (since they often assume no selection, or linkage to selection, on the sequences used). With a whole genome, we can actually estimate how far away a base pair has to be before it’s not linked anymore; we call these linkage blocks, and they’re very useful additions to analyses.

Linkage_example
An example of linkage as a process. We start with a particular sequence (top); during recombination, this sequence may randomly break and rearrange into different parts. In this example, I’ve simulated four different ‘breaks’ (dashed coloured lines) due to recombination. Each of these breaks leads to two separate blocks of fragments; for example, the break at the blue line results in the second two sequence blocks (middle). If we focus on one target base pair in the sequence (golden A), then we can see in some fragments it remains with certain bases, but sometimes it gets separated by the break. If we compare how often the golden A is in the same block (i.e. is co-inherited) as each of the other bases, across all 4 breaks, then we see that the bases that are closest to it (the golden A is represented by the golden bar) are almost always in the same block. This makes sense: the further away a base is from our target, the more likely that there will be a break between it. This is shown in the frequency distributions at the bottom: the left figure shows the actual frequencies of co-inheritance (i.e. linkage) using the top example and those 4 breaks. The right figure shows a more realistic depiction of how linkage looks in the genome; it rapidly decays as we move away from the target (although the width and rate of this can vary).

Improving conservation management

In a similar fashion to demography, full genome datasets can improve our estimates of relatedness and pedigrees in captive breeding programs. The massive scale of whole genomes allows us to more easily trace the genealogical history of individuals, allowing us to assign parents more accurately. This also helps with our estimations of genetic relatedness, arguably the most critical aspect of genetic-based breeding programs. This is particularly helpful for species with tricky mating patterns, such as polyamory, brood spawning or difficult to track organisms.

Pedigrees
An example of how whole genomes can improve our estimation of pedigrees. Say we have a random individual (star), and we want to know how they fit into a particular family tree (pedigree). With only a few genes, we might struggle to pick where in the family it fits based on limited genetic information. With a larger genetic dataset (such as reduced-representation genomics), we might be able to cross off a few potential candidate spots but still have some trouble with a few places (due to unknown parents, polygamy or issues with genetic analysis). With whole genomes, we should be able to much better clarify the whole pedigree and find exactly where our star individual fits in the tree (red circle). It is thanks to whole genomes, we can do those ancestry analyses that have gone viral lately!

The way forwards

While many non-model species are still lacking in the available genomic information, whole genomes are progressively being sequenced for more and more species. As this astronomical dataset grows, our ability to investigate, discover and test theories about evolution, natural selection and conservation will also improve. Many projects already exist which aim specifically to increase the number of whole genomes available for certain taxonomic groups such as birds and bats: these will no doubt prove to be invaluable resources for future studies.

Not that kind of native-ity: endemism and invasion of Australia

The endemics of Australia

Australia is world-renowned for the abundant and bizarre species that inhabit this wonderful island continent. We have one of the highest numbers of unique species in the entire world (in the top few!): this is measured by what we call ‘endemism’. A species is considered endemic to a particular place or region if that it is the only place it occurs: it’s completely unique to that environment. In Australia, a whopping 87% of our mammals, 45% of our birds, 93% of our reptiles, 94% of our amphibians 24% of our fishes and 86% of our plants are endemic, making us a real biodiversity paradise! Some lists even label us as a ‘megadiverse country’, which sounds pretty awesome on paper. And although we traditionally haven’t been very good at looking after it, our array of species is a matter of some pride to Aussies.

Endemism map
A map representing the relative proportion of endemic species in Australia, generated through the Atlas of Living Australia. The colours range from no (white; 0% endemics) or little (blue) to high levels of endemism (red; 100% of species are endemic). As you can see, some biogeographic hotspots are clearly indicated (southwest WA, the east coast, the Kimberley ranges).

But the real question is: why are there so many endemics in Australia? What is so special about our country that lends to our unique flora and fauna? Although we naturally associate tropical regions with lush, vibrant and diverse life, most of Australia is complete desert. That said, most of our species are concentrated in the tropical regions of the country, particularly in the upper east coast and far north (the ‘Top End’).

There are a number of different factors which contribute to the high species diversity of Australia. Most notably is how isolated we are as a continent: Australia has been separated from most of the rest of the world for millions of years. In this time, the climate has varied dramatically as the island shifted northward, creating a variety of changing environments and unique ecological niches for species to specialise into. We refer to these species groups as ‘Gondwana relicts’, since their last ancestor with the rest of the world would have been distributed across the supercontinent Gondwana over 100 million years ago. These include marsupials, many birds groups (including ratites and megapodes), many fish groups and a plethora of others. A Gondwanan origin explains why they are only found within Australia, southern Africa and South America (the closest landmass that was also historically connected to Gondwana).

Early arrivals and naturalisation to the Australian ecosystem 

But not all of Australia’s species are so ancient and ingrained in the landscape. As Australia drifted northward and eventually collided with the Sunda plate (forming the mountain ranges across southeast Asia), many new species and groups managed to disperse into Australia. This includes the first indigenous people to colonise Australia, widely regarded as one of the oldest human civilisations and estimated to have arrived down under over 65 thousand years ago.

Eventually, this connection also brought with them one of our most iconic species; the dingo. Estimates of their arrival dates the migration at around 6 thousand years ago. As Australia’s only ‘native’ dog, there has been much debate about its status as an Australian icon. To call the dingo ‘native’ implies it’s always been there: but 6 thousand years is more than enough time to become ingrained within the ecosystem in a stable fashion. So, to balance the debate (and prevent the dingo from being labelled as an ‘invasive pest’ unfairly), we often refer to them as ‘naturalised’. This term helps us to disentangle modern-day pests, many of which our immensely destructive to the natural environment, from other species that have naturally migrated and integrated many years ago.

Patriotic dingo
Although it may not be a “true native”, the dingo will forever be a badge of our native species pride.

Invaders of the Australian continent

Of course, we can never ignore the direct impacts of humans on the ecosystem. Particularly with European settlement, another plethora of animals were introduced for the first time into Australia; these were predominantly livestock animals or hunting-related species (both as predators and prey). This includes the cane toad, widely regarded as one of the biggest errors in pest control on the planet.

When European settlers in the 1930s attempted to grow sugar cane in the far eastern part of the country, they found their crops decimated by a local beetle. In an effort to eradicate them, they brought over a species of cane toad, with the idea that they would control the beetle population and all would be well. Only, cane toads are particularly lazy and instead of targeting the cane beetles, they just thrived on all the other native invertebrates around. They’re also very resilient and adaptable (and highly toxic), so their numbers exploded and they’ve since spread across a large swathe of the country. Their toxic skin makes them fatal food objects for many native predators and they strongly compete against other similar native animals (such as our own amphibians). The cane toad introduction of 1935 is the poster child of how bad failed pest control can be.

DSC_0867_small
This guy here, he’s a bastard. Spotted in my parent’s backyard in Ipswich, QLD. Source: me, with spite.

But is native always better?

History tells a very stark tale about the poor native animals and the ravenous, rampaging pest species. Because of this, it is a widely adopted philosophical viewpoint that ‘native is always best’. And while I don’t disagree with the sentiment (of course we need to preserve our native wildlife, and not the massively overabundant pests), there are rare examples where nature is a little more complicated. In Australia, this is exemplified in the noisy miner.

The noisy miner is a small bird which, much like its name implies, is incredibly noisy and aggressive. It’s highly abundant, found predominantly throughout urban and suburban areas, and seems to dominate the habitat. It does this by bullying out other bird species from nesting grounds, creating a monopoly on the resource to the exclusion of many other species (even larger ones such as crows and magpies). Despite being native, it seems to have thrived on human alteration of the landscape and is a serious threat to the survival and longevity of many other species. If we thought of it solely under the ‘nature is best’ paradigm, we would dismiss the noisy miner as ‘doing what it should be.’ The truth is really more of a philosophical debate: is it natural to let the noisy miner outcompete many other natives, possibly resulting in their extinction? Or is it only because of human interference (and thus is our responsibility to fix) that the noisy miner is doing so well in the first place? It’s not a simple question to answer, although the latter seems to be incredibly important.

Noisy miner harassing currawong
An example of the aggressive behaviour of the noisy miner (top), swooping down on a pied currawong (bottom). Despite the size differences, noisy miners will frequently attempt to harass and scare off other larger birds. Image source: Bird Ecology Study Group website.

The amazing biodiversity of Australia is a badge of honour we should wear with patriotic pride. Conservation efforts of our endemic fauna are severely limited by a lack of funding and resources, and despite a general acceptance of the importance of diverse ecosystems we remain relatively ineffective at preserving it. Understanding and connecting with our native wildlife, whilst finding methods to control invasive species, is key to conserving our wonderful ecosystems.

Why we should always pander to diversity

Diversity in the natural world

‘Diversity’ is a term that gets used a lot these days, albeit usually in reference to social changes and structures. However, diversity is not merely a human construct and reflects an extremely important aspect of the natural world at a variety of levels. From the smallest genes to the biggest ecosystems, diversity is a trait that confers a massive range of benefits to individuals, populations, species and even the entire globe. Let’s dissect this diversity down at different scales and see how beneficial it can be.

Hierarchy of diversity
The generalised hierarchy at life, with diversity being an important component of each tier. At the smallest tier, genes underpin all life. The collection of genetic diversity is often summarised into a population (as a single cohesive genetic unit). Several populations can be pooled together into a single (usually) cohesive speciesDifferent species are then components of a larger community (which in turn are components of a broader ecosystem).

Genetic diversity

At the smallest scale in the hierarchy of genetic differentiation, we have the genes themselves. It is a well-established concept that having a diversity of genetic variants (alleles) within a population or species is critical to their future adaptation, evolution and persistance. This is because different alleles will have different benefits (or costs) depending on the environmental pressure that influences them; natural selection might favour one allele over another at one time, but a different one as the pressure changes. Having a higher number of alleles within the population or species means that there is a greater chance at least a few individuals will possess an adaptive gene with the changing environment (which we know can be quite rapid and very, very strong). The diversity serves as a ‘buffer’ against extinction; evolution by natural selection functions best when there are many options to choose from.

Without this diversity, species run the risk of having no adaptive genes at the ready to deal with a selective pressure. Either a new adaptive gene must mutate (or come about in other ways, such as through gene flow from another population or species) or the population/species will suffer and potentially go extinct. As strong selection causes the species to dwindle, it enters what is referred to as the ‘extinction vortex’. Without genetic diversity, they can’t adapt: thus, more individuals die off, causing more genetic diversity to be lost from the population. This pattern is a vicious cycle which can inevitably destroy species (without serious intervention).

Extinction vortex
A very dramatic representation of the extinction vortex.

For this reason, captive breeding programs aim to maintain as much of the genetic diversity of the original population as possible. This reduces the probability of entering a downward extinction spiral from inbreeding depression and helps to maintain populations into the future (both the captive one and the wild population when we reintroduce individuals into the wild).

“Population”  diversity

Because genetic diversity is critically important for species survival, we must also try to preserve the diversity of the entire gene pool of a species. This means conserving highly genetically differentiated populations within a species as a priority, as they may be the only ones that possess the necessary adaptive genes to save the rest of the species. This adaptive genetic variation can then be introduced into other populations in genetic rescue programs and serve as a means to semi-naturally allow the species to evolve. Evolutionarily-significant units (ESUs) are one measure of the invaluable nature of genetically unique populations.

Although many more traditional conservationists strongly believe that ESUs should be managed entirely independently of one another (to preserve their evolutionary ‘pedigree’ and prevent the risk of outbreeding depression), it has been suggested that the benefit of genetic rescue in many cases significantly outweighs this risk of outbreeding depression. For some species, this really is an act of rescue: they are at the edge of extinction, and if we do nothing we condemn them to die out.

Introducing genetic material across populations (or even species!) can generate new functional genes that allow the recipient species to adapt to selective pressures. This might sound very strange, and could be extremely rare, but examples of adaptive genetic material in one species originating from another species through hybridisation do exist in nature. For example, the black coat of wolves is a highly adaptive trait in some populations and is encoded for by the Melanocortin 1 receptor (Mc1r) gene. However, the specific mutation in Mc1r gene that generates the black coat colour actually first originated in domestic dogs; when wild wolves and domestic dogs interbred, this mutation was transferred into the wolf gene pool. Natural selection strongly favoured this new variant, and it very rapidly underwent strong positive selection. Thus, the adaptiveness of black wolves is thanks to a domestic dog mutation!

Species diversity

At a higher level of the hierarchy, the diversity of species within a particular community or ecosystem has been shown to be important for the health and stability of said community. Every species, however small or seemingly unimpressive, plays a role in the greater ecosystem balance, through interactions with other species (e.g. as predator, as prey, as competitor) and the abiotic environment. While some species are known to have very strong impacts on the immediate ecosystem (often dubbed ‘keystone species’, such as apex predators), all species have some influence on the world around them (we’re especially good at it).

Species interactions flowchart

The overall health and stability of an ecosystem, as well as the benefits it can provide to all living things (including humans) is largely determined by the diversity of species. For example, ‘habitat engineers’ are types of species that, by altering the physical environment around them (such as to build a home), directly provide new habitat for other species. They are a fundamental underpinning of many incredibly vibrant ecosystems; think of what a reef system would look like if there were no corals in it. There’d be no anemones growing colourfully; no fish to live in them; no sharks to feed on these non-existent fish. This is just one example of a complex ecosystem that truly relies on its inhabiting species to function.

Ecosystem jenga
Much like Jenga, taking out one block (a species) could cause the entire stack (the ecosystem) to collapse in on itself. Even if it stands up, however, the system will still be weaker without the full diversity to support it.

Protecting our diversity

Diversity is not just a social construct and is an important phenomenon in nature, at a variety of different levels. Preserving the full diversity of life, from genetic diversity within populations and species to full species diversity within ecosystems, is critical to maintaining healthy and robust natural systems. The more diversity we have at each level of this hierarchy, the greater robustness and security we will have in the future.

The history of histories: philosophy in biogeography

Biogeography of the globe

The distribution of organisms across the Earth, both over time and across space, is a fundamental aspect of the field of biogeography. But our understanding of the mechanisms by which organisms are distributed across the globe, and how this affects their evolution, can be at times highly enigmatic. Why are Australia and the Americas the only two places that have marsupials? How did lemurs get all the way to Madagascar, and why are they the only primate that has made the trip? How did Darwin’s famous finches get over to the Galápagos, and why are there so many species of them there now?

All of these questions can be addressed with a combination of genetic, environmental and ecological information across a variety of timescales. However, the overall field of biogeography (and phylogeography as a derivative of it) has traditionally been largely rooted on a strong yet changing theoretical basis. The earliest discussions and discoveries related to biogeography as a field of science date back to the 18th Century, and to Carl Linnaeus (to whom we owe our binomial classification system) and Alexander von Humboldt. These scientists (and undoubtedly many others of that era) were among the first to notice how organisms in similar climates (e.g. Australia, South Africa and South America) showed similar physical characteristics despite being so distantly separated (both in their groups and geographic distance). The communities of these regions also appeared to be highly similar. So how could this be possible over such huge distances?

Arctic and fennec final
A pretty unreasonable mechanism (and example) of dispersal in foxes. And yes, all tourists wear sunglasses and Hawaiian shirts, even arctic fox ones.

 

Dispersal or vicariance?

Two main explanations for these patterns are possible; dispersal and vicariance. As one might expect, dispersal denotes that an ancestral species was distributed in one of these places (referred to as the ‘centre of origin’) before it migrated and inhabited the other places. Contrastingly, vicariance suggests that the ancestral species was distributed everywhere originally, covering all contemporary ranges within it. However, changes in geography, climate or the formation of other barriers caused the range of the ancestor to fragment, with each fragmented group evolving into its own distinct species (or group of species).

Dispersal vs vicariance islands
An example of dispersal vs. vicariance patterns of biogeography in an island bird (pale blue). In the top example, the sequential separation of parts of the island also cause parts of the distribution of the original bird species to become fragmented. These fragments each evolve independently of their ancestor and form new species (red, and then blue). In the bottom example, the island geography doesn’t change but in rare events a bird disperses from the main island onto a new island. The new selective pressures of that island cause the dispersed birds to evolve into new species (red and blue). In both examples, islands that were recently connected or are easy to disperse across do not generate new species (in the sandy island in the bottom right). You’ll notice that both processes result in the same biogeographic distribution of species.

In initial biogeographic science, dispersal was the most heavily favoured explanation. At the time, there was no clear mechanism by which organisms could be present all over the globe without some form of dispersal: it was generally believed that the world was a static, unmoving system. Dispersal was well supported by some biological evidence such as the diversification of Darwin’s finches across the Galápagos archipelago. Thus, this concept was supported through the proposals of a number of prominent scientists such as Charles Darwin and A.R. Wallace. For others, however, the distance required for dispersal (such as across entire oceans) seemed implausible and biologically unrealistic.

 

A paradigm shift in biogeography

Two particular developments in theory are credited with a paradigm shift in the field; cladistics and plate tectonics. Cladistics simply involved using shared biological characteristics to reconstruct the evolutionary relationships of species (think like phylogenetics, but using physical traits instead of genetic sequence). Just as importantly, however, was plate tectonic theory, which provided a clear way for organisms to spread across the planet. By understanding that, deep in the past, all continents had been directly connected to one another provides a convenient explanation for how species groups spread. Instead of requiring for species to travel across entire oceans, continental drift meant that one widespread and ancient ancestor on the historic supercontinent (Pangaea; or subsequently Gondwana and Laurasia) could become fragmented. It only required that groups were very old, but not necessarily very dispersive.

Lemur dispersal
Surf’s up, dudes! Although continental drift was no doubt an important factor in the distribution and dispersal of many organisms on Earth, it actually probably wasn’t the reason lemurs got to Madagascar. Sorry for the mislead.

From these advances in theory, cladistic vicariance biogeography was born. The field rapidly overtook dispersal as the most likely explanation for biogeographic patterns across the globe by not only providing a clear mechanism to explain these but also an analytical framework to test questions relating to these patterns. Further developments into the analytical backbone of cladistic vicariance allowed for more nuanced questions of biogeography to be asked, although still fundamentally ignored the role of potential dispersals in explaining species’ distributions.

Modern philosophy of biogeography

So, what is the current state of the field? Well, the more we research biogeographic patterns with better data (such as with genomics) the more we realise just how complicated the history of life on Earth can be. Complex modelling (such as Bayesian methods) allow us to more explicitly test the impact of Earth history events on our study species, and can provide more detailed overview of the evolutionary history of the species (such as by directly estimating times of divergence, amount of dispersal, extent of range shifts).

From a theoretical perspective, the consistency of patterns of groups is always in question and exactly what determines what species occurs where is still somewhat debatable. However, the greater number of types of data we can now include (such as geological, paleontological, climatic, hydrological, genetic…the list goes on!) allows us to paint a better picture of life on Earth. By combining information about what we know happened on Earth, with what we know has happened to species, we can start to make links between Earth history and species history to better understand how (or if) these events have shaped evolution.

Surviving the Real-World Apocalypse

The changing world

Climate change seems to be the centrefold of a large amount of scientific research and media attention, and rightly so: it has the capacity to affect every living organism on the planet. It’s our duty as curators and residents of Earth to be responsible for our influences on the global environmental stage. While a significant part of this involves determining causes and solutions to our contributions to climate change, we also need to know how extensive the effects will be: for example, how can we predict how well species will do in the future?

Predicting the effect of climate change on all of the world’s biodiversity is an immense task. Climate change itself is a complicated system, and causes diverse, interconnected and complex alterations to both global and local climate. Adding on top of this, though, is that climate affects different species in different ways; where some species might be sensitive to some climatic variables (such as rainfall, available sunlight, seasonality), others may be more tolerant to the same factors. But all living things share some requirements, so surely there must be some consistency in their responses to climate change, right?

Apocalypse 2
Lucky for Mr Fish here, he’s responding to a (very dramatic) climate change much, much better than his bird counterpart.

How predictable are species responses to climate change?

Well, evidence would surprisingly suggest not. Many species, even closely related ones, can show very different responses to the exact same climatic pressures or biogeographical events. There are a number of different traits that might affect a species’ ability to adapt, particularly their adaptive genetic diversity (which underpins ‘adaptive potential’). Thus, we need good information of a variety of genetic, physiological and life history traits to be able to make predictions about how likely a species is to adapt and respond to future (and current) climate changes.

Although this can be hard to study in species of high extinction risk (getting a good number of samples is always an issue…), traditional phylogeographic methods might help us to make some comparisons. See, although the modern Earth is rapidly changing (undoubtedly influenced by human society), the climate of the globe has always varied to some degree. There has always been some tumultuousness in the climate and specific Earth history events like volcano eruptions, sea-level changes, or glaciation periods (‘ice ages’) have had diverse effects on organisms globally.

Using comparative phylogeography to predict species responses

One tool for looking at how different species have, in the past, responded to the same biogeographical force is the domain of ‘comparative phylogeography’. Phylogeography itself is something we have discussed before: the ‘comparative’ aspect simply means comparing (with complex statistical methods) these patterns across different and often unrelated species to see how universal (‘congruent’) or unique (‘incongruent’) these patterns are among species. The more broadly we look at the species community in the region, the more we can observe widespread effects of any given environmental or geographical event: if we only look at fish, for example, we might not to be able to infer what response mammals, birds or invertebrates have had to our given event. Sometimes this still meets the scale we wish to focus; other times, we want to see how all the species of an area have been affected.

Actual island diagram
An (very busy) example of different species responses to a single environmental event. In this example, we have three species (a fish, a lizard, and a bird) all living on the same island. In the middle of the island, there is a small mountain range (A). At this point in time, all three species are connected across the whole island; fish can travel via lakes and wetlands (green arrows), lizards can travel across the land (blue arrow) and birds can fly anywhere. However, as the mountain range grows with tectonic movements, the waterways are altered and the north and south are disconnected (B). The fish species is now split into two evolutionarily separate groups (green and gold), while lizards and birds are not. As the range expands further, however, the dispersal route for lizards is cut off, causing them to eventually also become separated into blue and black groups (C). Birds, however, have no problems flying over the mountain range and remain one unified and connected orange group over time (D). Thus, each species has a different response to the formation of the mountain range.
Evol history of island diagram
The phylogenetic history of the three different species in the above example. As you can see, each lineage has a slightly different pattern; birds show no divergences at all, whereas the timing of the lizard and fish N/S splits are different (i.e. temporally incongruent).

Typically, comparative phylogeographic studies have looked at the neutral components of species’ evolution (as is the realm of traditional phylogeography). This includes studying the size of populations over time, how well connected they are and were, what their spatial patterns are and how these relate to the environment. Comparing all of these patterns across species can allow us to start painting a fuller picture of the history of biota in a region. In this way, we can start to see exactly which species have shown what responses and start to relate these to the characteristics that allowed them to respond in that certain way (and including adaptation in our studies). So, what kinds of traits are important?

What traits matter? Who wins?

Often, we find that life history traits of an organism better dictates how they will respond to a certain pressure than other factors such as phylogeny (e.g. one group does not always do better than another). Instead, individual species with certain physical characteristics might handle the pressure better than others. For example, a fish, bird and snake that are all able to tolerate higher temperatures than other fish, birds or snakes in that region are more likely to survive a drought. In this case, none of the groups (fish, birds or snakes) inherently do better than the other two groups. Thus, it can be hard to predict how a large swathe of species will respond to any given environmental change, unless we understand the physical characteristics of every species.

Climate change risk flowchart
A generalised framework of various factors, and their interactions, on the vulnerability of species under current and future climate changes by Williams et al. 2018. The schematic includes genetic, ecological, physical and environmental factors and how these can interact with one another to alleviate or exacerbate the risk of extinction.

We can also see that other physiological or ecological traits, such as climatic preferences and tolerance thresholds, can be critical for adapting to climatic pressures. Naturally, the genetic diversity of species is also an important component underlying their ability to adapt to these new selective pressures and to survive into the future. Trying to incorporate all of these factors into a projected model can be difficult, but with more data of higher quality we can start to make more refined predictions. But by understanding how particular traits influence how well a species may adapt to a changing climate, as well as knowing the what traits different species have, might just be the key to predicting who wins and who dies in the real-world Game of Thrones.

The many genetic faces of adaptation

The transition from genotype to phenotype

While evolutionary genetics studies often focus on the underlying genetic architecture of species and populations to understand their evolution, we know that natural selection acts directly on physical characteristics. We call these the phenotype; by studying changes in the genes that determine these traits (the genotype), we can take a nuanced approach at studying adaptation. However, our ability to look at genetic changes and relate these to a clear phenotypic trait, and how and why that trait is under natural selection, can be a difficult task.

One gene for one trait

The simplest (and most widely used) models of understanding the genetic basis of adaptation assume that a single genotype codes for a single phenotypic trait. This means that changes in a single gene (such as outliers that we have identified in our analyses) create changes in a particular physical trait that is under a selective pressure in the environment. This is a useful model because it is statistically tractable to be able to identify few specific genes of very large effect within our genomic datasets and directly relate these to a trait: adding more complexity exponentially increases the difficulty in detecting patterns (at both the genotypic and phenotypic level).

Single locus figure
An example of a single gene coding for a single phenotypic trait. In this example, the different combination of alleles of the one gene determines the colour of the cat.

Many genes for one trait: polygenic adaptation

Unfortunately, nature is not always convenient and recent findings suggest that the overwhelming majority of the genetics of adaptation operate under what is called ‘polygenic adaptation’. As the name suggestions, under this scenario changes (even very small ones) in many different genes combine together to have a large effect on a particular phenotypic trait. Given the often very small magnitude of the genetic changes, it can be extremely difficult to separate adaptive changes in genes from neutral changes due to genetic drift. Likewise, trying to understand how these different genes all combine into a single functional trait is almost impossible, especially for non-model species.

Polygenic adaptation is often seen for traits which are clearly heritable, but don’t show a single underlying gene responsible. Previously, we’ve covered this with the heritability of height: this is one of many examples of ‘quantitative trait loci’ (QTLs). Changes in one QTL (a single gene) causes a small quantitative change in a particular trait; the combined effect of different QTLs together can ‘add up’ (or counteract one another) to result in the final phenotype value.

Height QTL
An example of polygenic quantitative trait loci. In this example, height is partially coded for by a total of ten different genes: the dominant form of each gene (Capitals, green) provides more height whereas the recessive form (lowercase, red) doesn’t. The cumulative total of these components determines how tall the person is: the person on the far right was very unlucky and got 0/10 height bonuses and so is the shortest. Progressively from left to right, some genes are contributing to the taller height of the people, with the far right person standing tall with the ultimate 10/10 pro-height genes. For reference, height is actually likely to be coded for by thousands of genes, not 10.

The mechanisms which underlie polygenic adaptation can be more complex than simple addition, too. Individual genes might cause phenotypic changes which interact with other phenotypes (and their underlying genotypes) to create a network of changes. We call these interactions ‘epistasis’, where changes in one gene can cause a flow-on effect of changes in other genes based on how their resultant phenotypes interact. We can see this in metabolic pathways: given that a series of proteins are often used in succession within pathways, a change in any single protein in the process could affect every other protein in the pathway. Of course, knowing the exact proteins coded for every gene, including their physical structure, and how each of those proteins could interact with other proteins is an immense task. Similar to QTLs, this is usually limited to model species which have a large history of research on these specific areas to back up the study. However, some molecular ecology studies are starting to dive into this area by identifying pathways that are under selection instead of individual genes, to give a broader picture of the overall traits that are underlying adaptation.

Labrador epistasis figure
My favourite example of epistasis on coat colour in labradors. Two genes together determine the colour of the coat, with strong interactions between them. The first gene (E/e) determines whether or not the underlying coat gene (B/b) is masked or not: two recessive alleles of the first gene (ee) completely blocks Gene 2 and causes the coat to become golden regardless of the second gene genotype (much like my beloved late childhood pet pictured, Sunny). If the first gene has at least one dominant allele, then the second gene is allowed to express itself. Possessing a dominant allele (BB or Bb) leads to a black lab; possessing two recessive alleles (bb) makes a choc lab!
Labrador epistasis table
The possible combinations of genotypes for the two above genes and the resultant coat colour (indicated by the box colour).

One gene for many traits: pleiotropy and differential gene expression

In contrast to polygenic traits, changes in a single gene can also potentially alter multiple phenotypic traits simultaneously. This is referred to as ‘pleiotropy’ and can happen if a gene has multiple different functions within an organism; one particular protein might be a component of several different systems depending on where it is found or how it is arranged. A clear example of pleiotropy is in albino animals: the most common form of albinism is the result of possessing two recessive alleles of a single gene (TYR). The result of this is the absence of the enzyme tyrosinase in the organism, a critical component in the production of melanin. The flow-on phenotypic effects from the recessive gene most obviously cause a lack of pigmentation of the skin (whitening) and eyes (which appear pink), but also other physiological changes such as light sensitivity or total blindness (due to changes in the iris). Albinism has even been attributed to behavioural changes in wild field mice.

Albinism pleiotropy
A very simplified diagram of how one genotype (the albino version of the TYR gene) can lead to a large number of phenotypic changes via pleiotropy (although many are naturally physiologically connected).

Because pleiotropic genes code for several different phenotypic traits, natural selection can be a little more complicated. If some resultant traits are selected against, but others are selected for, it can be difficult for evolution to ‘resolve’ the balance between the two. The overall fitness of the gene is thus dependent on the balance of positive and negative fitness of the different traits, which will determine whether the gene is positively or negatively selected (much like a cost-benefit scenario). Alternatively, some traits which are selectively neutral (i.e. don’t directly provide fitness benefits) may be indirectly selected for if another phenotype of the same underlying gene is selected for.

Multiple phenotypes from a single ‘gene’ can also arise by alternate splicing: when a gene is transcribed from the DNA sequence into the protein, the non-coding intron sections within the gene are removed. However, exactly which introns are removed and how the different coding exons are arranged in the final protein sequence can give rise to multiple different protein structures, each with potentially different functions. Thus, a single overarching gene can lead to many different functional proteins. The role of alternate splicing in adaptation and evolution is a rarely explored area of research and its importance is relatively unknown.

Non-genes for traits: epigenetics

This gets more complicated if we consider ‘non-genetic’ aspects underlying the phenotype in what we call ‘epigenetics’. The phrase literally translates as ‘on top of genes’ and refers to chemical attachments to the DNA which control the expression of genes by allowing or resisting the transcription process. Epigenetics is a relatively new area of research, although studies have started to delve into the role of epigenetic changes in facilitating adaptation and evolution. Although epigenetics is still a relatively new research topic, future research into the relationship between epigenetic changes and adaptive potential might provide more detailed insight into how adaptation occurs in the wild (and might provide a mechanism for adaptation for species with low genetic diversity)!

 

The different interactions between genotypes, phenotypes and fitness, as well as their complex potential outcomes, inevitably complicates any study of evolution. However, these are important aspects of the adaptation process and to discard them as irrelevant will not doubt reduce our ability to examine and determine evolutionary processes in the wild.

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.

Fantastic Genes and Where to Find Them

The genetics of adaptation

Adaptation and evolution by natural selection remains one of the most significant research questions in many disciplines of biology, and this is undoubtedly true for molecular ecology. While traditional evolutionary studies have been based on the physiological aspects of organisms and how this relates to their evolution, such as how these traits improve their fitness, the genetic component of adaptation is still somewhat elusive for many species and traits.

Hunting for adaptive genes in the genome

We’ve previously looked at the two main categories of genetic variation: neutral and adaptive. Although we’ve focused predominantly on the neutral components of the genome, and the types of questions about demographic history, geographic influences and the effect of genetic drift, they cannot tell us (directly) about the process of adaptation and natural selective changes in species. To look at this area, we’d have to focus on adaptive variation instead; that is, genes (or other related genetic markers) which directly influence the ability of a species to adapt and evolve. These are directly under natural selection, either positively (‘selected for’) or negatively (‘selected against’).

Given how complex organisms, the environment and genomes can be, it can be difficult to determine exactly what is a real (i.e. strong) selective pressure, how this is influenced by the physical characteristics of the organism (the ‘phenotype’) and which genes are fundamental to the process (the ‘genotype’). Even determining the relevant genes can be difficult; how do we find the needle-like adaptive genes in a genomic haystack?

Magnifying glass figure
If only it were this easy.

There’s a variety of different methods we can use to find adaptive genetic variation, each with particular drawbacks and strengths. Many of these are based on tests of the frequency of alleles, rather than on the exact genetic changes themselves; adaptation works more often by favouring one variant over another rather than completely removing the less-adaptive variant (this would be called ‘fixation’). So measuring the frequency of different alleles is a central component of many analyses.

FST outlier tests

One of the most classical examples is called an ‘FST outlier test’. This can be a bit complicated without understanding what FST is actually measures: in short terms, it’s a statistical measure of ‘population differentiation due to genetic structure’. The FST value of one particular population can determine how genetically similar it is to another. An FST value of 1 implies that the two populations are as genetically different as they could possibly be, whilst an FST value of 0 implies that they are genetically identical populations.

Generally, FST reflects neutral genetic structure: it gives a background of how, on average, different are two populations. However, if we know what the average amount of genetic differentiation should be for a neutral DNA marker, then we would predict that adaptive markers are significantly different. This is because a gene under selection should be more directly pushed towards or away from one variant (allele) than another, and much more strongly than the neutral variation would predict. Thus, the alleles that are way more or less frequent than the average pattern we might assume are under selection. This is the basis of the FST outlier test; by comparing two or more populations (using FST), and looking at the distribution of allele frequencies, we can pick out a few alleles that vary from the average pattern and suggest that they are under selection (i.e. are adaptive).

There are a few significant drawbacks for FST outlier tests. One of the most major ones is that genetic drift can also produce a large number of outliers; in a small population, for example, one allele might be fixed (has a frequency of 1, with no alternative allele in the population) simply because there is not enough diversity or population size to sustain more alleles. Even if this particular allele was extremely detrimental, it’d still appear to be favoured by natural selection just because of drift.

Drift leading to outliers diagram
An example of genetic drift leading to outliers, featuring our friends the cat population. Top row: Two cat populations, one small (left; n = 5) and one large (middle, n = 12) show little genetic differentiation between them (right; each triangle represents a single gene or locus; the ‘colour’ gene is marked in green). The average (‘neutral’) pattern of differentiation is shown by the dashed line. Much like in our original example, one cat in the small population is horrifically struck by lightning and dies (RIP again). Now when we compare the frequency of the alleles of the two populations (bottom), we see that (because a green cat died), the ‘colour’ locus has shifted away from the general trend (right) and is now an outlier. Thus, genetic drift in the ‘colour’ gene gives the illusion of a selective loci (even though natural selection didn’t cause the change, since colour does not relate to how likely a cat is to be struck by lightning).

Secondly, the cut-off for a ‘significant’ vs. ‘relatively different but possibly not under selection’ can be a bit arbitrary; some genes that are under weak selection can go undetected. Furthermore, recent studies have shown a growing appreciation for polygenic adaptation, where tiny changes in allele frequencies of many different genes combine together to cause strong evolutionary changes. For example, despite the clear heritable nature of height (tall people often have tall children), there is no clear ‘height’ gene: instead, it appears that hundreds of genes are potentially very minor height contributors.

Polygenic height figure final
In this example, we have one tall parent (top) who produces two offspring; one who is tall (left) and one who isn’t (right). In order to understand what genetic factors are contributing to their height differences, we compare their genetics (right; each dot represents a single locus). Although there aren’t any particular loci that look massively different between the two, the cumulative effect of tiny differences (the green triangles) together make one person taller than the other. There are no clear outliers, but many (poly) different genes (genic) acting together.

Genotype-environment associations

To overcome these biases, sometimes we might take a more methodological approach called ‘genotype-environment association’. This analysis differs in that we select what we think our selective pressures are: often environmental characteristics such as rainfall, temperature, habitat type or altitude. We then take two types of measures per individual organism: the genotype, through DNA sequencing, and the relevant environmental values for that organisms’ location. We repeat this over the full distribution of the species, taking a good number of samples per population and making sure we capture the full variation in the environment. Then we perform a correlation-type analysis, which seeks to see if there’s a connection or trend between any particular alleles and any environmental variables. The most relevant variables are often pulled out of the environmental dataset and focused on to reduce noise in the data.

The main benefit of GEA over FST outlier tests is that it’s unlikely to be as strongly influenced by genetic drift. Unless (coincidentally) populations are drifting at the same genes in the same pattern as the environment, the analysis is unlikely to falsely pick it up. However, it can still be confounded by neutral population structure; if one population randomly has a lot of unique alleles or variation, and also occurs in a somewhat unique environment, it can bias the correlation. Furthermore, GEA is limited by the accuracy and relevance of the environmental variables chosen; if we pick only a few, or miss the most important ones for the species, we won’t be able to detect a large number of very relevant (and likely very selective) genes. This is a universal problem in model-based approaches and not just limited to GEA analysis.

New spells to find adaptive genes?

It seems likely that with increasing datasets and better analytical platforms, many more types of analysis will be developed to delve deeper into the adaptive aspects of the genome. With whole-genome sequencing starting to become a reality for non-model species, better annotation of current genomes and a steadily increasing database of functional genes, the ability of researchers to investigate evolution and adaptation at the genomic level is also increasing.