A Primer on Evolution pt 3: Higher Concepts

What follows are more conceptual aspects of evolution that build on the ideas discussed in the part 1. It’s not absolutely necessary, but I would recommend checking out part 2 first as well. In this conclusion to my three-part primer on evolution, I will discuss things like reproductive isolation, the different ways that evolution occurs, sexual selection, ecology, chaos theory, and evolutionary equilibrium.

Modern Synthesis

Charles Darwin formulated the theory of evolution by natural selection between his participation in the second voyage of the HMS Beagle and the publication of “On the Origin of Species” in 1859. In 1854, Gregor Mendel performed experiments mating pea plants, where he discovered rules of inheritance, which are as follows:

1) The Law of Segregation: Each inherited trait is defined by a gene pair. Parental genes are randomly separated to the sex cells so that sex cells contain only one gene of the pair. Offspring therefore inherit one genetic allele from each parent when sex cells unite in fertilization.

2) The Law of Independent Assortment: Genes for different traits are sorted separately from one another so that the inheritance of one trait is not dependent on the inheritance of another.

3) The Law of Dominance: An organism with alternate forms of a gene will express the form that is dominant.

Neither Darwin nor Mendel were aware of each others work. It wasn’t until the twentieth century where the two ideas were combined into what is often referred to as the Modern Synthesis. Simply put, the Modern Synthesis states that genetic mutation supplies the variation and natural selection culls those variants that are less able to reproduce. It was through this idea that scientists searched for the ‘unit’ of inheritance, which we now know is the gene. Now it is commonly understood that nothing in biology would make sense but for these two principles.

The Selfish Gene:

“The Selfish Gene” by Richard Dawkins lays out a theoretical way of understanding evolution from what Dawkins calls a ‘gene’s eye view’ of evolution. The ‘gene’s eye view’ is thinking about genes as the unit of selection. A gene that helps an organism survive long enough to reproduce will get passed on; a gene that doesn’t confer enough fitness will be eliminated. Therefore, it is not the individual organism or the species that is trying to survive, but the individual genes.

The gene-centred view of evolution that Dawkins championed and crystallized is now central both to evolutionary theorizing and to lay commentaries on natural history such as wildlife documentaries. A bird or a bee risks its life and health to bring its offspring into the world not to help itself, and certainly not to help its species — the prevailing, lazy thinking of the 1960s, even among luminaries of evolution such as Julian Huxley and Konrad Lorenz — but (unconsciously) so that its genes go on. Genes that cause birds and bees to breed survive at the expense of other genes. No other explanation makes sense, although some insist that there are other ways to tell the story (see K. Laland et al. Nature 514, 161–164; 2014).

There is a common misconception that the selfish gene is either referring to a gene for selfishness or that it means people ought view the world as genes do – to succeed (ie make money) even at other people’s expense. Neither of these are true. The Selfish Gene is merely a way to anthropomorphize how genes propagate.

The Red Queen Hypothesis:

In Lewis Carroll’s “Through the Looking Glass” the Red Queen explains the Looking-Glass Land thusly: “Now, here, you see, it takes all the running you can do, to keep in the same place.” This is where the Red Queen Hypothesis in evolution gets its name.

The Red Queen Hypothesis describes the evolutionary arms race between species competing in a particular habitat. A hypothetical example might be an ant that eats a particular type of plant, so only the more toxic versions of the plant remain uneaten and therefore propagate. The plant has then evolved to be resistant to the ants. Many ant colonies die off, except the ones that can continue eating the plant due to resistance. These resistant ants then propagate, thus evolving to be able to eat the plant again. Both organisms underwent evolutionary selection pressures, yet both ended up back in the same place as before.

The Red Queen Hypothesis was a way to explain the rate of extinction in the fossil record. Because organisms in an environment are constantly evolving due to this arms race, they will constantly be changing, with the prior forms dying off. In my hypothestical example above, both the first version of the plants and the ants go extinct, with the new variants originating via evolution. This explains the prevalence of extinction in the fossil record.

The Red Queen Hypothesis has also been used to explain the prevalence of sexual reproduction as opposed to asexual reproduction. Sexual reproduction allows for faster rates of evolution and sexual selection allows parasitized members of a species to be selected out (ie a parasitized member will be less sexually appealing and therefore won’t pass the parasite on to offspring).

Reproductive Isolation:

Reproductive isolation does not necessarily mean that two organisms are separated from each other spatially. Reproductive isolation is when two organisms are either unable to breed, or do not breed for other reasons.

reproductive-isolation-deer

Spatial Isolation is when a population of organisms is split up due to geography, and then face different selection pressures. One example of this is antelope squirrel, which has speciated due to the grand canyon.

Squirrel

Behavioral Isolation is when two populations, because of facing differing sexual selection pressures, will acquire different mating rituals and behaviors. Some organisms within a population will not breed with another organism if it doesn’t have the same mating rituals. In the birds in the following picture, the mating ritual in the left differs from the mating ritual on the right, and if a bird (even though they look the same) tries to present the ritual between the two variations, the female will not breed with them.

Meadowlarks

Mechanical Isolation is pretty self explanatory. One could say a form of speciation has happened between a great dane and a chihuahua, because even though their seed is still viable, it’s almost logistically impossible for them to breed.

Temporal Isolation occurs when two organisms have different breeding times. This is separation in time. As the above chart mentioned, flowers bloom at different times of year, and therefore will not cross pollinate. In this way, two species can be reproductively isolated, yet live side-by-side.

Types of Evolution:

350px-speciation_modes-svg

Allopatric Evolution:
This is the most basic form of evolution. When a population of organisms is separated by physical barriers, they will face different selection pressures that select for different alleles. Over time, the split population will diverge enough that if the two populations ever crossed paths again, they would be unable to interbreed (or they may breed, but they would produce sterile hybrids, like the liger or mule). Peripatric evolution is a form of allopatric evolution, but when one population is significantly smaller than the other.

Sympatric Evolution:
This is when organisms evolve in either overlapping or identical environments. This is very similar to parapatric speciation, which is generally referred to when behavioral sexual isolation occurs. One way in which sympatric evolution occurs is in a rain forest, there are several different environments – for example, the canopy and the ground. A single population of insects may separate into two, with one facing different selection pressures in the canopy while the others face a very different pressure on the ground. There is also the famous (in biology circles) Chiclid fish in Africa.

index
Source

In three lakes of Africa’s Rift Valley, a member of a family of fish named cichlids has evolved a range of ecologies and sizes unmatched anywhere else. Those lakes are known to have formed no later than 1.5-2 million years ago, and the hundreds of species of fish in those lakes occupy ecological niches, and exhibit biological forms, unheard of elsewhere. (One species specializes in eating the eyes of other fish.) The range is greater than what you might find at a coral reef, and all from a small number of evolutionary starting points.

Sexual Selection:

Peacock

This is a theory that Darwin came up with after natural selection – although the two are under the same umbrella of evolution. The story goes that Darwin was bothered by the peacock:

‘It is curious that I remember well time when the thought of the eye made me cold all over, but I have got over this stage of the complaint, and now small trifling particulars of structure often make me very uncomfortable. The sight of the peacock’s tail, whenever I gaze it, makes me sick!’
Darwin, Charles correspondence 8, 140pp

This is because the tail of the peacock, being so ostentatious and requiring such upkeep would seemingly be detrimental to an organisms survival. This is when he came up with the theory of sexual selection, which is when organisms (usually females) choose male mates for certain traits or behaviors that portray that they have good, healthy genes. A male peacock with the biggest plumage will be a peacock that is healthy and well fed, and therefore have the most fit genes.

This is an interesting (and quite humorous) scientific article where they tested the effect of ovulation on the tip earnings of strippers – with telling results.

YouTube- Evolution Sweaty T-shirts and Human Mate Choice

Ecology

Evolution ensures what people often times call the balance of nature. Why are there so many herbivores and only a few carnivores? Why are plants so important to the environment? Why is over-hunting so deleterious to an environment?

The above picture shows the 90% reduction in kilocalories every time we move up a level in the “food chain”. Herbivores only get 10% of the kilocalories that the plants produce. This, obviously, is because plants have to use most of the calories they produce for their own metabolic functions, and not all of the calories the herbivore takes in will be used – some of it will be excreted as waste. This is decreased once again with carnivores, who only get 10% of the calorie efficiency of the herbivores, as the herbivores also use most of their own caloric intake for metabolic functions.

It’s because of this that nature maintains a tenuous ‘balance,’ with carnivores being few and far between, requiring large hunting ranges; herbivores are much more common, and plants are (ideally) very plentiful. This is an idea known as the carrying capacity.

population-growth-and-carrying-capacity-diagram

Carrying capacity is the maximum number of organisms occupying a particular niche that a given environment can sustain. Too many and the population will decrease due to insufficient resources; lower than carrying capacity and the population will increase due to abundant resources.

Cooperation:

The evolutionary benefit of intraspecies cooperation isn’t immediately obvious. One organism must give up some of its own resources and possibly risk losing its own opportunity to reproduce by cooperating with other members of its own species. However, if genes that increase cooperativity between members of a species increase the chance of that gene being passed on, it becomes clearer why cooperation would evolve. Other genes that make the cooperation genes survive will also propagate.

Further reading: “The Evolution of Reciprocal Altruism” by Robert Trivers

We can use humans as an example. Lets say there are three people, person A, person B, and person C, who form a tribe. Person A would obviously benefit if everything they hunted and gathered, they kept for themselves. From a selfish gene perspective, it seems like person A might have a better chance of living until they have the opportunity to pass on their genes if every calorie of work they put in, they reaped all the benefits. That is, unless person A becomes sick or injured. Then persons B and C could be there for acquire food and stave off predators while person A recuperates. Also, there could be a greater amount of calories hunted and gathered through cooperation.

So, then why aren’t all organisms cooperative? One reason may be that the evolutionary ‘equilibrium’ (never truly an equilibrium – see Hardy-Weinberg below) may occasionally result in a sort of Braess’s paradox, where those organisms who do not cooperate get more benefit than those who do and thereby out-compete them. It may also be that cooperation occasionally results in too many free riders, which results in a breakdown of cooperativity within a group, or when cooperativity is still nascent. And surely there are just tradeoffs to cooperation that may, in some instances and/or in some niches just not balance out.

Phyletic Gradualism vs Punctuated Equilibrium:

Phyletic gradualism is the idea that evolution occurs in a slow, continuous process. Punctuated equilibrium is the idea that species remain relatively stable (stasis) most of the time and evolution occurs only in short periods of rapid change.

Punctuations-versus-gradualism-1024x494

The theory as envisioned by Darwin was gradualism. Punctuated equilibrium is a theory proposed by Eldredge and Gould in 1972 based on evidence in the fossil record that seems to show some organisms maintaining morphological stasis for long periods of time.

Proposed mechanisms that could potentially maintain stasis for extended periods of time are habitat tracking, stabilizing selection (1)(2), the Stenseth-Maynard Smith stability hypothesis, and koinophilia (1)(2).

Whether phyletic gradualism or punctuated equilibrium is the dominant mode of speciation is still not settled. However, the answer seems to be a mixture of the two, with some species leaning toward one or the other.

Evolvability:

Evolvability is essentially how well beneficial adaptations can be gained. Most mutations are going to be neutral or detrimental. Evolvability is the way the genome-phenotype relationship is carried out, such that changes in the genotype are more likely to confer beneficial changes to the phenotype. This is done largely through gene regulation.

Evolvability is an organism’s capacity to generate heritable phenotypic variation. Metazoan evolution is marked by great morphological and physiological diversification, although the core genetic, cell biological, and developmental processes are largely conserved. Metazoan diversification has entailed the evolution of various regulatory processes controlling the time, place, and conditions of use of the conserved core processes. These regulatory processes, and certain of the core processes, have special properties relevant to evolutionary change. The properties of versatile protein elements, weak linkage, compartmentation, redundancy, and exploratory behavior reduce the interdependence of components and confer robustness and flexibility on processes during embryonic development and in adult physiology. They also confer evolvability on the organism by reducing constraints on change and allowing the accumulation of nonlethal variation. Evolvability may have been generally selected in the course of selection for robust, flexible processes suitable for complex development and physiology and specifically selected in lineages undergoing repeated radiations

(Source)

Life On The Edge Of Chaos and Sensitivity To Initial Conditions:

Deep in the chaotic regime, slight changes in structure almost always cause vast changes in behavior. Complex controllable behavior seems precluded.
-Stuart Kauffman
Of self-organizing behaviors, two are of particular interest to the study of evolution. One is adaptation. We see it everywhere. Corporations adapt to the marketplace, brain cells adapt to signal traffic, the immune system adapts to infection, animals adapt to their food supply. We have come to think that the ability to adapt is characteristic of complex systems, and may be one reason why evolution seems to lead toward more complex organisms. But even more important is the way complex systems seem to strike a balance between the need for order and the imperative to change. Complex systems tend to locate themselves at a place we call ‘The Edge of Chaos’. We imagine the edge of chaos as a place where there is enough innovation to keep a living system vibrant, and enough stability to keep it from collapsing into anarchy. It is a zone of conflict and upheaval, where the old and the new are constantly at war. Finding the balance point must be a delicate matter. If a living system drifts too close, it risks falling over into incoherence and dissolution; but if the system moves too far away from the edge, it becomes rigid, frozen, and totalitarian. Both conditions lead to extinction. Too much change is as destructive as too little. Only at the edge of chaos can complex systems flourish.
-Michael Crichton

This is a theoretical model of evolution that says that the “balance of nature” maintains a place on the edge between chaos and stagnation. It’s in this area that complexity can arise, that evolution can innovate new solutions to selection pressures.

Of course, life doesn’t follow a single line across the edge of chaos, but fluctuates as the complex dynamic system evolves, subject to the sensitivity of initial (or previous) conditions. Complex dynamic systems are non-linear systems, essentially meaning that the output will be disproportional to the input, and do not have single cause-and-effect variables.

What this means is that a change in a single variable (for example, a small change in an environments climate, or the introduction/extinction of a single species) will have unpredictable and disproportional effects on the system. The popular example of this is the butterfly effect – a small input (the butterfly flaps its wings) has a disproportionate output (causes a hurricane or some other large impact elsewhere).

This is on account of the sensitivity of initial conditions, which is often represented with a logistic map:

Logistic Map
r = a single number representing birth rate and death rate.
x = carrying capacity of population.

Small changes in r (birth rate and death rate) creates large distortions in the logistic map of a population when plotted on a graph.

logisticcobwebchaos
A cobweb diagram of the logistic map, showing chaotic behaviour for most values of r > 3.57.

With specific increases in the value of r making bifurcations:

Bifurcation

If x is set to different values, even with very tiny alterations, the logistic map will make what is called strange attractors (some of you may remember Ian Malcolm talking about this at one point in the movie Jurassic Park).

Strange Attractors 2
Two time series for r=3.99, x(1)=.3 compared to x(1)=.3000001, 48 iterations
Strange Attractors
Two time series for r=3.99, x(1)=.3 compared to x(1)=.301, 48 iterations

What does this all mean for evolution? The sensitivity of the initial condition is the small changes in R and x (R being a single number representing birth and death rates for a single iteration or “generation” and x being the carrying capacity of an environment for that organism, as discussed in the ecology section).

Tiny changes in the environment alter these initial conditions (initial here essentially meaning previous conditions) which causes the selection pressures of an environment to change, which causes populations of organisms to increase and decrease the frequency of alleles from generation to generation, as these new conditions select different traits – this changes the value of R as organisms with different traits will 1) breed at different frequencies (more fit (suitable to the environment) organisms breeding more, less fit organisms breeding less) and 2) die at different frequencies (more fit organisms living longer, less fit organisms dying quicker).

Hardy-Weinberg Equilibrium:

Hardy-Weinberg-Equilibrium

Hardy-Weinberg Equilibrium (HWE) is the state of alleles for a particular gene in a population in which both allele frequencies will remain constant from generation to generation in an infinitely large interbreeding population in which mating is at random and no selection, migration or mutation occurs.

  • No mutation: No new alleles are generated by mutation, nor are genes duplicated or deleted.
  • Random mating: Organisms mate randomly with each other, with no preference for particular genotypes (e.g., no sexual selection).
  • No gene flow: Neither individuals nor their gametes (e.g., windborne pollen) enter or exit the population.
  • Very large population size: The population should be effectively infinite in size.
  • No natural selection: All alleles confer equal fitness (make organisms equally likely to survive and reproduce).

(Source)

Mathematically we say that if there is a gene with two alleles, A and a.

                      p + q = 1

  • p = frequency of A allele
  • q = frequency of a allele

                  p2 + 2pq + q2 = 1

  • p2 = frequency of AA genotype
  • 2pq = frequency of Aa genotype
  • q2 = frequency of aa genotype

If a population is in HWE, it means that no evolution is occurring. This state of affairs is obviously impossible, as the conditions for HWE cannot happen, but it is useful as a null hypothesis. By comparing the observed frequency of alleles for a particular gene in a population with HWE, one can obtain the rate of evolution and compare the relative fitness of different alleles.

Evolutionary Psychology:

Biochemical processes like metabolism and development are determined by genetics. This is fairly uncontroversial. However, when it comes to psychology, there is still debate about how much is influenced by genetics (nature) and how much by culture and upbringing (nurture). The field of psychology that attempts to explain genetic determinants of human psychology is called evolutionary psychology.

Evolutionary psychology doesn’t just look at a person’s genetics due to their parents, though. It attempts to explain human psychology through the lens of humanities entire evolutionary past. For instance, less controversial things like why humans find flowers to be beautiful or why humans are afraid of spiders, and more controversial things like why humans invented religion or why homosexuality exists. What evolutionary psychology attempts to do is study psychological traits that are common amongst humans or particular populations of humans and ask why it might have arisen in an evolutionary sense – what evolutionary benefit did, say, being afraid of spiders or inventing religion bestow?

Due to the often controversial nature of evolutionary psychology, arguments rage as to its validity. Some accuse it of sampling bias – doing studies only on college-aged people in the U.S. and western Europe – and of coming up with just-so stories for how common psychological traits evolved.

Genetic Algorithms:

Evolution has come up with many unique “answers” to various problems – the evolution of the leg “answers” the problem of food not always being right where you are; the evolution of the eye “answers” the problem of how to actually sense and navigate yourself to food. Evolution doesn’t just answer these questions with what an engineer might see as the most optimal method, though. It can often do so using very novel approaches and always with an eye at energy efficiency. Because of this, engineers have come to rely on genetic algorithms in order to utilize evolutionary principles to generate novel solutions.

Genetic algorithms work by first generating a library of random ‘solutions’ to a problem (population initialization). This may be some way or arranging roads for a new city that a civil engineer is supposed to design such that there is as little congestion as possible on a given budget. The process will then go as follows:

GA

Continuing with my hypothetical example, after the library of 100 arrangements for roads is generated, it is then tested using a simulation (fitness assignment). The 10 best arrangements are selected (selection) and then their various elements are ‘bred’ (crossover) so as to regenerate 100 new arrangements and then some level of random mutation is applied (mutation). The criteria for selection and mutation rate can be adjusted by the engineer. Afterwards, the simulation is run again and tested against a criteria for termination. If they’re good enough, those solutions are kept. If not, those 100 new solutions are run through the process again. This is done over multiple generations until the termination criteria is met.

Genetic algorithms can be used for many other problems as well. If you’re interested, there is a tutorial on github for making genetic algorithms here (not mine).

Conclusions:

That evolution by natural selection is happening is undeniable. The work being done in the field of evolutionary biology is in where, when, why, and how it is happening and has happened. The concepts in this article covered just some of the ideas being discussed within evolutionary biology.

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