Stimulating the drunk on the platform

Gotcha! I mean “simulating” in the title, not “stimulating.” This one’s about programming.

I’m interested, for various reasons, in how evolution might bring about change over time. Recall from my Evolution Overview that evolutionary changes could occur by drift or natural selection. Drift means random change, because a given polymorphism has no effect on fitness. Natural selection, on the other hand, is what my advisor likes to call the 900-lb gorilla: it does whatever the eff it wants. Selection can take existing variation in a population and mold it into all kinds of oddities. Within Primates, natural selection has fashioned inquisitive apes that walk on two legs and go to the moon, and sexual selection has festooned male mandrills in variegated visage (right). Selection can be gentle and allow gradual change (what I like to call sensual selection), or it could be strong and cause rapid change.
Selection can seem random for various reasons (e.g. why is it acting as intensely as it does when it does?), so it is hard to tell whether a given evolutionary scenario can be explained by selection for a given behavior, or if it reflects totally random change (drift).
Monte Carlo statistical methods allow one to simulate a given scenario, to test competing hypotheses. A simple null hypothesis that can be simulated is drift – change is completely random in direction, and if I reject this hypothesis I could argue that an alternative explanation (selection) is appropriate

The random walk is the oft-used analogy for this null hypothesis of random change. Now, if I’d ever been so imperfect as to have succumbed to the siren-song of spirits, maybe I’d corroborate the analogy. But using the extent of your limited but unadulterated imagination, pretend there is a drunk kid who happened to go to Loyola Chicago (like myself), and who walks onto the L platform (like I often did; left, looking north from the Lawrence Red Line stop). As booze takes the reins, he stumbles randomly between the edges of the train platform. This random walk down the train platform could result in the drunkard making it safely to the end, or he could fall off either side to a gruesome doom awaiting on the tracks below.

Thinking about limb proportions, and how to program this hypothesis/scenario, I stumbled upon the useful cumsum() function for the R statistical program. This function allows me to indicate how much change to occur for how many steps (i.e. generations), thus effectively simulating the random walk. For example (right), say I want to ask if the tibia (shin bone) gets long relative to the femur (thigh bone) in human evolution, because of drift vs. natural selection. I start with a given proportion of [tibia/femur] and simulate change in a random direction in tibia and femur length, over a quarter million years (or 18,000 15-year generations).

The figure is a bird’s eye view of a random walk: at each generation the drunken tibia/femur ratio steps forward (to the right in the picture) and randomly right or left (toward the top or bottom of the picture). This took literally 2 seconds to program and graph. The dashed black line represents the relative tibia/femur relationship at the beginning of the evolutionary sequence, and the red line is the ratio 250,000 years (18,000 generations) later. Note that in this particular random scenario, not only is the final tibia/femur ratio exactly that observed, but that over the time span this ratio was reached about 20 different times. Do this randomization 500 or more times to see how often random change will result in the observed difference between time periods. Assuming the simulations realistically model reality, the observed change in limb proportions could easily be explained by drift (i.e. climate or efficiency adaptations did not have so strong a selective advantage as to be detected by this test). That is, the change in proportions could have been effected by random change or by weak directional selection.
I’m currently looking for any ways to make the model more realistic, for example:
  1. how much evolution (e.g. change) could occur per generation. Currently, each generation changes by plus or minus a given maximum. I would like to be able to simulate any amount of change between zero and an a priori maximum.
  2. it’s easier to let the tibia and femur change randomly with respect to one another. However, this is unrealistic because the thigh and leg are serially homologous, their variation is not independent of one another. I would like to model each element’s change per generation to reflect this covariance.
Anyway, I’ve only begun looking into the topic of how to analyze evolutionary change, but it looks like testing evolutionary hypotheses might not be impossible?

Evolution: What it is and why humans aren’t immune to it

An alternate title for this post could be “BigThink Too Big For Own Britches.”

Physicist Michio Kaku (via John Hawks via Pharyngula) has re-brought my attention to the fact that a great deal of people who don’t study biology have no idea what evolution is or how it works (smart people like Kaku included). I will no further rebuke Kaku for abusing his power as a respected public figure in big Science and saying things that are outside his purview, not to mention just incorrect. His comments on biology would be like me telling high school students that the invention of the wheel or lubricants have obviated the effects of friction. Rather, I think it might be best to refresh people on what evolution is and how it works.

Quite simply, evolution is change in a gene pool. This pool could be an entire species or a small population within that species.
There are a number of ways evolution can happen. A mutation is a new genetic variant that arises in an individual, which can then be spread to later generations when that individual reproduces. A single strand of human DNA is like a string of some 3 billion letters. When a person replicates their DNA for it to be passed on to their offspring (meiosis), having to reproduce such a long strand ensures that a mistake is made at least once in a while. Hence mutations increase variation in a gene pool.
But the frequencies of genes in a population can change, that is they may become more or less common within the gene pool. This could happen by genetic drift, which is the random loss of genes. If a gene is neither adaptive nor harmful, it could simply be lost over time due to sheer chance. In contrast to mutation, drift reduces genetic variation.
If genes are adaptive or harmful, their frequency in a gene pool becomes subject to natural selection. If a gene (or set of genes) is adaptive, that means the possessor of those genes will be more likely to survive and reproduce than others. This advantage ensures the individual will pass on these genes. Over time, the adaptive genes will increase in frequency in a population. Conversely, genes that lower the likelihood of surviving and reproducing will be culled by selection. Either of these scenarios means selection is reducing genetic variation. But sometimes different forms of a gene can be adaptive in different situations or combinations, so selection will act to maintain both of these in the gene pool. So in contrast to mutation and drift, selection can reduce or maintain genetic variation.
Finally, gene flow refers to genes being introduced into a gene pool from another source. This could occur when someone from one population reproduces with an individual from another population, and so new genes may enter one of the groups. Like mutation, this will increase genetic variation in a gene pool.
Common misconceptions
It may seem counterintuitive, but evolution does not equate with progress. This is a common misconception, probably due to the social ideologies under which evolutionary theory developed. Because of selection, evolution often means that a population becomes better-suited to its environment over time, which seems like progress. But as we’ve seen above, not all evolution is selection; mutation and drift are fairly random processes of evolution that don’t necessarily bear on adaptation. In addition, environments and circumstances change, so that even if something evolved in a place where it was adaptive, it may be harmful in a new context. For example, as the earliest humans lost their body hair, they probably evolved to have darker skin: adaptive in the tropics where humans originated. But later, when early humans moved into more northerly latitudes with less ultraviolet exposure from the sun, the dark skin that was adaptive for a hairless human in a tropical environment came to hinder the body’s vitamin D synthesis: maladaptive!
Also contra popular opinion, individuals do not evolve, populations do. Trojan brand condoms recently had an ad campaign in which they encouraged men to “evolve” by using Trojan condoms when having promiscuous sex. This is in line with the incorrect idea above that ‘evolving’ means ‘becoming better’ or ‘more sophisticated.’ Of course, condoms may actually help a population to evolve: those who use condoms to prevent pregnancy are ensuring they do not pass on their genes. And if there’s any genetic predisposition to make one more likely to use condoms (and there’s not), these genes would certainly become less common in future generations. [I am NOT encouraging people not to use protection, by the way]
So this brings us to a final point: the outrageous thing (well, the main one) Dr. Kaku foolishly leashed upon an unsuspecting world is that humans are not evolving. Technology and urbanization, he tells us, has obviated natural selection on human features (well, the “gross” or visible ones). This is very wrong and shortsighted. In fact, this is one of the bases of the eugenics movement of the early 20th century. Eugenicists thought, ‘Nature is no longer ensuring some people don’t pass on their genes, so we ought to do it ourselves for the good of humankind.’ This first thought, about the insufficiency of Nature, is echoed by Dr. Kaku (surely he does not think the second).
Simply HUMANS ARE STILL EVOLVING. Remember, not all evolution = natural selection. The genetic composition of humankind is still subject to the random forces of mutation and drift. In fact, because the human population size has increased exponentially of late, the fact that there are way more people than ever means that there are more mutations entering the population, and at a faster rate, than ever! But selection is still at work, too. There are still diseases that kill people before they can pass on their genes. There are still environmental situations – even in civilized places! – that prevent people from passing on their genes.
We humans are still evolving because we are still subject to the forces of evolution, and we always will be. Now what physicist could’ve told you that?!