Continuing my series of notes on the work of Sewall Wright, I come to the question of population size. This is important in Wright’s formulation of population genetics and his evolutionary theory generally. One of the major differences between Wright and R. A. Fisher is that Fisher believed that, in general, evolutionary processes could be treated as if they took place in a very large random-mating population. He did not believe, contrary to some caricatures, that species were literally random-mating across their entire range (which is obviously false), but rather that there was usually enough migration between different parts of that range that for most purposes the departures from random mating did not matter. Wright, on the other hand, believed that in many cases local populations were sufficiently isolated from each other that they could be treated as populations evolving separately. This difference of views had a major impact on Wright’s and Fisher’s assessment of the relative importance of selection and genetic drift.
Inductivist looked into the General Social Survey and found that the mean IQs of white college graduates has been dropping:
Remember that the popualtion mean is around 100, with a standard deviation of 15. That means that since the 1960s the college graduate has gone from being, on average, in the 17.5th percentile to the 37th percentile of the population! What’s going on here? I think it has to be the fact to a great extent a college degree is now substitute for a high school diploma, the pool is getting larger and so of course less select. I noticed in high school that looking at SAT scores from the 1980s that Mississipi had a higher average than Massachusetts! That totally shocked me, until I noticed that the proportion of high school graduates taking the SAT was on the order of 10% in Mississipi while in Massachusetts it was closer to 60%. One of my teachers assumed that this was the reason for the slow but steady decrease in average SAT score since 1960 before recentering in 1995. She explained that when she was in high school the SAT was something that only the elite students would be assumed to take. Today of course it is something that only the dumb avoid.
You’ve probably read Carl and Ed’s posts, but the paper is finally out, Historical contingency and the evolution of a key innovation in an experimental population of Escherichia coli:
The role of historical contingency in evolution has been much debated, but rarely tested. Twelve initially identical populations of Escherichia coli were founded in 1988 to investigate this issue. They have since evolved in a glucose-limited medium that also contains citrate, which E. coli cannot use as a carbon source under oxic conditions. No population evolved the capacity to exploit citrate for >30,000 generations, although each population tested billions of mutations. A citrate-using (Cit+) variant finally evolved in one population by 31,500 generations, causing an increase in population size and diversity. The long-delayed and unique evolution of this function might indicate the involvement of some extremely rare mutation. Alternately, it may involve an ordinary mutation, but one whose physical occurrence or phenotypic expression is contingent on prior mutations in that population. We tested these hypotheses in experiments that “replayed” evolution from different points in that population’s history. We observed no Cit+ mutants among 8.4 x 1012 ancestral cells, nor among 9 x 1012 cells from 60 clones sampled in the first 15,000 generations. However, we observed a significantly greater tendency for later clones to evolve Cit+, indicating that some potentiating mutation arose by 20,000 generations. This potentiating change increased the mutation rate to Cit+ but did not cause generalized hypermutability. Thus, the evolution of this phenotype was contingent on the particular history of that population. More generally, we suggest that historical contingency is especially important when it facilitates the evolution of key innovations that are not easily evolved by gradual, cumulative selection.
John Hawks has a post up, Handling exponential growth in demographic models. You might like to read it in concert with p-ter’s post Modeling human demographic history. One question I have in regards to human evolutionary genetic history is this: how typical are our population dynamics up to this point for a typical sexually reproducing species? And therefore, how might that impact deviations for our species from the norm? Also, if you are interested in the intersection of evolutionary genetics and models of demography you can go back to R. A. Fisher’s Genetical Theory of Natural Selection, there’s a nice, if somewhat tedious, exposition of the relevance of the latter toward developing a good model of the former.
When I was a kid I was what you might call a “climate nerd.” I would be at a party my parents took me to and pour over atlases and maps, as well as descriptive books on climatology, just to pass the time. Though it was just a phase I have kept a lot of that knowledge with me, and I’ve found it really useful. Many times I’m shocked at how ignorant many of my friends are of geography. If one was to choose between learning technique or information (e.g., math vs. history) I would pick technique because my own feeling is that technique is very versatile. But in the real world we don’t choose, we mix & match. We combine a theoretical model of the world with a dense network of empirical data. A few weeks ago I was chatting with a friend of mine and it became clear that he thought China was placed “very far north.” I told him to look at a map and he was shocked. The reality is that China is to a great extent a subtropical country, with a small portion even to the south of the Tropic of Cancer.
One of the main things I recall from my childhood climate phase is the importance of physical geographical parameters in combining to produce a particular regime. Additionally, one can work with a few rules of thumb to make predictions. For example, the wider a landmass east-west is the greater the difference in mean winter temperature will be between the west coast and the east coast, with the former generally being far milder than the latter. But let’s make this concrete.
A week ago I posted on the gender gap in politics; today Statistical Modeling, Causal Inference, and Social Science critiques a similar argument:
Via Craig Newmark, I saw a column by John Lott summarizing his 1999 paper with Lawrence Kenny, “Did women’s suffrage change the size and scope of government?” Lott and Kenny conclude Yes, by comparing the spending and revenue patterns of state governments before and after women were allowed to vote. I haven’t looked at the analysis carefully and would need a little more convincing that it’s not just a story of coinciding time trends (they have a little bit of leverage because women were given the vote sooner in some states than others), but the story is plausible, at least from the perspective of voting patterns nowadays.
On the other hand . . .
poll data appear to show that the gender gap in voting between men and women is relatively recent–if anything, women used to vote more Republican than men did–so it’s not clear if the effect Lott seems to be finding is occurring from women actually voting for conservative candidates or from some indirect effect of legislators trying to adapt to what they perceive as the preferences of women.
History is good for you. Really. It increases the sample space from which you can select data. You want to test your hypotheses on different populations, but let’s include the dimension of time as well as space.
Shrimp is my favorite food; I really like shrimp. When I was an undergrad I used to stuff myself during “shrimp night” at the cafeteria. Basically I would show up at 4:30 and hang out eating until 7:00, then I would recline for an hour because moving was going to be really, really, painfull. Once I managed to walk without discomfort I’d go and lay down on my bed in the dorm room because I was worried about my stomach exploding. I really like shrimp. So with that, check out Deep Sea News as CJ posts about sustainable seafood. To my chagrin I ordered fried shrimp when I was visiting CJ in Monterey last winter…I hope it was Oregon shrimp!
I was chatting with a friend about a few quantitative genetic “back-of-the-envelopes.” Specifically, about the expectation of the heights of the offspring of any given couple in the United States. I say the United States because it is a nation where most people get enough to eat; that means that heritability is on the order of 80-90% for this trait. By this, I mean that 80-90% of the variation in height we see within the population is due to variation in genetics. Those who are tall are likely to have tall parents, and those who are short are likely to have short parents. The key is likely of course, expectation is not a guarantee.