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In the comments below it seems that most people don’t know about the existence of Eurostat, and the NUTS2 and NUTS3 maps which they generate. They’re really great, insofar as they give you a fine-grained picture of variation within Europe. Sometimes you see how national boundaries matter a great deal…and in other ways how they don’t.

Above you see a NUTS3 map of purchasing power in relation to the European median. A few things that are salient.

1) France and the United Kingdom exhibit a great deal of wealth concentration around their capital cities.

2) The geographically fragmented and culturally diverse zone from the Low Countries down to Italy’s Po River Valley is seems to be characterized by a large number of economically vibrant cities/regions. The only common variable that I’ve ever been able to point to for this area is that they were under Habsburg hegemony for a very long time.

3) There are zones of poorer nations, such as Spain, which are wealthier than most regions of wealthier regions (e.g., Catalonia is more prosperous than the north of England or rural France across the border).

4) A few of the cities of Eastern Europe seem to be diverging from their host nations.

Below are screenshots of maps I generated from Eurostat, submitted for your comment (remember, don’t be stupid).

Screenshot 2016-05-17 22.41.22

Screenshot 2016-05-17 22.43.58

Screenshot 2016-05-17 22.45.08

Screenshot 2016-05-17 22.46.07Screenshot 2016-05-17 22.46.40Screenshot 2016-05-17 22.47.30Screenshot 2016-05-17 22.48.02Screenshot 2016-05-17 22.48.38Screenshot 2016-05-17 22.49.05Screenshot 2016-05-17 22.49.30Screenshot 2016-05-17 22.49.58Screenshot 2016-05-17 22.50.23Screenshot 2016-05-17 22.50.58

• Category: Economics, Foreign Policy • Tags: Geography 
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Screenshot - 12032015 - 01:57:15 AM

The guy who runs the Pop vs. Soda page has really improved it. You can look at county level metrics just by hovering over the county. You can see counts, to get a good sense of the confidence in the representation of the underlying demographics. One thing that must be amended is that it’s not just soda vs. pop, there’s also coke in the South.

Screenshot - 12032015 - 01:54:14 AM

It is now very clear from these maps that there is an extremely sharp cline between the Middle Atlantic/New England region and the Great Lakes/Midwest on this dialect difference. I grew up in a soda region of upstate, though in the upper Hudson valley (95% soda), closer to New England than Syracuse. But in west-central New York you have counties right next to each other which are 60% vs. 15% pop, with reasonable sample sizes. Pennsylvania is similar. Clearfield county is 83% pop. Centre county just to the east is 19% pop (I know Centre county has Penn State, but the other counties around it are mostly soda as well).

In some places state lines matter a lot. Look at Oregon vs. California. The two “soda counties” in Oregon are more tied to the far north of California than the Willamette valley (the state of Jefferson). The Wisconsin-Illinois state line is a huge barrier as you approach Lake Michigan. But in other areas borders don’t matter so much. South Florida is part of soda territory, but that makes sense with its cultural history (lots of Jews with family roots in the Northeast). And there’s the huge zone that radiates out of St. Louis.

Screenshot - 12032015 - 02:11:39 AM

But in some ways the distribution of coke is the most interesting. First, state lines matter a lot in some areas. In the west there is a sharp drop off as one moves into Oklahoma, but an even sharper one into Kansas. Basically it’s the old Confederacy states, as Missouri has very little coke. As you move east it becomes more complicated. Northern Florida is part of the south, but you see in parts of Indiana that coke is a very common term for soft drinks. Why? It’s the “butternut” folk; descendants of Southerners who had settled large swaths of the Old Northwest. They retain connections and affinities with the South to this day.

Finally, on the Atlantic coast, you see the impact I suspect of border position and Northeastern migration into Virginia and North Carolina. The far west of North Carolina is like eastern Tennessee. West Virgina has an Appalachian extension in eastern Kentucky. State borders are less important in the east, just as is in the case further north. Cultural patterns that emerged organically when states were rather inchoate exist today in these regions, while newer states to the west were defined partly by their borders in terms of their cultural background (e.g., Kansas as a free state would be less appealing to Southern settlers culturally than if it was a slave state).

Those will more local knowledge can probably say more.

• Tags: Geography, Miscellaneous 
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The above map accompanies an article titled Imagining a Remapped Middle East. Do you notice something off? I do. Here’s a list of the provinces of Iraq. Do you notice any that end in -stans? No. Here’s why, -stan:

The suffix -stan (Persian: ـستان‎ -stān) is Persian for “place of”[1] or “country”.[2]

The suffix also appears in the names of many regions, especially in Central and South Asia, but also in the Caucasus and Russia; areas where significant amounts of Persian culture were spread or adopted. The suffix is also used more generally, as in Persian and Urdu rigestân (ریگستان) “place of sand, desert”, Pakistan “land of the pure” and golestan (گلستان) “place of flowers, garden”, Hindi devasthan (“place of devas, temple”), etc.

It’s obviously Indo-Iranian; note Rajasthan. Therefore it is bizarre to label a region as “Wahhabistan“. To make it clear for readers “Wahhabistan” is in Saudi Arabia, which is an Arab land, and Arabs don’t use any such suffix. The usage of that suffix connotes areas of Persianate cultural hegemony, which has often included non-Persian regions such as Turkestan and Hindustan (i.e., the Turkic and Indian cultural domains). But not Arab ones. There is a term “Arabistan”, but it means “land of the Arabs” in Persian. Wahhabistan, Shiitestan, and Sunnistan might make sense if the cartographer was Iranian. But that seems strange in an American publication, to be presenting an Iranian-centric worldview. Then again, mainstream publications have a problem with remembering that Iran is not an Arab country, so perhaps they tasked an Iranian with coming up with the labels.

The main reason I point this out is not to catch people in picayune details, but observe how shallow and superficial a grasp of facts is in much of the media establishment which is attempting to inform and enlighten the public. The reality is that the establishment is full of bullshit artists. Beware. If these people can’t even best 12 year old contestants for the geography bee, do you think they can inform you reasonably about world affairs?

(of course to be fair to The New York Times 99% of people who talk about foreign policy seem to be bullshit artists with a tenuous grasp of history and geography)

• Category: Foreign Policy • Tags: Geography 
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I’ve been thinking about how best to visualize PCA/MDS type of results, which allow for the two dimensional representation of genetic variation. Below are a few of my efforts with a data set I have. You can see the individuals in gray, but also ellipses which cover ~95% of the distribution of a given population.

Please click the images for a larger version. They represent coordinate 1 on the y axis and 2 on the z axis derive from a multidimesional scaling representing identity by state across individuals.

• Category: Science • Tags: Genetics, Genomics, Geography 
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Obviously the news over the past week has been filled with the events in the Middle East, and the broader Muslim world, in reaction to an anti-Muslim film. I think the most eloquent commentary is from The Onion (NSFW!!!), No One Murdered Because Of This Image. That being said, there are some serious broader issues here. A friend of mine who lives in India (he is Indian American, though raised for several years in India, so not totally unfamiliar with the culture) has expressed to me his frustration with having to defend American liberalism in a society where American liberalism is an abstraction, rather than concrete. The frustration has to do with the fundamental divergence in basic values. For example, his interlocutors have argued to him (he is a practicing Christian of libertarian political orientation) that if someone committed an act of blasphemy against his faith of course he would react in anger and violence. And yet of course the clause “and” is false, though he is greeted with skepticism when he asserts he wouldn’t react violently. As a matter of fact I can attest to the reality that he wouldn’t react angrily necessarily, because in interactions where I’ve made casually blasphemous comments he’s only rolled his eyes. Just as Americans have a vague, even misleading, understanding of the broader historical forces which engender resentment of American hegemony in the broader world, so many non-Americans lack a proper awareness of the broader historical forces, and cultural reality, of the particular American radicalism and extremism in the domain of free expression.

I say radicalism and extremism because that is exactly what free speech near absolutism is. Over the course of human history blasphemy has been understood to be unacceptable in most human societies, and often entails extreme sanction. The American, and to a lesser extent Western, elevation of liberty of speech over the sacred values of the community is a peculiar counter-cultural trend which has become normative. But that doesn’t mean that it’s normal or natural. I stipulate here the term “sacred values of the community,” because though blasphemy connotes violations of religious norms, obviously outrage can be triggered by violations of sacred communal norms more generally. Imagine, for example, if someone violated Lenin’s Tomb during the 1950s in the Soviet Union. Jonathan Haidt has alluded to this issue. Someone who reacts calmly to “Piss Christ” might not react so calmly to “Piss Martin Luther King.”

This points to the second issue. Not only is there is a human universal of offense at violation of sacred norms, but those sacred norms vary from culture to culture. So, for example, I have pointed out to followers of the Abrahamic religions that the core documents of their own faiths and the dominant interpretations are often gravely offensive and hostile toward those of other religious traditions. There is a certain incommensurability of offense across cultures. What may be sacred to one culture may be offensive and blasphemous to another. To give an example, the institutions of sacred prostitution has cropped up repeatedly over human history. Many religious people would consider prostitution in the service of gods or God blasphemous, whereas others might consider it an exalted act. Similarly, blood sacrifice, whether of humans or animals, has been central to many religions, and taboo and blasphemy in the context of others. In contrast to this there are acts and violations which seem relatively universal in interpretation. This is clear when offended people make analogies to insulting one’s mother; this is generally communicable across societies, because emotional family ties are fundamental. And the collective paroxysms of rage, anger, and violence, due to violations of communal honor probably draw from the same cognitive reflexes as those which are triggered by violations of family honor.

But let’s put the shoe on the other foot here. Would Americans tolerate anti-American preaching from Muslim clerics in this country? We can explore this with the General Social Survey with the SPKMSLM variable. It asks:

Now consider a Muslim clergyman who preaches hatred of the United States.

If such a person wanted to make a speech in your community preaching hatred of the United States, should he be allowed to speak, or not?

The question was asked in 2008 and 2010. Since the sample sizes are large I’ll limit to non-Hispanic whites first.

Now in tabular format.

Non-Hispanic whites, 2008 & 2010
Demographic Allow Muslim clergymen to preach hatred of US
Male 52.6
Female 39.7
< HS 19
High School 38.2
Junior College 45.3
Bachelor 62.5
Graduate 71.6
Stupid 28
Average 43.7
Smart 73.6
Liberal 59.9
Moderate 40.6
Conservative 43.6
18-34 years old 49.3
35-64 years old 48.5
65-* years old 33.4
Protestant 40.7
Catholic 43.6
Jewish 45.7
No religion 61.1
Word of God 26.6
Inspired Word of God 48
Book of Fables 66.1

The exact row variables in the GSS:

SEX DEGREE WORDSUM(r:0-4″Stupid”;5-8″Average”;9-10″Smart”) POLVIEWS(r:1-3″Liberal”;4″Moderate”;5-7″Conservative”) AGE(r:18-34;35-64;65-*) RELIG BIBLE

I then decided to run a logistic regression. I wanted to see which variables predict attitudes toward speech on this issue. I expanded the data set to include Hispanics and non-whites.

Below positive values in the “B” column include opposition to allowing a Muslim cleric preach. Therefore, a negative value favors freedom of speech in this case.

B SE(B) Probability
SEX 0.484 0.156 0.002
AGE 0.008 0.005 0.084
SEI -0.01 0.005 0.041
REALINC 0 0 0.43
DEGREE -0.289 0.082 0
WORDSUM -0.301 0.05 0
RACE(Recoded) -0.059 0.229 0.795
HISPANIC(Recoded) 0.843 0.333 0.012
GOD 0.145 0.057 0.012
POLVIEWS 0.075 0.055 0.176
Log Likelihood = -533.697
Pseudo R-sq = 0.151

What’s striking to me is that once you account for education and intelligence, income and socioeconomic status don’t matter. That makes sense since the former are related causally to the latter. The sex difference here is pretty robust. Once you account for other variables race is not so important, but Hispanic identity is. I would suggest here that assimilation to American values is the determining factor, but nativity (BORN variable) doesn’t seem to matter when I checked. It is not surprising to me that political ideology (very liberal to very conservative) doesn’t matter when you account for other variables, especially religion. Well educated conservatives who are not religious tend toward social libertarianism. So once you account for religion and education, ideology isn’t as predictive, similar to race.

There are other similar variables in related to free speech. One pattern is clear. American cultural elites are particularly protective of free speech, while the lower orders tend to have attitudes which are more “relaxed,” and would be more in keeping with other parts of the world. Why? One can imagine many reasons, but this republic was founded by prominent and powerful men who were traitors, and who valued their own personal individual liberty. This is not an uncommon tendency; liberty of thought has been one of the privileges of aristocracy throughout human history. One aspect of ancient Greek democratic populism which rankled aristocrats was that the community might censor and restrain the freedoms of those who traditionally had more license to violate communal norms.

• Category: Science • Tags: Anthropology, Geography, GSS 
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Planet Money recently did a report on the difficulty of maintaining high economic productivity in southern Italy. I won’t rehash the specifics of the story, but, I think it is important to get a visual sense of just how large the contrast between the south and north of Italy is. Too often we speak of nation-states. Nation-states are real, and they are important, but they are often not comparable. Just like comparing the USA to Sweden is only marginally informative, so comparing a small nation like Ireland to a more substantial one like Italy is deceptive. Here is a 2008 regional GDP map with sub-national breakdowns. Though some of the values are certainly lower now (basically, everything outside of Germany and Sweden), the relationships still hold.

There has been a gap between the north and south of Spain and England, as well as the west and east of Germany, but none of these are of the same magnitude of what you see in Italy (for one, southern Italy is much more populous than eastern Germany). Sicily and the southern provinces are the poorest regions of western Europe. In contrast, the area between Milan and Bologna in the north is among the wealthiest.

Here is a map of unemployment rates:



• Category: Economics, Science • Tags: Culture, Europe, Geography 
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I was alerted to Samuel’s Arbesman’s new paper, The Life-Spans of Empires, by the fact that he pointed to his research on his weblog. Interestingly I’m not the only one who was interested, as after I pointed to it on my link round up a few people asked if they could get a copy of the paper (yes, I almost always send papers if I have access). Luckily it’s a nicely elegant piece of work, basically quantifying what we’ve already probably known qualitatively. There isn’t that great of a value-add to quantification as such, but with a mathematical understanding of a topic one can engage in an algebra of mental manipulations so as to construct models with which one can project other facts. Quantitative information is often an excellent way to generate “free information” from theoretical models. The figure above is the primary result of the paper. Basically Arbesman took a data set which was laying around which measured the lengths of various empires (N = 41), and showed that the rise and fall of these political entities tends to follow an exponential distribution: e−λt . This is an incredibly elegant summation of what we know qualitatively: some empires last a long time, but most do not.

Interestingly the mean length of an empire is 220 years. That’s basically what you’d probably expect from intuition, especially if you knew Chinese history. To the left is a density plot I generated with the data provided in the paper. You can see that the mode and mean are a bit different because of the skewness. One of the interesting points about the exponential distribution is that it implies that the the duration of an empire at any given moment can’t tell you the probability that it’s going to collapse in the near future. The distribution is “memoryless.” In other words, the likelihood of doom striking isn’t greater as time passes. This seems somewhat counterintuitive. After all doesn’t the cohesion and elan of the a ruling caste of a given empire wane as the society slowly lose its vital force? Hasn’t the author read Spengler! Arbesman admits that there are more complex equations which can describe the distribution more precisely, but the exponential formula has only one parameter, so it’s quite parsimonious. But even if we have a first approximation we don’t have a total description.

Like evolutionary process as a whole I’m not convinced that the nature of the current data set is sufficient to deny the shifting background parameters which are operative over time. As I’ve noted before, there are two counteracting tendencies over time in human history when it comes to social & political entities:

– A greater rate of cultural change over time

– A greater cohesion and integrative power of social and political systems (more rapid bounce-backs from collapse, and greater civilizational continuity)

One thing I wanted to do is check to see what the correlation between age of the polity and its duration was. My intuition was that older polities will have greater recorded duration. Obviously there’s just more time for them, but some societies, such as Egypt, were very stable for longer periods of time in far antiquity. When I ran the correlate it was pretty weak, -0.23. Below is a chart which shows the scatter plot and the r-squared (correlation squared):

Here’s the original data:

Empire Adulthood Duration
Western Turk (C. Asia) 582 0.7
Avar (Europe) 580 2
T’u Chueh Turk (C. Asia) 550 0.9
Visigoth (Europe) 470 2.4
White Hun (Indo-Iran) 460 1
Toba (China) 440 1.3
Yuen-Yuen (C. Asia) 400 0.3
Byzantine (Europe) 395 3.5
Hun (Europe) 380 0.8
Gupta (India) 370 0.9
Liu-Sung (China) 330 2.1
Ptolemaic (Africa) 323 2.9
Bactria (Indo-Iran) 200 0.6
Kushan (Indo-Iran) 75 2
Rome (Europe) 0 4
Saka (Indo-Iran) -50 1.2
Parthia (Iran) -60 7
Ch’in (China) -90 2.9
Andhra (India) -170 3.7
Hsiung Nu Hun (C. Asia) -190 1
Maghada-Maurya (India) -300 0.9
Achaemenid (Iran) -540 3.2
Lydia (Anatolia) -610 0.6
New Babylon (Mesopotamia) -610 0.7
New Assyrian (Mesopotamia) -700 0.8
Late Period (Egypt) -715 1.9
Phrygia (Anatolia) -760 0.6
Urartu (Mesopotamia) -810 0.9
Babylon (Mesopotamia) -1000 2.5
Middle Assyrian (Mesopotamia) -1090 0.5
Hittite (Anatolia) -1320 1.3
Hsia-Shang (China) -1350 4
New Empire (Egypt) -1500 5
Mitanni (Mesopotamia) -1500 1.4
Elam (Mesopotamia) -1600 10
Hykso (Syria) -1650 0.8
Babylon—Hammurabi (Mesopotamia) -1700 2
Old Assyria (Mesopotamia) -1800 1
Middle Empire (Egypt) -2000 3
Akadia (Mesopotamia) -2310 1
Old Empire (Egypt) -2800 5
• Category: History, Science • Tags: Anthropology, Cliodynamics, Geography 
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The image above is adapted from the 2010 paper A Predominantly Neolithic Origin for European Paternal Lineages, and it shows the frequencies of Y chromosomal haplogroup R1b1b2 across Europe. As you can see as you approach the Atlantic the frequency converges upon ~100%. Interestingly the fraction of R1b1b2 is highest among populations such as the Basque and the Welsh. This was taken by some researchers in the late 1990s and early 2000s as evidence that the Welsh adopted a Celtic language, prior to which they spoke a dialect distantly related to Basque. Additionally, the assumption was that the Basques were the ur-Europeans. Descendants of the Paleolithic populations of the continent both biologically and culturally, so that the peculiar aspects of the Basque language were attributed by some to its ancient Stone Age origins.

As indicated by the title the above paper overturned such assumptions, and rather implied that the origin of R1b1b2 haplogroup was in the Near East, and associated with the expansion of Middle Eastern farmers from the eastern Mediterranean toward western Europe ~10,000 years ago. Instead of the high frequency of R1b1b2 being a confident peg for the dominance of Paleolithic rootedness of contemporary Europeans, as well as the spread of farming mostly though cultural diffusion, now it had become a lynch pin for the case that Europe had seen one, and perhaps more than one, demographic revolutions over the past 10,000 years.

This is made very evident in the results from ancient DNA, which are hard to superimpose upon a simplistic model of a two way admixture between a Paleolithic substrate and a Neolithic overlay. Rather, it may be that there were multiple pulses into a European cul-de-sac since the rise of agriculture from different starting points. We need to be careful of overly broad pronouncements at this point, because as they say this is a “developing” area. But, I want to go back to the western European fringe for a moment.

As I stated above the Basques were long used as a Paleolithic “reference” by historical geneticists. That is, the deviation of a population from the Basques would be a good measure of how much admixture there had been from post-Paleolithic sources. Connections between Iberian populations and those of western and northern Europe were used to trace expansions out of the ecological refuges of modern humans during the Last Glacial Maximum ~20,000 years ago. Just goes to show how reliant we are on axioms which are squishier than we’d like to think.

Last fall I posted a result from Dodecad on the difference between French and French Basques (both from the HGDP). I’ve replicated this myself a few times now too:

The striking aspect is that the Basque are less cosmopolitan than the other French. This is evident in most of the runs of the HGDP Basque; they just have a “simpler” genetic heritage than other Western Europeans. Today Dienekes posted some results from the IBS Spanish data set in the 1000 Genomes. He suggests there are clearly a few Spanish Basques in there (I’ve highlighted them):

Recall that the Basques were exempt from inspection for “cleanliness of blood”, because they were presumed to lack Jewish or Moorish ancestry by virtue of being Basque. It seems that the Spanish IBS sample, like the Behar et al. Spaniards and Portuguese, do have some Moorish genetic imprint. This is not too surprising. The Moriscos might have been expelled in the early 17th century, but not before the majority had converted to Christianity over the centuries (in fact, some of the most virulent anti-Morisco partisans had Moorish ancestry themselves, and were particularly tainted by association with the remaining culturally unassimilated crypto-Muslims). All that being said, I suspect that the “West Asian” ancestry amongst the majority of the Spaniards is not due mostly to the Arab period (when of the majority of the settlers probably were Berbers or Arabicized Berbers), but to population impacts prior to that. By the time of the Roman conquest much of Spain was Celtiberian. I have low confidence in this assertion, but I am coming to believe that the Indo-Europeans brought a mix of East European and West Asian ancestry (or at least those two distinct strands which tend to shake out of ADMIXTURE in a broad array of European samples) to western Europe.

On a related note, Wave-of-Advance Models of the Diffusion of the Y Chromosome Haplogroup R1b1b2 in Europe:

Whether or not the spread of agriculture in Europe was accompanied by movements of people is a long-standing question in archeology and anthropology, which has been frequently addressed with the help of population genetic data. Estimates on dates of expansion and geographic origins obtained from genetic data are however sensitive to the calibration of mutation rates and to the mathematical models used to perform inference. For instance, recent data on the Y chromosome haplogroup R1b1b2 (M269) have either suggested a Neolithic origin for European paternal lineages or a more ancient Paleolithic origin depending on the calibration of Y-STR mutation rates. Here we examine the date of expansion and the geographic origin of hgR1b1b2 considering two current estimates of mutation rates in a total of fourteen realistic wave-of-advance models. We report that a range expansion dating to the Paleolithic is unlikely to explain the observed geographical distribution of microsatellite diversity, and that whether the data is informative with respect to the spread of agriculture in Europe depends on the mutation rate assumption in a critical way.

Really I’m waiting for more ancient DNA. These sorts of studies are starting to feel like rewarming cold pizza. Edible, but suboptimal. Next, Phylogeography of a Land Snail Suggests Trans-Mediterranean Neolithic Transport:

Fragmented distribution ranges of species with little active dispersal capacity raise the question about their place of origin and the processes and timing of either range fragmentation or dispersal. The peculiar distribution of the land snail Tudorella sulcata s. str. in Southern France, Sardinia and Algeria is such a challenging case.

Statistical phylogeographic analyses with mitochondrial COI and nuclear hsp70 haplotypes were used to answer the questions of the species’ origin, sequence and timing of dispersal. The origin of the species was on Sardinia. Starting from there, a first expansion to Algeria and then to France took place. Abiotic and zoochorous dispersal could be excluded by considering the species’ life style, leaving only anthropogenic translocation as parsimonious explanation. The geographic expansion could be dated to approximately 8,000 years before present with a 95% confidence interval of 10,000 to 3,000 years before present.

This period coincides with the Neolithic expansion in the Western Mediterranean, suggesting a role of these settlers as vectors. Our findings thus propose that non-domesticated animals and plants may give hints on the direction and timing of early human expansion routes.

So basically the snail hitched a ride from Sardinia to Algeria to France. I don’t think this is that surprising. First, it seems pretty obvious that a lot of the cultural expansion in the prehistoric period did not consist of the fission of villages along a continuous wave of advance, but involved leap-frogging to suitable nuclei from which the populations expanded. Imagine a rising flood where the lowest zones are inundated first, and then the higher peaks. Additionally, we shouldn’t presume that these expansion events were without conflict and institutional support. Consider that the expansion of farming across much of southern European Russia and Ukraine could only occur after the state had pacified, expelled, or assimilated, the mobile Turkic populations which were wont to extract unsustainable rents out of isolated and vulnerable peasant populations.

Finally, what’s up with the strong north-south differentiation across the Mediterranean basin, peaking in the west? It’s as if there were two waves of demographic and cultural advance which laid the ground work, and later perturbations haven’t disrupted that bedrock. It suggests to me the critical importance of lateral coastal transport in connecting cultural colonies, as opposed to more long distance jumps across the open sea. The latter were probably important for the transport of luxury goods and the exchange of memes, but not so much for the exchange of genes.

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Since most international migration is apparently between “developing nations”, I thought the Iran-Iraq-Turkey-Syria border would be interesting to look at in terms of differences in economic and social indices.

• Category: Science • Tags: Comparisons, Data Analysis, Geography, Iraq, Syria, Turkey 
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ResearchBlogging.orgThe Pith: Over the past 10,000 years a small coterie of farming populations expanded rapidly and replaced hunter-gatherer groups which were once dominant across the landscape. So, the vast majority of the ancestry of modern Europeans can be traced back to farming cultures of the eastern Mediterranean which swept over the west of Eurasia between 10 and 5 thousand years before the before.

Dienekes Pontikos points me to a new paper in PNAS which uses a coalescent model of 400+ mitochondrial DNA lineages to infer the pattern of expansions of populations over the past ~40,000 years. Remember that mtDNA is passed just through the maternal lineage. That means it is not subject to the confounding dynamic of recombination, allowing for easier modeling as a phylogenetic tree. Unlike the autosomal genome there’s no reticulation. Additionally, mtDNA tends to be highly mutable, and many regions have been presumed to be selectively neutral. So they are the perfect molecular clock. There straightforward drawback is that the history of one’s foremothers may not be a good representative of the history of one’s total lineage. Additionally the haploid nature of mtDNA means that genetic drift is far more powerful in buffeting gene frequencies and introduced stochastic fluctuations, which eventually obscure past mutational signals through myriad mutations. Finally, there are serious concerns as to the neutrality of mtDNA…though the authors claim to address that in the methods. I should also add that it also happens to be the case that there is less controversy and more surety as to the calibration of mutational rates of mtDNA than the Y chromosomal lineages of males. Their good for determining temporal patterns of demographic change, and not just tree structures.

Here’s the abstract, Rapid, global demographic expansions after the origins of agriculture:

The invention of agriculture is widely assumed to have driven recent human population growth. However, direct genetic evidence for population growth after independent agricultural origins has been elusive. We estimated population sizes through time from a set of globally distributed whole mitochondrial genomes, after separating lineages associated with agricultural populations from those associated with hunter-gatherers. The coalescent-based analysis revealed strong evidence for distinct demographic expansions in Europe, southeastern Asia, and sub-Saharan Africa within the past 10,000 y. Estimates of the timing of population growth based on genetic data correspond neatly to dates for the initial origins of agriculture derived from archaeological evidence. Comparisons of rates of population growth through time reveal that the invention of agriculture facilitated a fivefold increase in population growth relative to more ancient expansions of hunter-gatherers.

As Dienekes notes until recently the orthodoxy was that the genetic variation of modern populations was well explained by the genetic variation of Paleolithic groups after the Last Glacial Maximum ~20,000 years B.P. In this line of thought agriculture spread often by cultural diffusion, and the first local adopters in a region would then enter into a phase of demographic expansion. Bryan Sykes’ Seven Daughters of Eve and Stephen Oppenheimer’s The Real Eve are expositions of this point of view, which really was the historical genetic mainstream. This also dovetailed with the anthropological bias of “pots-not-people,” whereby cultural forms moved through transmission and not migration. There were some dissenters, such as Peter Bellwood, but by and large the genetic evidence at least was robust enough that they could be dismissed.

So what happened? Several things. First, the sample sets of mtDNA and Y chromosomes kept getting larger. There was deeper sequencing of informative regions. Thick SNP-chip autosomal studies came to the fore, with different conclusions. Finally, ancient DNA extraction allowed scientists to compare the real lineages of hunter-gatherers in ancient Europe vs. what they had presumed were hunter-gatherer descendant lines in modern Europeans. The strong disjunction often found was indicative of a major failing in the prior assumptions of the theorists of the early 2000s: that they could infer confidently past events from the palimpsest of modern genetic variation. They couldn’t. We know that because they seem to have been wrong.

Let’s give India as an example of “what went wrong.” Here’s a paper from 2005, Most of the extant mtDNA boundaries in South and Southwest Asia were likely shaped during the initial settlement of Eurasia by anatomically modern humans:

Since the initial peopling of South and West Asia by anatomically modern humans, when this region may well have provided the initial settlers who colonized much of the rest of Eurasia, the gene flow in and out of India of the maternally transmitted mtDNA has been surprisingly limited. Specifically, our analysis of the mtDNA haplogroups, which are shared between Indian and Iranian populations and exhibit coalescence ages corresponding to around the early Upper Paleolithic, indicates that they are present in India largely as Indian-specific sub-lineages. In contrast, other ancient Indian-specific variants of M and R are very rare outside the sub-continent.

The Upper Paleolithic is pre-Holocene. I generally accepted this, until the the studies came out from the SNP-chips which had hundreds of thousands of autosomal markers. To be short about it Indians just seemed too close to West Eurasians if the mtDNA results were correct, and, representative. In fact, if Reconstructing Indian History is correct, about half the South Asian genome in aggregate is very close to that of West Eurasians, to the point where it seems likely to have a common ancestry in the Holocene. The mistaken inference from mtDNA may be due in part to sex-biased gene flow. That is, the South Asian exogenous genome was strongly biased toward male migration, while the deep time mtDNA substrate has tended to persist underneath all these successive layers.

Moving to the paper in question, they use a “Bayesian skyline” method to reconstruct past demographic history. Specifically, the history of the direct maternal lineage. We wouldn’t really pay attention if they didn’t have interesting results. And they do indeed.

The table is rather straightforward. They partitioned the samples they had into putative hunter-gatherer and Neolithic lineages. Notice the difference. For some of these cases we have very robust non-genetic evidence of expansion. This is true especially for the African and Southeast Asian Holocene cases. Their methods here predict exactly what we already know. So the key value add is that the methods are predicting something which is more in dispute: the demographic history of contemporary European mtDNA lineages. The concordance of the archaeological evidence of the Neolithic transition in Europe and the inferred demographic expansion of European Neolithic mtDNA lineages is striking.

The plot to the left is the curve of demographic expansion predicted from their method for Neolithic and Paleolithic lineages in Europe. The y-axis is log-scaled, so it naturally understates the explosive growth of Neolithic lineages. It comports well with what we know of how agricultural societies tend to expand and stabilize over time. During a phase of “land surplus” they enter into rapid demographic expansion, forcing the frontier of settlement out. Once the land is “filled up” we enter into the classic Malthusian “stationary state,” where the grinding misery of the peasantry becomes the lot of most. In contrast hunter-gatherer lineages didn’t experience such an explosive shift. Though pre-modern hunter-gatherer landscapes were more diversified than what we experience today, because they had access to the rich “bottom lands” and seashores now monopolized by agriculturalists, the carrying capacity of the land was generally lower for their lifestyle, and waxed and waned more gradually with shifts in ecology.

The authors also did some neat geo-visualization, if I do say so (and I’m jealous!). The two panels illustrate the spread of agriculture as inferred from archaeology, and the rate of population growth calculated from the joint information of the time of onset of a farming lifestyle in a region and the point on the “growth curve” for the Middle Eastern lineages at that time. So above you see the spread of agriculture from the eastern Mediterranean from 8000 BC to 2500 BC. Then, you see a geographical illustration of the S-shaped growth curve of the farmers. Their initial colonies experienced modest growth, but there was a transition zone in the middle of rapid expansion. Why? Perhaps there was a necessary critical mass, before the superiority of numbers began to wear down the hunter-gatherers. But this itself was a transient, as the farmer societies ran up against the limits of ecology along the northern European plain (or, perhaps just as likely, they encountered dense hunter-gatherer societies which were able to temporarily withstand their aggressive expansion on the European maritime fringe). I suspect that the models are more complex than a one-two punch, in either time or space. There were likely several pulses and distinct streams coming out of the Middle East which populated Europe.

They conclude that “Mesolithic ancestry makes up only a fraction of contemporary European genomes. U5a, U5b1, V, and 3H combined account for ≈15% of western Europeans mtDNA haplogroups.” Note that U5a and U5b are modal among the Finnic peoples of Europe. V seems widely distributed, and modal in northern Scandinavia and the western Mediterranean. I can’t seem to find easy information on 3H.

From the supplements here are the European haplgroups they selected:

We chose haplogroups associated with an origin in Near Eastern populations during the Holocene: T1, T2, J1a, K2a, and H4a. These haplogroups (T1, T2, J1a, and K) all appear to have Near Eastern founders that migrated to Europe after the Younger Dryas (2). After inspecting the haplogroup K network in Behar et al. (4), we chose the subgroup K2a, which appears to be present in the Near East (including non-Ashkenazi Jews) and European populations (but not North Africa). Haplogroup H4a is thought to have expanded throughout Europe during the Neolithic (5). However, the location of its origin is still not certain (6). Removing H4a from the Skyline analysis did not substantively change the timing of Holocene period expansion (results not shown). European haplogroups U5, V, and 3H are associated with an indigenous origin in Europe (2). Haplogroups U5a, U5b1, V, and 3H have all been attributed a TMRCA during the Last Glacial Period (2, 7–9)

Readers more well versed in the literature on mtDNA haplogroups can pick these details apart.

Where does this leave us? If this and other recent papers are correct. then the expansion of farming to Europe from the Middle East resembles the settlement of the New World far more than we may have thought! In some regions there was likely near total replacement of the substrate, perhaps like the United States. In others there was modest uptake of the indigenous substrate, as is the case in Argentina. Finally, there were regions where the indigenous hunter-gatherer substrate may have persisted to a far greater extent. I think this may be the case mostly in Baltic Europe, which combined both the possibility of relatively high hunter-gatherer carrying capacities because of marine resources and a climatic regime rather unsuitable to the initial Middle Eastern crops.

Citation: Gignoux CR, Henn BM, & Mountain JL (2011). Rapid, global demographic expansions after the origins of agriculture. Proceedings of the National Academy of Sciences of the United States of America, 108 (15), 6044-9 PMID: 21444824

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One of the major issues in our world today is that we’re a people of specialties. This means that we don’t have basic interpretative frameworks in which to place novel facts. Because of the abstruse and formal nature of the discipline, this is probably starkest in the domain of science, but it is not restricted to only science. Consider geography. In many ways this is “low hanging” cognitive fruit in the shallow part of the learning curve which mostly consists of assembly of facts, but because of the shifts in emphases in American education geography has tended to get short shrift. This means that whenever there’s a foreign policy crisis middle-brow journals of record such as The New York Times have to commission pieces about nations such as Libya which read like a “first book” for six year olds on that nation (and on political weblogs commenters proudly brandish their “first book” level of knowledge).

But a bigger general issue seems to be in relation to climate. “Climate Change” is in the news constantly, but the average person on the street seems to have zero historical perspective on events such as the Medieval Warm Period, the Little Ice Age, let alone more obscure epochs such as the Younger Dryas. Fair enough, it isn’t as if Deep Time is ever going to be broadly interesting. But more disturbing to me is the total lack of perspective when it comes to current spatial patterns.

For example, a friend who has college degrees in history and philosophy, has traveled to Europe, Canada, and is planning a trip to Thailand and the Philippines, thought China was further to the north than Europe. Take a look at this map:

New York City, Madrid, and Beijing, are all at the same latitude. The average low in Beijing in January is -8.4 °C. For New York City it is -3.22. And finally, for Madrid it is 2.6. Why the difference? Barcelona, to the north and east of Madrid, on the coast, has a mean low of 4.4 °C. This tells us what’s going in the most general sense. Continentality. My friend’s ignorance was understandable; Beijing has a much more frigid clime than southern Europe. China as a whole is much further south than climate without context would suggest, while Europe is much further north than most expect. All that has to do with the rough shape of the continents (and possibly the Gulf Stream for Europe, though this might be overdone taking into account the generally mild character of western upper temperate regions of continents). But first, let’s look at another example.

The town of San Luis Obispo in California gets about 33% more rainfall in the aggregate than Medford, in Oregon. The reason for this difference in aggregate rainfall seems clear when you look at their positions on the map to the left. Medford is inland, and somewhat in a rain shadow behind the Siskiyou mountains. San Luis Obispo in contrast has a much more maritime location. All things equal, maritime locations will generally have more precipitation than inland locations. But not only are all things rarely equal, notice that Medford has a longer “rainy season” than San Luis Obispo. This can’t be explained by the coastal vs. inland position.

My immediate explanation is that this must be due to the waxing and waning of the Westerlies with the seasons. The Westerlies are powerful winds in the temperate latitudes which blow out of the west and which tend to shift toward the equator during the winter, and retreat toward the poles during the summer. The shift of the westerlies on the western coasts of continents during the cold season is also accompanied by rainfall across broad swaths of the lower temperate latitudes, ergo, “Mediterranean” climate patterns on the southern tip of Africa, southwest Australia, central Chile, California, and yes, the Mediterranean. As physical dynamics not subject to magic, the movements of these winds exhibit a regular pattern where the areas which are furthest on the margin of their zones of expansion will also be the first subject to their retreat (this same pattern occurs with subtropical monsoons, as the rains abate fastest in the regions where they came the latest).

So what you have here is a two-variable model on the western coast of the United States in terms of predicting precipitation. On the one hand there are the coarse large-scale spatial relationships on the continental and planetary level which predict the flow of winds which bring the rainfall. But, there are also more fine-grained patterns of local positioning and topography.

All of the above I constructed as a model within 5 minutes, drawing upon a period of fascination with physical geography which I had when I was 8 to 10 years old. Because of my primitive mental state I only had a descriptive “stamp collecting” understanding of the patterns, but even my cursory knowledge of those patterns has been very useful to me as an adult. If the globe does warm, for example, I’d hazard to guess that the Pacific Northwest of the United States will have a climate resembling that of California far more likely than that of the American South. Why? Because the western coasts of continents are characterized by a particular set of temperature and precipitation regimes. Nature is not flat in its possibilities.

A broad background knowledge of spatial patterns allows one to infer facts and test ludicrous assertions “quick & dirty.” Of course one is often wrong if one lacks the subtle and precise knowledge of a specialist, but it is superior to the theory and data-free speculation which is par for the course in normal conversation.

Below is a Köppen climate map, the kind of mental image which I’ve long had seared in my brain:

Here are some quick facts which many people don’t know, but are often useful:

– The eastern coasts will tend to have a more “continental” climate than the western coasts (greater temperature fluctuations)

– The extent of this difference should be proportional to the size of the temperate zone hinterland

– Because of the coriolis effect winds going toward the poles will be deflected to the west, and those going toward the equator will be deflected toward the east (ergo, Westerlies vs. Trade winds)

– Large continents have a distorting effect all around them due to their massive temperature fluctuations. The larger the continent, the bigger the distorting effect (ergo, the most famous “monsoon” generated by the hyper-heating of continental interiors is the Asian one, even though there are monsoons operative in North America and Africa)

• Category: Science • Tags: Climate, Geography 
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Credit: David Shankbone

The more and more I see fine-scale genomic analyses of population structure across the world the more and more I believe that the “stylized” models which were in vogue in the early 2000s which explained how the world was re-populated after the last Ice Age (and before) were wrong in deep ways. I’m talking about the grand narratives outlined in works such as Bryan Sykes’ The Seven Daughters of Eve, the subtitle of which was “The Science That Reveals Our Genetic Ancestry.” If I had less faith in science to always ultimately right its course I’d probably become a post-modernist type who asserts that all these stories are fictions. Sykes’ model in particular seems to be very likely incorrect because of the utilization of ancient DNA to elucidate population movements past in Europe. From what we can gather it looks like coarse attempts to infer past distributions from current distributions (of specific lineages and their diversity) resulted in a great deal of false clarity. We’re not talking differences on the margins, but fundamental confusions. For example, Basques were always assumed to be a viable “reference” population for descendants of European hunter-gatherers. This was one of the linchpins of older historical genetics models. It turns out that this fixed assumption may have been a false one.

Not only were our past assumptions in simple models wrong, but the real explanations may also be rather complex. It turns out that ancient DNA of the “first farmers” and their “hunter-gatherer” neighbors in Central Europe reveals a lot of discontinuity between both these groups and modern Europeans. Why? It may be that in fact there were multiple migrations, and the palimpsest is going to be a tough cookie to excavate. But there’s no need to be disheartened, the old paradigms came crashing down thanks to data. With that in mind I’ve been particularly interested in the European fringe, the far west and north. If any hunter-gatherer descendants survive in large numbers, it will be here. This is why I’m curious as to the genetics of the Sami as well as the archaeology which tracks the spread of agriculture in Northern Europe. A new paper in PLoS ONE focuses on Sweden, Swedish Population Substructure Revealed by Genome-Wide Single Nucleotide Polymorphism Data:

The use of genome-wide single nucleotide polymorphism (SNP) data has recently proven useful in the study of human population structure. We have studied the internal genetic structure of the Swedish population using more than 350,000 SNPs from 1525 Swedes from all over the country genotyped on the Illumina HumanHap550 array. We have also compared them to 3212 worldwide reference samples, including Finns, northern Germans, British and Russians, based on the more than 29,000 SNPs that overlap between the Illumina and Affymetrix 250K Sty arrays. The Swedes – especially southern Swedes – were genetically close to the Germans and British, while their genetic distance to Finns was substantially longer. The overall structure within Sweden appeared clinal, and the substructure in the southern and middle parts was subtle. In contrast, the northern part of Sweden, Norrland, exhibited pronounced genetic differences both within the area and relative to the rest of the country. These distinctive genetic features of Norrland probably result mainly from isolation by distance and genetic drift caused by low population density. The internal structure within Sweden (FST = 0.0005 between provinces) was stronger than that in many Central European populations, although smaller than what has been observed for instance in Finland; importantly, it is of the magnitude that may hamper association studies with a moderate number of markers if cases and controls are not properly matched geographically. Overall, our results underline the potential of genome-wide data in analyzing substructure in populations that might otherwise appear relatively homogeneous, such as the Swedes.

Playing around with ADMIXTURE I’m now happy to see 350,000 SNPs, but less assured by 29,000 SNPs. After a bunch of pruning I have a data set where individuals have 100,000 SNPs, and that seems marginal when it comes to differentiating variation in Western Europe among populations, though I suppose I didn’t do it very intelligently (i.e., I didn’t try to bias toward ancestrally informative markers).

A major “top line” finding of this paper is that Swedes exhibit more geographical substructure than more numerous populations inhabiting expansive Central European regions. Additionally, though not as distinctive as Finns vis-a-vis other Europeans, they are somewhat distinctive, especially those in the north. The bar plot to the left is generated by STRUCTURE, and you see set sets of populations at particular K’s, each K being a putative ancestral group.

The differentiation within Sweden is evident at higher K’s. That’s striking because notice that the Germans and British don’t exhibit the pattern (they state in the paper that they looked for geographical patterns). But for me what is striking is the disjunction between Scandinavians and continental Germans, and the relative lack of one between the British and the Germans. At K = 5 a difference does crop up. At the top you see Russians, so it looks like blue = Eastern European, while red = Western European, and the Germans are a mix of the two, with the Russians and British representing extreme “types” (again, these are very stylized facts, there are no pure “types). But the break with Swedes occurs at lower K’s. Why? The first thought is water. Water blocks gene flow a great deal, but then what about Britain? I doubt all the sampling in Britain was from the old Saxon Shore of East Anglia! I will hazard a rather general explanation: maybe it’s agriculture! More specifically, the switch to agriculture may have occurred via different demographic processes in the two locales. Britain has a milder climate than Sweden, and could presumably support a more dense transplanted culture more easily than Sweden.

Let’s look at the data in a different way. The figure to the left shows the top two dimensions of variation in the data. The x axis explains 0.64% of the variance, and the y axis 0.24% (these are genetically close groups remember). The bottom left of the distribution consists of Germans, the top of the point the Russians, and to the far right eastern Finns. Finns are something of a European outlier, along with Basques and Sardinians, but it is interesting how much greater east-west distances correspond to less variance than north-south at this scale. On the broader trans-European level north-south differentiation is usually more significant than west-east. Why? I think geography explains it, the Mediterranean and the Atlantic fringe allowed for a rapid expansion of agriculturalists in Southern Europe from their point of origination in Anatolia. The move north was slower, and involved more amalgamation with hunter-gatherers. But, within Northern Europe there were local differences. Inland North European plain with its rich soil and riverine network may have allowed for a great deal of demographic expansion in the face of an extremely thin pre-Neolithic population. But, they met another point of resistance at the oceanic fringe, where maritime resources were great enough to support denser hunter-gatherer populations. This, I suspect, explains the discontinuity at the Kattegat and Skagerak.

Let’s take another look at genetic distance. The visualization to the left is a representation of the Fst between pairs of populations. I’ve added labels. Fst just measures the proportion of genetic variance which can be partitioned between groups. The x axis is the first dimension, and the y the second. That geography is not always a good predictor of genetic distance. Look at how close the sample for Orkney (off the coast of northern Scotland), the British, Germans, and the Utah whites (who are mostly British and German in origin) cluster in terms of genetic distance. In contrast, the French and French Basques differ a great deal.

To illustrate the weirdness of some of the patterns, like a 5 year old I took a blank map of Europe and just drew a line from region to region based on distances on the first dimension (x axis). So you see a zig-zag in Western Europe, a sweep to the east, and finally the terminus in the east of Finland. You’d be surprised how often I want to scribble on a map nonsensically when I see some of the SNP-chip data. Yes, geography does correspond to genetic distance, roughly, but some of the deviations from expectation are really weird. Sardinians and Finns in particular seem to be the extreme points on some broad underlying pattern of genetic variance in Europe. But, obviously the Basques also represent another dimension. A simple model is bound to be wrong, but a complex one is going to be wrong in a lot of the details.

Finally, we’ve been talking about ancestry only. What about functionality? Genes sometimes after code for differences, some of them visible, and many of them significant. Not surprisingly ancient hunter-gatherers who were resident in Sweden were lactose intolerant. Why would they need to be able to digest milk as adults if they didn’t have herds of cattle?

By and large the authors didn’t find much functional significant in the sharp north-south difference in Sweden. But, there were some suggestions (there’s some issues with the statistical likelihood due to the lack of particular precautions which would mitigate against false positives):

Phenotype Unique GWA hits SNPs within 200 kb
Total SNPs with regional differences( p < 0.05)
observed expected chi-square p1
Eye color 9 410 24 34.3 0.08
Hair color 19 774 73 64.8 0.29
Skin pigment 3 140 22 11.7 0
Height 197 8683 680 726.5 0.08
Lactase deficiency LCT gene 34 0 2.8 0.11
Immune system MHC region 1262 162 105.6 0
Blood lipids 92 2465 257 206.2 0
Cardiovascular disease 32 1921 190 160.7 0.02

Why the differentiation? I think this is a clear case of “maybe it’s agriculture.” Northern Sweden was not ethnically cleansed and assimilated of its Sami until the early modern period. These were traditionally non-agricultural people, the closest Europe had to hunter-gatherers (since they herded reindeer they obviously weren’t hunter-gatherers). Some of the difference may simply be a Sami substrate in the north of Sweden, with all the functional differences entailed due to the lack of thousands of years of dense agriculture life.

Citation: Salmela E, Lappalainen T, Liu J, Sistonen P, & Andersen PM (2011). Swedish Population Substructure Revealed by Genome-Wide Single Nucleotide Polymorphism Data PLoS ONE : 10.1371/journal.pone.0016747

• Category: History, Science • Tags: Agriculture, Genetics, Genomics, Geography 
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Since I know plenty of friends are getting, or just got, their V3 results, I thought I’d pass this on, Open-ended submission opportunity for 23andMe data (#2):

Who is eligible

Everyone who is of European, Asian, or North African ancestry and all four of his/her grandparents are from the same European, Asian, or North African ethnic group or the same European, Asian, or North African country.

Also, Zack has more than 30 individuals in HAP. The “cow belt” is still way underrepresented. The only Bengalis in the data set are my parents.

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A comment below inquired about “good books” on American history. Unfortunately I don’t know as much about American history as I do about Roman or Chinese history. But over the years there have been several books which I find to have been very value-add in terms of understanding where we are now. In other words, these are works which operate with a broader theoretical framework, and aren’t just a telescope putting a spotlight on a sequence of facts.

Albion’s Seed. I read this in 2004, and it was a page turner.

The Cousins’ Wars. I had thought of Kevin Phillips as a political writer, but this was a very engaging and deep cultural history. My prejudice resulted in my not reading this until 2009.

What Hath God Wrought. This book focuses on the resistance of the Whigs and Greater New England to the cultural ascendancy of the Democrats and their “big-tent” coalition which included most of the South, the Mid-Atlantic, and much of the “Lower North” (e.g., the “butternut” regions of the Midwest settled from the Border South).

The Rise of American Democracy. This is a good compliment to the previous book, in that it takes the “other side,” that of the Democrats. In many ways this is the heir to Arthur Schlesinger’s Age of Jackson.

Throes of Democracy. A somewhat “chattier” book than the previous ones, it is still an informative read. It covers a period of history with the Civil War as its hinge, and so gives one the tail end of the Age of Sectionalism.

Freedom Just Around the Corner. By the same author, but covering a period of history overlapping more with Albion’s Seed.

The Age of Lincoln. This is not a “Civil War book.” It is of broader scope, though since the the war is right in the middle of the period which the book covers it gets some treatment. I’d judge this the “easiest” read so far of the list.

Replenishing the Earth. This is about the Anglo world more generally, but it is nice to plug in America into a more general framework. North America is not sui generis.

The English Civil War. This is obviously not focused on America, but it is a nice complement to Albion’s Seed, as it shows the very deep roots of the division between two of America’s folkways. The Cousins’ Wars serves as a bridge between the two, shifting as it does between both shores of the Atlantic.

I’m game for recommendations! I had a relatively traditional education in American history, and did very well in my advanced courses, but I knew very little before I read books like this.

• Category: History • Tags: American History, Culture, Geography, History 
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Guelta d’Archei, Chad. Credit: Dario Menasce.

Everyone who is literate knows that the Sahara desert is the largest of its kind in the world. The chasm in cultural, biological, and physical geography is very noticeable. Northern Africa is part of the Palearctic zone, while the peoples north of the Sahara have long been part of the circum-Mediterranean population continuum. The primary continuous habitable corridor is that of the Nile valley. And yet scholars have long known that there has been variation in the climatic regime of the Sahara. The pharaohs of ancient Egypt seem to have hunted a wider range of fauna than is to be found in the deserts surrounding the current Nile valley, perhaps relics from a more humid period. Rock art in some regions of the desert indicate aquatic life, and species more characteristic of the savanna. And yet we should not think of the Sahara as a recent phenomenon; it does seem to be geologically ancient, despite periodic humid interregnums. A new paper in PNAS attempts to map the hydrography of the Sahara over the Holocene, as well as back to the Pleistocene. The ultimate aim seems to be to better frame the geographic constraints on the expansion of humanity from its African homeland, and refute a simple projection from the present to the past. In this case, it is the existence of the Nile as a verdant and habitable watercourse which connects the north and south, and bisects the continuous desert. Ancient watercourses and biogeography of the Sahara explain the peopling of the desert:

Evidence increasingly suggests that sub-Saharan Africa is at the center of human evolution and understanding routes of dispersal “out of Africa” is thus becoming increasingly important. The Sahara Desert is considered by many to be an obstacle to these dispersals and a Nile corridor route has been proposed to cross it. Here we provide evidence that the Sahara was not an effective barrier and indicate how both animals and humans populated it during past humid phases. Analysis of the zoogeography of the Sahara shows that more animals crossed via this route than used the Nile corridor. Furthermore, many of these species are aquatic. This dispersal was possible because during the Holocene humid period the region contained a series of linked lakes, rivers, and inland deltas comprising a large interlinked waterway, channeling water and animals into and across the Sahara, thus facilitating these dispersals. This system was last active in the early Holocene when many species appear to have occupied the entire Sahara. However, species that require deep water did not reach northern regions because of weak hydrological connections. Human dispersals were influenced by this distribution; Nilo-Saharan speakers hunting aquatic fauna with barbed bone points occupied the southern Sahara, while people hunting Savannah fauna with the bow and arrow spread southward. The dating of lacustrine sediments show that the “green Sahara” also existed during the last interglacial (∼125 ka) and provided green corridors that could have formed dispersal routes at a likely time for the migration of modern humans out of Africa.

This paper was written before the Denisovan admixture results shifted the necessity to genuflect so explicitly to Out of Africa. But its results are interesting nonetheless, since they don’t depend too deeply on a paleoanthropological model. Rather, by surveying biogeogeography and geologic data they produce a sense of how the Sahara exhibited climatic flux over the past 100,000 years as a function of time and space. The latter is important because the Sahara is not an amorphous sandy waste. Rather, it exhibits a great deal of topographical variation:

Credit: T L Miles

In the Tibesti mountains the highest peaks are ~11,000 feet above sea level (3,400 meters). Because of the aridity of the Sahara in general even these elevations does not induce sufficient precipitation to produce a “green mountain” effect, common in other arid parts of northern Africa and Arabia. But in a regime of slightly only higher precipitation and milder temperatures (remove 3 degrees fahrenheit per 1,000 feet against latitude controlled sea level temperature) one can imagine the Tibesti having been much more biologically productive in the past. Consider this from the Tassili n’Ajjer region of southern Algeria:

Because of the altitude and the water-holding properties of the sandstone, the vegetation is somewhat richer than the surrounding desert; it includes a very scattered woodland of the endangered endemic species Saharan Cypress and Saharan Myrtle in the higher eastern half of the range.

The range is also noted for its prehistoric rock paintings and other ancient archaeological sites, dating from neolithic times when the local climate was much moister, with savannah rather than desert. The art depicts herds of cattle, large wild animals including crocodiles, and human activities such as hunting and dancing….

The main thrust of the paper seems to be to refute the common assumption that an eternal Nile served as the north-south corridor for African fauna, including humans. Here is the reason:

Reanalysis of the Saharan zoogeography…suggests that many animals, including water-dependent creatures such as fish and amphibians, dispersed across the Sahara recently. For example, 25 North African animal species have a spatial distribution with population centers both north and south of the Sahara and small relict populations in central regions. This distribution suggests a trans-Saharan dispersal in the past, with subsequent local isolation of central Saharan populations during the more recent arid phase. If a diverse range of species (including fish) can cross the Sahara, it is impossible to envisage the Sahara functioning as barrier to hominin dispersal. The zoogeography of the Nile suggests that it was a much less effective corridor…Only nine animal species that occupy the Nile corridor today are also found both north and south of the Sahara….

There are also isolated pieces of evidence which refute a Nile-only model: Saharan oases which have endemic species of crocodiles. The existence of “desert crocodile” populations is a signal of a more well-watered past, with a subsequent retreat into isolated oases (some of these populations did go extinct in the 20th century though). In some ways this is a problem. Simple models make simple predictions, and are easier to test. But if simple models are false, that is an even greater problem.

Here are the figures which outline the primary results from geology and biogeography:

[nggallery id=27]

There are two primary inferences made in regards to humans:

1) The Holocene inference seems to be that Nilo-Saharan populations have their origins in the societies which expanded north and south along the liminal zone of the Sahara. The authors argue that Nilo-Saharan populations on isolated oases in the northern Sahara are relics from the past expansion in the early Holocene. This sounds plausible, but it would be nice to explore this in more depth via linguistic and genetic analysis. With the rise of the camel and Islam a trans-Saharan trade in humans may have resulted in a great deal of trans-location of whole populations from one area to another. Concurrent with the Nilo-Saharans who pushed north the authors also suggest that savanna hunters moved south. I am not clear who these people are from the paper, and the mapping between archaeology and linguistics here seems more tentative.

2) A deep history inference also seems to be that trans-Sahara population movements were feasible in a period around 120-100 years BP, but not 50-60 years BP. The distinction here matters because the latter is a relatively young age for the Out of Africa migration, while the former is an older one. If the latter view is correct then the only plausible route of migration is probably the coastal fringe of the Horn of Africa. If the former view is correct then a whole host of possibilities confront us, because the hydrography of the Sahara may have been constrained, but there were several avenues of migration.

In regards to #2, a clement phase, and then resealing of the genetic barrier, may align well with recent models which posit a non-trivial period of separation between Africans and non-Africans after the Out of Africa migration. In other words early modern humans may have followed the pattern of many species, with an expansion into, and beyond, the Sahara, and then a subsequent separation of two populations by a resurgent desert. The difference is that the daughter population isolated on the far side of the desert eventually “broke out” from the margins of the African homeland to the rest of the world.

Citation: Drake NA, Blench RM, Armitage SJ, Bristow CS, & White KH (2010). Ancient watercourses and biogeography of the Sahara explain the peopling of the desert. Proceedings of the National Academy of Sciences of the United States of America PMID: 21187416

• Category: Science • Tags: Geography, Human Evolution, Out-of-Africa 
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I decided to take the Dodecad ADMIXTURE results at K = 10, and redo some of the bar plots, as well as some scatter plots relating the different ancestral components by population. Don’t try to pick out fine-grained details, see what jumps out in a gestalt fashion. I removed most of the non-European populations to focus on Western Europeans, with a few outgroups for reference.

Here’s a table of the correlations (I bolded the ones I thought were interesting):

W Asian NW African S Europe NE Asian SW Asian E Asian N European W African E African S Asian
W Asian * -0.01 -0.18 0.04 0.81 0.59 -0.64 0.39 0.2 0.04
NW African * * 0.19 -0.16 0.23 -0.09 -0.19 0.26 0.67 -0.11
S European * * * -0.38 -0.03 -0.27 -0.42 -0.11 -0.02 -0.36
NE Asian * * * * -0.06 0.5 0.26 -0.04 -0.1 -0.07
SW Asian * * * * * 0.21 -0.62 0.74 0.59 -0.13
E Asian * * * * * * -0.27 0.08 0 0.14
N European * * * * * * * -0.34 -0.28 -0.31
W African * * * * * * * * 0.86 -0.04
E African * * * * * * * * * -0.07

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EarWhen I was in college I would sometimes have late night conversations with the guys in my dorm, and the discussion would random-walk in very strange directions. During one of these quasi-salons a friend whose parents were from Korea expressed some surprise and disgust at the idea of wet earwax. It turns out he had not been aware of the fact that the majority of the people in the world have wet, sticky, earwax. I’d stumbled onto that datum in the course of my reading, and had to explain to most of the discussants that East Asians generally have dry earwax, while convincing my Korean American friend that wet earwax was not something that was totally abnormal. Earwax isn’t something we explore in polite conversation, so it makes sense that most people would be ignorant of the fact that there was inter-population variation on this phenotype.

But it doesn’t end there. Over the past five years the genetics of earwax has come back into the spotlight, because of its variation and what it can tell us about the history and evolution of humans since the Out of Africa event. Not only that, it seems the variation in earwax has some other phenotypic correlates. The SNPs in and around ABCC11 are a set where East Asians in particular show signs of being different from other world populations. The variants which are nearly fixed in East Asia around this locus are nearly disjoint in frequency with those in Africa. Here are the frequencies of the alleles of rs17822931 on ABCC11 from ALFRED:
abcc11A The expression of the dry earwax phenotype is contingent on an AA genotype, it has recessive expression. So in a population where the allele frequency of A ~0.50, the dry earwax phenotype would have a ~0.25 frequency. In a population where the A allele has a ~0.20 frequency, the dry earwax phenotype would be at ~0.04 frequency. Among people of European descent the dry earwax phenotype is present at proportions of less than ~5%. Because of recessive expression a larger minority of Japanese and Chinese should manifest wet earwax, though interestingly the ALFRED database indicates that Koreans are fixed for the A allele. In Africa conversely the G allele seems to be fixed.

So the question is: why? A new paper in Molecular Biology and Evolution argues that the allele frequency differences are a function of positive directional selection since humans left Africa ~100,000 years ago. The impact of natural selection on an ABCC11 SNP determining earwax type:

A nonsynonymous single nucleotide polymorphism (SNP), rs17822931-G/A (538G>A; Gly180Arg), in the ABCC11 gene determines human earwax type (i.e., wet or dry) and is one of most differentiated nonsynonymous SNPs between East Asian and African populations. A recent genome-wide scan for positive selection revealed that a genomic region spanning ABCC11, LONP2, and SIAH1 genes has been subjected to a selective sweep in East Asians. Considering the potential functional significance as well as the population differentiation of SNPs located in that region, rs17822931 is the most plausible candidate polymorphism to have undergone geographically restricted positive selection. In this study, we estimated the selection intensity or selection coefficient of rs17822931-A in East Asians by analyzing two microsatellite loci flanking rs17822931 in the African (HapMap-YRI) and East Asian (HapMap-JPT and HapMap-CHB) populations. Assuming a recessive selection model, a coalescent-based simulation approach suggested that the selection coefficient of rs17822931-A had been approximately 0.01 in the East Asian population, and a simulation experiment using a pseudo-sampling variable revealed that the mutation of rs17822931-A occurred 2006 generations (95% credible interval, 1023 to 3901 generations) ago. In addition, we show that absolute latitude is significantly associated with the allele frequency of rs17822931-A in Asian, Native American, and European populations, implying that the selective advantage of rs17822931-A is related to an adaptation to a cold climate. Our results provide a striking example of how local adaptation has played a significant role in the diversification of human traits.

The region around ABCC11 has come under scrutiny with the emergence of tests of natural selection predicated on inspecting patterns of linkage disequilibrium (LD). LD is basically measuring the association of genetic variants within the genome shifted away from expectation. A selective sweep tends to generate a lot of LD around the target of natural selection because as the allele in question rises in frequency its neighbors also hitchhike along. The hitchhiking process means that within a population you may see regions of the genome which exhibit long sequences of correlated single-nucelotide polymorphisms (SNPs), haplotypes. An initial selective event will presumably generate a very long homogenized block, which over time will break apart through recombination and mutation, as variation is injected back into the genome. The extent and decay of LD then can help us gauge the time and strength of selection events.

But LD can emerge via other processes besides natural selection. Imagine for example that a population of Africans and Europeans mix in a given generation. Europeans and Africans have different genetic makeups, on average, so the initial generations will have more LD than expectation because recombination will only slowly break apart the physical connection between genomic regions from European and African ancestors. The decay of LD then can give one a sense of the time since admixture as well as selection. Not only that, stochastic demographic events and processes are also important and may drive the emergence of LD. Consider a bottleneck where the frequency of a particular haplotype is driven up by random genetic drift alone. The details of these alternative scenarios are explored in the 2009 paper The role of geography in human adaptation.

All this is preamble to the fact that there’s a lot of LD around ABCC11. Here’s a visualization from the HapMap populations:


abc11From left to right you have Chinese & Japanese, Utah whites, and the Yoruba from Nigeria. An absolute value of D’ ~0 means that there’s linkage equilibrium; the default or null state where there are no atypical excessive correlations of alleles across the genome. The axes here are pairwise combinations of SNPs around ABCC11, with a focus around rs17822931, a nonsynonymous SNP which seems to be the likely functional source of the variance in earwax and other phenotypes. In terms of LD rank order the results are not surprising, across the genome East Asians tend to exhibit more LD than Europeans, and Europeans exhibit more LD than the Yoruba. Part of this is probably a function of population history, a serial bottleneck model Out of Africa would posit that drift and other stochastic forces would have a stronger impact on the genomes of East Asians than Europeans. But this seems like it can’t be the whole picture here; note the variance in allele frequency in the New World as well as in Oceania. Some of the Amerindian populations seem to have a higher frequency of the ancestral G allele on rs17822931. The figure above is easier to understand, the Y-axis is showing you the extent of heterozygosity at a given location. GA is heterozygous, GG is homozygous. Africans again tend to exhibit more heterozygosity than non-Africans, but note the sharply diminished heterozygosity for the East Asian sample around rs17822931 in ABCC11. Remember that heterozygosity tends not to go above 0.50 in a random mating population in a diallelic model (though in selective breeding it may go above 0.50 for F1 generations).

The major findings of this paper beyond what was known before seem to be a) an explicit model of how East Asians could have arrived at a high frequency of the AA genotype at rs17822931, and, b) the correlation between climate and the frequency of A. I’ll get to the second point in a bit, but what about the first? Using the nature of variation in two microsatellites flanking the SNP of interest in East Asians, and assuming a recessive selection model, the authors posit that the A allele began to rise in frequency ~50,000 years ago, and, that the selection coefficient was ~1% per generation. This a significant value for the selection parameter, and the timing is possible in light of the separation of non-Africans into a western and eastern group around that period.

But honestly I’m pretty skeptical of this. The confidence intervals don’t inspire confidence, and from what little I know selection for recessive traits should exhibit less linkage disequilibrium. At low frequencies there is very little affect of natural selection on the allele because it is mostly “masked” in heterozygotes, and therefore there will be a long period before its proportion begins to rise more rapidly. During this time recombination will have time to chop up the haplotypes around the SNP, reducing the length of the statistically associated haplotype block. Also, the authors themselves don’t seem to believe that the phenotype of earwax itself was the target of selection, so its recessive expression pattern should be less important from where I stand.

abcc11dThe idea that the genes around ABCC11 might have something to do with adaptation to cold is suggestive, but almost every East Asian trait of distinction has been hypothesized to have something to do with cold at some point by physical anthropologists. You’d figure that the Cantonese lived in igloos going by all the myriad adaptations to frigid conditions which they exhibit. The reality is that much of China, Korea and Japan are subtropical today. In any case the last figure shows the correlation across several lineages. Earlier they found that by comparing variation around this region in humans with other primates that Africans seem to be subject to purifying selection. This means that there’s constraint so that neutral forces don’t change the frequencies of functionally significant regions. It is well known that on average Africans are more diverse than non-Africans, probably because the latter are a sampling of the former, but, on a small minority of genes the reverse is true. This is likely due to the relaxation of functional constraint as humans left the ancestral African environment. And this is clearly true for rs17822931; most non-African populations exhibit some heterozygosity. East Asians here are an exception, not the rule, at having derived allele frequencies nearly fixed. The regression lines in this last figure are all statistically significant. It is interest that there are particularly strong correlations between latitude and and frequency of the derived A allele among Europeans and Native Americans. In contrast the relationship within Asian populations is weaker. Only 17% of the allele frequency variance can be explained by latitude variance among the Asian ALFRED sample.

But we shouldn’t allow the hypothesis to rise and fall just on this evidence. After all there have likely been substantial movements of populations within the last 10,000. Perhaps especially in East Asia, where the expansion of the Han south may have triggered the movement of both the Thai and Vietnamese people out of South China and into mainland Southeast Asia. The best evidence of adaptation would be among admixed populations; presumably those at higher latitudes would have higher frequencies of the AA genotype than those at lower latitudes. Instead of categorizing the populations into three coarse classes probably a more sophisticated treatment using ancestral quanta derived from STRUCTURE or ADMIXTURE as independent variables would be informative. Remember, adaptation should show evidence of decoupling ancestry from phenotype.

Finally, I have to point to this section of the discussion:

What is the cause of the selective advantage of rs17822931-A? Although the physiological function of earwax is poorly understood (Matsunaga 1962), dry earwax itself is unlikely to have provided a substantial advantage. The rs17822931-GG and GA genotypes (wet earwax) are also strongly associated with axillary osmidrosis, suggesting that the ABCC11 protein has an excretory function in the axillary apocrine gland (Nakano et al. 2009)…,

I really didn’t know what this meant. So I looked it up. Here’s what I found, A strong association of axillary osmidrosis with the wet earwax type determined by genotyping of the ABCC11 gene:

Apocrine and/or eccrine glands in the human body cause odor, especially from the axillary and pubic apocrine glands. As in other mammals, the odor may have a pheromone-like effect on the opposite sex. Although the odor does not affect health, axillary osmidrosis (AO) is a condition in which an individual feels uncomfortable with their axillary odor, regardless of its strength, and may visit a hospital. Surgery to remove the axillary gland may be performed on demand. AO is likely an oligogenic trait with rs17822931 accounting for most of the phenotypic variation and other unidentified functional variants accounting for the remainder. However, no definite diagnostic criteria or objective measuring methods have been developed to characterize the odor, and whether an individual suffers from AO depends mainly on their assessment and/or on examiner’s judgment. Human body odor may result from the breakdown of precursors into a pungent odorant by skin bacteria….

Perhaps the paper should have been titled “why barbarians smell bad”? In any case, an idea for a book title on Korean genetics: “the least smelly race.”*

Citation: Ohashi J, Naka I, & Tsuchiya N (2010). The impact of natural selection on an ABCC11 SNP determining earwax type. Molecular biology and evolution PMID: 20937735

* I’m referencing The Cleanest Race.

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There’s a lot of stuff you stumble upon via Google Public Data Explorer which you kind of knew, but is made all the more stark through quantitative display. For example, consider Saudi Arabia and Yemen. In gross national income per capita the difference between these two nations is one order of magnitude (PPP and nominal). Depending on the measure you use (PPP or nominal) the difference between the USA and Mexico is in the range of a factor of 3.5 to 5. Until recently most Americans did not know much about Yemen. It was famous for being the homeland of Osama bin Laden’s father and the Queen of Sheba.

Let’s do some comparisons.

Good luck Saudi Arabia! 🙂 Couldn’t happen to a nicer nation.

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Languages_of_EuropeTo the left you see a map of the distribution of languages and language families in Europe. Language is arguably the most salient cultural feature of our species, as well as one of the most obviously biologically embedded. The trait of language is a human universal, to the point where even those without hearing can create their own gestural languages de novo. But the specific nature of language as it is instantiated from region to region varies greatly. Language in the generality is a straightforward utility with which you communicate with your fellow man. But language also separates you from your fellow man.

European nationalism in the 19th and 20th centuries was in large part rooted in the idea that language defined the boundaries of a nation. During the Reformation era some German-speaking Roman Catholic priests declaimed the value of the bond of language against that of religion, praising those non-Germans who adhered to the Catholic cause against German speaking heretics (in the specific case the priest was defending Spanish tercios brought in by the Holy Roman Emperor to put down the rebellion of Protestant German princes). In the long centuries between the Reformation and the Enlightenment the idea of a Western Christian Commonwealth slowly melted in the face of the rise of vernacular, but even after the shattering of Western Christianity with the explosion of Reformations the accumulated capital of a unified Christian European elite persisted. Hungarian Protestant students at Oxford could make do with Latin even if they were totally innocent of English (see The Reformation). Newer lingua francas, French and later English, lack the deep unifying power of Latin in part because they are also living vernaculars. They may resemble Latin in some particulars of function, but eliding the differences removes far too much from the equation to be of any use. Linguistic diversity is a fact of our universe, but how it plays out matters a great deal, and has mattered a great deal, over the arc of history.

806-8 This is the subject of Empires of the Word: A Language History of the World. Nicholas Ostler, the author, tackles an enormous subject here. He acknowledges the Herculean nature of his task in the introduction. And yet he does avoid some of the more intractable controversies within historical linguistics by constraining his subject matter to the period of history. That is, where we have some written records. This means that Ostler does not address the origins of the Indo-European language family, or the more recent expansion of the Bantus. Despite being separated by thousands of years these are both in the domain of pre-history, because we have no written records of proto-Bantu or proto-Indo-European. This does not mean that the book is not ambitious all the same. On the contrary, Empires of the Word takes on the “thicker” and messier tangle which is the association between language and fine-grained historical processes, social, cultural, economic and political. How history has shaped the nature and distribution of languages which we see extant in our world today is a labyrinth with many doors. Ostler doesn’t come close to opening the majority of those doors, but those he selects in Empires of the Word yield a rich number of surprises and insights, though he does not in the end seem to be able to generate a Grand Unified Theory of linguistic diversity and change from the welter of details.

top-20-languagesThere are two parallel threads throughout Ostler’s narrative: description and prediction. The latter is not prediction as a physicist would predict, rather, it is as a historical scientist might. Taking the data and producing models which can plausibly explain the phenomena we describe. Let’s take a look at the top 20 languages in the world . It seems that there are two primary ways that the speakers of a language can become numerous: rice & empire. Such a generalization is a bit glib, as many Mandarin speakers do not live by the “rice bowl,” but the big picture is that some languages gained adherents through “brute force,” pushing inexorably against the Malthusian possibilities of primary production and reproduction and assimilating smaller groups on the wave of advance of the speakers. The Asian languages on this list fall into that category. In contrast, you have the languages which spread with empire, exploration, and colonialism. English and Spanish are the exemplars of this class. Of the hundreds of millions of English and Spanish speakers a majority can not be accounted for simply by demographic expansion of the home countries. Rather, these languages colonized new lands, and acquired new speakers, rather rapidly over the past 500 years. Turkish is almost certainly in this category, though the transition from Greek, Armenian and Kurdish speech in Anatolia is less clearly understood because of thinner textual records of the process.

Of course the distinction between the two is somewhat artificial. The expansion of Mandarin, let alone the Chinese dialects, was almost certainly a synthesis of demographic expansion & migration, and linguistic assimilation of “barbarians.” Han Chinese are a genetically far less homogeneous than the Koreans or Japanese, in large part because the expansion of Han identity occurred over a diverse group of populations which were resident within China proper 2,000 years ago. Similarly, it seems implausible that the Vietnamese ethnically cleansed all the Malay and Khmer speaking populations along the Annamese coast as they pushed toward the Mekong delta. The genetic data in fact hint to a large scale assimilation of Malay Chams by the Vietnamese. Inversely, the rise of English was partially accompanied by the demographic explosion of British peoples, while Spaniards contributed a great deal genetically to the mestizo populations of the New World. So it is not rice or empire, but rice and empire. Albeit with different weights on a case-by-case basis.

“Rice” really refers to social, cultural and economic forces which bubble up from below and swallow up the numerous islands of linguistic diversity. “Empire” connotes the political and military structure which allows for the trickle down from above of imperial values and mores. But the two are also intimately connected. The Chinese state under the Ching Dynasty saw a rapid rise in population, and that rise was enabled in large part due to political stability. That stability fostered long term projects which increased the land under cultivation as well as public works infrastructure which could distribute grain so as to dampen the effect of local shocks. The Greek historian Polybius attributed the resiliency and strength of the Roman state in to its assimilative capacity, turning barbarians into citizens. The military and political resiliency of the Roman Empire through the Crisis of the Third Century was probably conditioned on the expansion of Romanitas from the the Atlantic to the Black Sea (the military core of the revival drew from the Latin speaking regions south of the Danube in the Balkans).

Just as the Roman Catholic Church is sometimes referred to as “the ghost of the deceased Roman Empire,” so the distribution of modern languages are tells of political, social and economic events of the past. Social and economic forces almost certainly loom large in language family explosions which Ostler did not cover, that of the Bantus, the Polynesians and Indo-Europeans. In the first case it seems that the Bantu peoples brought with them a new mode of production to east and south Africa. This was then a rice expansion, along with some genetic assimilation. The case of the Polynesians is more difficult, but the existence of a similar group in Madagascar, attests to the power of long distance seafaring techniques in scattering obscure peoples. Without the existence of Malagasy, both their genetic and linguistic uniqueness, the written record would not clue us in to the existence of an organized community of long distance seafaring Southeast Asians across the Indian ocean basin. Finally, the Indo-European expansion is more mysterious because it is so much further back in time, but it is also the most significant as nearly half the world’s population speaks an Indo-European language. David Anthony in The Horse, the Wheel, and Language: How Bronze-Age Riders from the Eurasian Steppes Shaped the Modern World makes the case that a shift toward nomadic pastoralism enabled by the horse is the critical catalyst for the sweep of this language group from the Atlantic to the Bay of Bengal.

Though the Indo-European case is likely an ancient one Empires of the Word actually begins its story earlier. Ostler’s in depth knowledge of ancient Near Eastern linguistic history is frankly mind-blowing, and is arguably the most insightful and novel spin on the topic I’ve ever encountered. The extent of detailed and subtle grasp of the facts is awe inspiring. I did not know, for example, that the Elamites of southwest Iran once had their own writing system, which they eventually abandoned for Akkadian cuneiform. Ostler recounts the life-after-death which Sumerian experienced for over 1,000 years because of the nature of cuneiform itself, which was fitted to the Sumerian language, a linguistic isolate with no known relatives. For the last thousand years of cuneiform it was written in Akkadian, the first great Semitic language in the world, later to be succeeded by Aramaic, Punic, Hebrew, and Arabic. Parallel to the waxing and waning of these antique Semitic languages was the ebb and flow of ancient Egyptian, with its own peculiar form of writing.

One aspect of these ancient societies and their languages is the almost cold-blooded torpidity with which change occurred. Sumerian persisted as a liturgical language in what became Babylonia down to the Roman and Parthian period, 3,000 years of written history. The social-political entity which we term ancient Egypt arguably spanned 2,500 years, up until the final Persian conquest. Egyptian culture in a sense that the Pharaohs would recognize persisted for another 1,000 years, until the closure of the Temple of Philae under the orders of the Christian Emperor Justinian in the 6th century. This cut the last link with the literature and religion of ancient Egypt. Consider that the time between our own era and that of Jesus Christ is equivalent to that between the rise of the Egyptian polity and its decline in the late Bronze Age. Though there are certainly similarities between Paul of Tarsus and a modern Western man, a great many disruptions have broken chains of cultural continuity.

There may be one exception to this, and that is another language which arose just as Egypt went into decline, and that is Chinese. Classical Chinese in its written form remained relatively static between the ancient period of the first dynasties, and the early 20th century. This continuity is telling insofar as Western scholars never had to “discover” the history of the Chinese, they had always remembered it. The continuity of language, culture values, and political and ethnic identity, dovetailed together so that despite the reality that the architecture of China is ephemeral, its stories are not. In contrast, much of the literary corpus of the ancient Western world comes down to us only because of three intense periods of copying: the Carolingian Renaissance, 10th century translations in the Byzantine Empire, and the Abbasid translation project in the 9th century. The history of the societies before Greece was perceived only obliquely through the Bible and the classical authors. Modern archaeology and linguistics eventually unlocked the secrets of both hieroglyphics and cuneiform, but the reality that we did not know of the significance of the Hittites in the ancient world attests to the poverty of knowledge which lack of cultural continuity imposes (the great disruption between the Indus civilization and pre-Maurya India means that the script of the former remains lost to us).

The distribution and continuity of dead languages also is a signpost for that other aspect of human culture which is very powerful and ubiquitous: religion. Today most of the Latin spoken is “Church Latin,” and that is because of the languages sacred role within the Roman Catholic Church. Though Hebrew is the spoken language of the secular state of Israel thanks to a modern revival, for nearly 2,500 years it was a language of religion only, as the Jews adopted the languages of the people amongst whom they lived, Aramaic, Greek, Persian, Arabic, Latin, German, etc. The ancient languages of the Near East, Coptic from ancient Egyptian, and Syriac from Aramaic, persist as liturgical languages. It seems that so long as the gods do not die in the minds of believers the tongues of the ancients persist down the ages. So next to the language of rice and empire, you have languages of the gods.

As I indicated above Empires of the Word is rather thin on robust generalizations. But one point which the author mentions repeatedly is that the rise and fall of languages of great expanse and utility is the norm, not the exception. In particular, Nicholas Ostler takes time out to emphasize that languages which spread via trade often do not have long term staying power. Portuguese, Aramaic, Punic and Sogdian would fall into this category (the later success of Portuguese was a matter of rice and empire in Brazil). It seems that mercantile communities are too ephemeral, that successive historical shocks inevitably result in their decline when there isn’t a peasant demographic reservoir or imperial power which imposes it by fiat. Even those languages which eventually spread beyond traders and gain cultural and political cachet may fall from grace. Greek is the best case of this. It was the dominant language of the Roman East, and spoken as far as modern Pakistan, and studied in Dark Age Ireland. By the early modern period it was a strange and foreign language in the West, and with the rise of Islam in the east it lost its cultural glamor, and even those Christians in Arab lands who were Melkite, Greek Orthodox who adhered to the theological position of Constantinople, became Arab in speech and identity (in greater Syria the Greek Orthodox have been instrumental in the formulation of Arab nationalism).

And yet to some extent one must be cautious about over-reading the recession of Greek in the face of Arabic after the rise of Islam. Ostler repeats the conventional wisdom that the predominant vernacular in the Roman East was never Greek, but rather Semitic dialects descended from Aramaic. This is manifest in the fact that the Oriental Orthodox churches do not use Greek in their liturgy, but forms of Syriac. Their root is in an alternative intellectual tradition from that of the Greek Church. The transition to Arabic was then predominantly from a closely related Semitic language, not from Greek. One of the theses to explain the spread of Arabic across North Africa, but not into Persia, is that Arabic found it easier to replace other members of the Afro-Asiatic language family. I can accept that people can intuitively perceive differences of language family without a deep knowledge of said languages. In Sons of the Conquerors: The Rise of the Turkic World it is recounted that an ambassador to the court of the Hapsburg Emperor in Vienna communicated to the Sultan that apparently the locals spoke a dialect of Persian! Persian and German are of course both Indo-European languages, and set next to Turkish they may sound vaguely similar.

This thesis is plausible to me, and I have long held to it in regards to Arabic’s replacement of Aramaic. I have been told by a friend who is familiar with both languages (in addition to Hebrew) that they are rather close, and if not intelligible close enough to make language acquisition much easier. But Ostler extends the argument much further, suggesting that genetic affinity also explains the replacement of Egyptian and Berber dialects in North Africa. These are Afro-Asiatic languages, but they are not Semitic. I assume linguists do perceive similarities of character which can connect these languages, but what features span the Afro-Asiatic languages which would make language acquisition easier even at this remove of relationship? The Afro-Asiatic theory for the spread of Arabic is somewhat convenient in that it does explain the data well: Arabic has spread widely only in regions of other Afro-Asiatic languages, the exception being in Spain. And in Spain the Mozarab dialect had a stabilized existence with the Romance language of the rural areas, which eventually came back in the form of Castilian, Portuguese, etc. What Nicholas Ostler seems to be proposing is that the world of language acquisition is not flat. This is clearly true for closely related languages, but I think the thesis needs to be explored for distantly related languages from the same family. Does a native speaker of Marathi have a leg up on a Hungarian when it comes to learning Gaelic? I remain skeptical of the affirmative in that case.

So Empires of the Word outlines some broad generalizations of how languages grow, which seem born out by the record of history, and offers some more speculative theories about the importance of the cultural terrain upon which languages can flow and spread. But the narrative also lingers long on the future of the current lingua franca of our age, English. Nicholas Ostler does nothing to dismiss the omnipresence of English at the commanding heights of international culture. He reports for example that in 1994 50% of international telephone calls were between English speakers. 45% were between English speakers and those who were not English speakers! That means only 5% of international calls in 1994 were cases where people neither spoke English as their native language. I suspect that the numbers have changed a bit since then, but if that study is correct then it points to the awesome international spread of the English language. But Nicholas Ostler does not think that it will last, and his rationale seems to be the record of history, where such universal languages always fall. His next book, The Last Lingua Franca: English Until the Return of Babel outlines his thesis in detail.

And yet contra Ostler I have to suggest that perhaps this time it’s different. I do not believe that English in a unified form will dominate all. Already there has been considerable dialect drift. But the past 200 years are qualitatively different from what has come before, and there is already a revolution in communication technology. It may be that in the future languages do not crystallize as a function of geography, but perhaps more as a function of class and occupation. It does seem historically that trade lingua francas have been ephemeral in impact, and English, the language of McWorld, is the language of capital. But the modern world is much more dependent on flows of capital and commerce than the pre-modern world, the Sogdians and Portuguese were primarily vectors for high value luxury goods. Pre-modern capitalism had the air of a parlor game between the high and mighty, and was quite often in bad odor among rentier elites themselves. It is with reason that I observed above that the pace of cultural change in the past was less than what it is today. Positive feedback loops may be much more powerful than they once were, so that a “Globish” derived from English may quickly sweep away all comers, before it diversifies again.

But really I should wait for Ostler’s new book. The arguments I make here may be addressed, or I may misunderstood what I gleaned from Empires of the Word. It is as I said a story with rich and vibrant detail, much of which I glossed over, or did not address. For that Ostler’s tale is worth the time it takes to complete it. But there is I must say a lack of theoretical punch and heft. Perhaps this is just a function of the subject domain, which has too much complexity to distill down to any model of elegance or tractability. But I suspect a more rigorous analytical framework could squeeze some juice out of the enormous pile of detail which Nicholas Ostler has at his disposal. Perhaps he should read Replicated Typo.

Image Credit: Wikimedia, Ethnologue

• Category: Science • Tags: Anthropology, Culture, Empires of the Word, Geography 
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It’s easy to find maps of American ancestries, but I wanted to play around with the data, and in particularly the visualization myself. So I went to the Census and got the county level numbers. The first thing I wanted to do was look at non-Hispanic white ethnicities as a proportion of non-Hispanic whites. That would for example increase the Anglo-Saxon character of the lowland South because it would remove African Americans from the equation.

All the data was from the 2000 Census, and I simply divided the % of each European ancestry group by the non-Hispanic white percentage to reweight appropriately. Here are some correlations I found:

English X Scots-Irish = 0.34

English X Irish = 0.30

English X American = -0.20

Scots-Irish X Irish = 0.37

Scots-Irish X American = -0.25

Irish X American = -0.45

I left the Scottish and Welsh out of this because their numbers were relatively small. One of the main issues with look at the “Irish” and “American” category is that both of these are probably heavily loaded with Scots-Irish. Below the fold are some maps I generated.

Blue = above the median for the frequency of that group nationally (the median being calculated again with non-Hispanic whites only included).

Red = below the median.

The distributions of frequencies by county tend to be positively skewed, so the shading is covering a larger spectrum of frequencies in the blue than the red.

Min = 1.6%
25% = 8.5%
Median = 11%
75% = 14%
Max = 48%

Min = 0%
25% = 1%
Median = 2%
75% = 3%
Max = 10%

Min = 2%
25% = 10%
Median = 12%
75% = 14%
Max = 37%

Min = 0%
25% = 7%
Median = 14%
75% = 22%
Max = 70%

“Isles” includes Scottish & Welsh, as well as “American.”

Min = 9%
25% = 39%
Median = 44%
75% = 51%
Max = 85%

Finally, here’s a map where those of “Isles” origin are 50% or more of the non-Hispanic white population.

The shading for the “Isles” doesn’t look right. But here’s the histogram:

The median is 0.45. So that’s probably why the blue is relatively homogeneous, the distribution is negatively skewed.

• Category: Science • Tags: Geography 
Razib Khan
About Razib Khan

"I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. If you want to know more, see the links at"