Community differentiation and kinship among Europe’s first farmers (via Dienekes):
Community differentiation is a fundamental topic of the social sciences, and its prehistoric origins in Europe are typically assumed to lie among the complex, densely populated societies that developed millennia after their Neolithic predecessors. Here we present the earliest, statistically significant evidence for such differentiation among the first farmers of Neolithic Europe. By using strontium isotopic data from more than 300 early Neolithic human skeletons, we find significantly less variance in geographic signatures among males than we find among females, and less variance among burials with ground stone adzes than burials without such adzes. From this, in context with other available evidence, we infer differential land use in early Neolithic central Europe within a patrilocal kinship system.
I have already stated on this weblog that we will probably begin to discern a rather strong pattern soon of an interleaved genetic pattern across Eurasia and Africa where we can infer that populations in an expansionary demographic phase absorbed a host of other groups (more, or less). The exact details are to be worked out, but I’m moderately confident in this sort of pattern.
But these results align with another of my expectations, which I have rather stronger confidence in: that in parts of Eurasia the emergence of agriculture was correlated with the rise of powerful patrilineal kinship groups, which served as the cores of pre-historic polities. I no longer believe that demographic expansion due to cultural innovation can be separated from the likely political and social consequences of these changes. No, rather what we saw with the rise of agriculture was another powerful social innovation, collective units of large numbers of males who operated as one in the quest for land, women, and material self-enrichment. I do not mean to imply here that violence began with the Neolithic. Rather, I simply believe that the numbers enabled by agriculture allowed for specialization and scalability to fundamentally change the game. This was a high stakes “winner-take-all” bet.
As these males spread across the landscape, enabled by their culture (agriculture) and propagating their culture (language), in many cases their genetic-demographic signal may have been diluted across the wave of advance. But their cultural cohesion remained, and I believe that the patterns of Y chromsomal patterns evident across the modern world are an echo of their elimination of rivals. A tree of many Abels was pruned, as a few Cains proliferated like weeds.
A reader reminded me of an amusing paper, Who Likes Evolution? Dissociation Of Human Evolution Versus Evolutionary Psychology. The gist of the results are below (I added some clarification):
As a follow up to my post below on the thick coverage of European information in genealogical and genomic databases, here are the “Ancestry Finder” matches from 23andMe for my daughter using the default settings:
If I increase sensitivity India does come up, at 0.1%, second to last in a very long list of European nations. I’m pointing this peculiarity out because my daughter is 50 percent South Asian, but this element of her ancestry doesn’t find many matches because there aren’t many people out there in the database to match. In contrast, because she is 1/8th Norwegian (her great-great grandparents were immigrants from the Olso area; thanks Ancestry.com!) this “block” jumps out, and aligns up with many people in their database.
This isn’t just an exceptional case. Here’s the result for a friend who is 50 percent East Asian (Chinese) and 50 percent American white:
The old warning rears its ugly head: the tool is just a tool, and must be used with and understanding of what it can and can’t do. If you decrease sensitivity many South Asians actually match people from European nations before they do people from India. Why? Part of it is probably that many South Asian groups are highly endogamous, which dampens intra-South Asian segment sharing. And the other part is that the sample size of Europeans is so large that random matches with this population are just as, or more, likely than genuine matches with the smaller number of South Asians.
One point which I’ve made on this weblog several times is that on a whole range of issues and behaviors people simply follow the consensus of their self-identified group. This group conformity probably has deep evolutionary origins. It is often much cognitively “cheaper” to simply utilize a heuristic “do what my peers do” than reason from first principles. The “wisdom of the crowds” and “irrational herds” both arise from this dynamic, positive and negative manifestations. The interesting point is that from a proximate (game-theoretic rational actor) and ultimate (evolutionary fitness) perspective ditching reason is often quite reasonable (in fact, it may be the only feasible option if you want to “understand,” for example, celestial mechanics).
I follow CeCe Moore’s blog posts on scientific genealogy pretty closely. But it’s more because of my interest in personal genomics broadly, rather than scientific genealogy as such. My own knowledge of my family’s past beyond the level of grandparents is very sketchy. This despite the fact that I know I have two very well documented lines of ancestry which I could follow up on, my paternal lineage, and the paternal lineage of my mother’s maternal grandfather. I don’t have a great interest in this beyond the barest generalities, and my parents tend to have a rather disinterested stance as well. Why? I can’t help but wonder if part of the issue is that unlike many South Asians my family has a relatively diverse background, so it isn’t as if we are sustained by a coherent self-identity as members of a sub-ethnicity (Bengalis are not tribal, so lineage groups are more ad hoc and informal). Additionally, there is probably some self-selection in the type of personalities who would transplant themselves across continents and are willing to spend the majority of their lives in a nation not of their birth.
Brings back some memories.
And the original….
It’s been a big few weeks for space, with the success of Dragon. I don’t have anything to add in a descriptive or analytic sense, I know as much (or likely less) as you on this issue (this is why should read Bad Astronomy). Needless to say I’ve been rooting for Elon Musk’s enterprise, so to speak. I’m not old enough to remember the “space race,” which put a man on the moon. Rather, for my generation space and NASA had become rather pedestrian, with the shuttle being a sky ferry par excellence. Space is important not because of what it will do for us in concrete terms (e.g., Tang), but what will do for us on a deeper level. Otherwise we may fall prey to the sort of ennui one reads about in science fiction universes such as the city of Diaspar. Remember, we’re the species which made it to the New World and Oceania. This sort of crazy and irrational endeavor is part of who we are.
On a different note, hope people are enjoying the de facto start of the summer (Memorial Day weekend in the USA).
Update: Please do not take the labels below (e.g., “Baloch”) as literal ancestral elements. The most informative way to read them is that they indicate populations where this element is common, and, the relationship of proportions can tell us something. The literal proportion does not usually tell us much.
I was browsing the Harappa results, and two new things jumped out at me. Zack now has enough St. Thomas Christian samples from Kerala that I think we need to accept as the likely model that this community does not derive from the Brahmins of Kerala, as some of them claim. Their genetic profile is rather like many non-Brahmin South Indians, except the Nair, who have a peculiar attested history with the Brahmins of their region.
But that’s not the really interesting finding. Below is a table I constructed from Zack’s data.
Accidental Blogger points me to a rather funny event, the yearly victory of some brown kid in the National Spelling Bee. ‘I was nervous’: Texas whiz kid beats teens in 2012 National Geographic Bee. This Texas whiz kid, Rahul Nagvekar, beat a prodigy from Wisconsin, Vansh Jain. Here were the 10 finalists for the GeoBee:
– Raghav Ranga, Arizona
– Varun Mahadevan, California
– Anthony Stoner, Louisiana
– Adam Rusak, Maryland
– Karthik Karnik, Massachusetts
– Gopi Ramanathan, Minnesota
– Neelam Sandhu, New Hampshire
– Rahul Nagvekar, Texas
– Anthony Cheng, Utah
– Vansh Jain, Wisconsin
Speaking of bees, the National Spelling Bee is coming up. Here are the contestants (page down). And here’s a list of the 2012 Intel Science Contest finalists. And winners of the American Mathematics Competition.
I think it’s great that kids from certain demographics do so well at these academic competitions. But I have to be honest and wonder if sometimes we aren’t seeing individuals who are so focused on the measure, that they forget what we’re trying to measure. God knows I think metrics are very important, but the pursuit of knowledge ultimately has nothing to do with a panel of judges or selection of correct answers. South Korea already exists, it’s a fine enough country, we don’t need to replicate it.
From some of the same people who brought you the genetic map of Europe, a very important paper, A model-based approach for analysis of spatial structure in genetic data. Here’s the abstract:
Characterizing genetic diversity within and between populations has broad applications in studies of human disease and evolution. We propose a new approach, spatial ancestry analysis, for the modeling of genotypes in two- or three-dimensional space. In spatial ancestry analysis (SPA), we explicitly model the spatial distribution of each SNP by assigning an allele frequency as a continuous function in geographic space. We show that the explicit modeling of the allele frequency allows individuals to be localized on the map on the basis of their genetic information alone. We apply our SPA method to a European and a worldwide population genetic variation data set and identify SNPs showing large gradients in allele frequency, and we suggest these as candidate regions under selection. These regions include SNPs in the well-characterized LCT region, as well as at loci including FOXP2, OCA2 and LRP1B.
Within the guts of this paper they make an important observation: constructing a set of populations and then generating pairwise statistics of differentiation across those populations has an element of arbitrariness. Rather than going in that direction the authors here are evaluating variation of genes as a function of continuous space, rather than binning them into discrete populations. In this way they can use patterns of genes to back infer the likely geographic origin of an individual, and more intriguingly pinpoint genetic loci which exhibit sharp gradients across space, and so may be targets of natural selection. The adaptive story for LCT is straightforward. But what of OCA2, which is mostly well known as a pigmentation locus which has been implicated in blue vs. brown eye variation in Europeans? As I like to say, interesting times….
And of course, they have released the software.