Prehistory and Plug & Play Genetics


June 2, 2018

AS NOTED EARLIER THIS WEEK at SCIENCE DIALOGUES, the popular science monthly Scientific American has now published a lengthy and decidedly critical commentary on current practice in the new field of paleogenetics .

At present it looks like the hype promoting paleogenetics research far exceeds the actual performance.

But who knows what the future will bring once human geneticists realize that there are no simple ways to connect the dots between human genes and the realities of human history.

 

 

Dynamic Network Analysis (DYNA) — new series

“. . . network ideas appear, are then dissipated, and re-emerge again. They have never defined the core concerns of any discipline or research specialism to the extent that they form part of its canon and are seen as fundamental to its ongoing concerns” (Knox et al. 2006: 114).

 


John Terrell

DURING THE SECOND HALF of 2018 SCIENCE DIALOGUES will be featuring a series of reports on the steps that have been taken at the Field Museum in Chicago since the early 1970s to promote dynamic network analysis (DYNA) in the social and historical sciences. 

The goal of these reports is to prepare the way for writing a book about how networks analysis is currently revolutionizing scientific (and hopefully human) thought about the world we live in and our place in it.

  1. Human nature

  2. Relativity

  3. Connecting the dots

  4. Exploring the 5th dimension

  5. What is a relationship?

  6. What is a network?

  7. Why do network analysis?

  8. Adaptive networks

  9. Asking questions

  10. What?

  11. Where? 

  12. Who?

  13. Why?

  14. When?

  15. How?

  16. what’s next?

Cover art (a fantasy) for the proposed book on networks thinking.

Reference cited

Knox, Hannah, Mike Savage, and Penny Harvey (2006). Social networks and the study of relations: Networks as method, metaphor and form. Economy and Society 35: 113–140.

History and Human Genetics: challenges of collaboration

 Writing history is a lot harder than some may realize

John Terrell

UK’s LEADING ARCHAEOLOGY MAGAZINE Current Archaeology has taken a  sympathetic look at the often strained relationship between archaeology and human molecular genetics today.

It should come as no surprise to anyone who knows firsthand the challenges of writing history that this brief assessment highlights the concerns some archaeologists have voiced that “aDNA is unable to account for the complexity and subtleties of human behavior.”

This brief published commentary ends on a hopeful note. In the years ahead, collaborations between archaeologists and experts working in other sciences will “becoming stronger and more balanced.”

 “So what? Why should I care?”

This same week in May 2018, Scientific American published my own assessment of  the strengths and weaknesses of paleogenetics today focusing on what is being written about Pacific prehistory by David Reich and others. Reich is the author of an enthusiastic overview of aDNA research around the world published this year by Pantheon.

John Terrell on Teop Island, North Solomons, 1969

Here is what I say at the end of this analysis (somewhat shortened in length):

There are two thoughts I want to leave you with.

My first thought is about scientific responsibility. Pacific Islanders have been dealing with foreigners telling them what to do and how to do it ever since Europeans began sailing around the Pacific in the 16th century. Are we now committed to telling them also what was their history? Why would we want to do this? The days of European colonialism are over, aren’t they? Or are they?

The second thought is this one. Call them “populations” or call them “races,” it makes no difference. As modern molecular genetics has now shown us in remarkable detail, we are all 99.9 percent the same. It may be conventional wisdom to think we humans come in different kinds called races, populations and the like. A statistic like this one, however, ought to be enough to convince anyone willing to listen that we don’t come in kinds whatever you want to call them.

Hence the apparent willingness of more than a few geneticists today to use words like populations, migrations and admixture when they are writing about ancient DNA and the past does more than just misinform the rest of us. As reviews of Reich’s book, both pro and con, have sometimes scoldingly observed, when scientists talk this way, they can sound like they are doing racial profiling. Apparently, it can be hard for some folks to see that what my grandfather called hogwash may not just be something unbelievable. Hogwash can also be words and stories that are socially, politically and, yes, historically misleading. Maybe even dangerous.

Challenging our assumptions about the antiquity of trade and social networks in Middle Stone Age Africa

Nature human behavior has just published a research highlight written John Carson about work at the Sibilo School Road Site in Kenya done by Nick Blegen, Harvard University, that has recovered large quantities of obsidian along with Middle Stone Age (MSA) tools . The finds are thought to date back at least 200 kyr.

As Carson summarizes: “Geochemical analyses demonstrated that the majority of obsidian pieces had their provenance at a source site >160 km away, indicating long-distance transport of raw materials during the MSA.” Previously, East African sites evidencing long-distance resource transport have all be less than <50 kyr old.

Evidently known MSA sites of this age are rare in East Africa. If more sites can be found and excavated, the “big story” usually told about the evolution of human social behavior may need updating: far-reaching resource networks and/or intergroup trade in raw materials could have developed earlier than generally believed in the history of our species. If so, then in Carson’s words: “we may gain greater insight into the timeline of social evolution that eventually led to our modern group behaviours.”

Blegen’s report was just published (unfortunately behind a paywall) in the Journal of Human Evolution. Here is the abstract you will find available there for free:

Abstract

This study presents the earliest evidence of long-distance obsidian transport at the ∼200 ka Sibilo School Road Site (SSRS), an early Middle Stone Age site in the Kapthurin Formation, Kenya. The later Middle Pleistocene of East Africa (130–400 ka) spans significant and interrelated behavioral and biological changes in human evolution including the first appearance of Homo sapiens. Despite the importance of the later Middle Pleistocene, there are relatively few archaeological sites in well-dated contexts (n < 10) that document hominin behavior from this time period. In particular, geochemically informed evidence of long-distance obsidian transport, important for investigating expansion of intergroup interactions in hominin evolution, is rare from the Middle Pleistocene record of Africa. The SSRS offers a unique contribution to this small but growing dataset. Tephrostratigraphic analysis of tuffs encasing the SSRS provides a minimum age of ∼200 ka for the site. Levallois points and methods of core preparation demonstrate characteristic Middle Stone Age lithic technologies present at the SSRS. A significant portion (43%) of the lithic assemblage is obsidian. The SSRS obsidian comes from three different sources located at distances of 25 km, 140 km and 166 km from the site. The majority of obsidian derives from the farthest source, 166 km to the south of the site. The SSRS thus provides important new evidence that long-distance raw material transport, and the expansion of hominin intergroup interactions that this entails, was a significant feature of hominin behavior ∼200 ka, the time of the first appearance of H. sapiens, and ∼150,000 years before similar behaviors were previously documented in the region.

© 2016 Elsevier Ltd. All rights reserved

The moral of the story of how we came to be – 1

Tom Clark


Please note: this commentary, recovered on 28-Jan-2017, was originally published in Science Dialogues on 17-May-2015.


From our one short lifetime, we look back and wonder “How did we get here?” This matters because we also want to know “What are we doing here?”  Our imaginations squint to make out answers.

Looking back to the way we got here, we try to imagine the magnitude of time and the qualities of changes that made up the past. Our views are limited not only by the shortness of our lifetimes, but also by the stories we tell about the view backwards through the keyhole of our lives.

We have portrayed the past in our own image, assigning nature’s varied powers to a single human-like God who put us here for a reason and authorized our dominion over life. Exaggerating how much purpose has been a part of our story, how much the past anticipated our own local purposes, these stories mislead us because they are too much about us. We are not all that.

Making sense of our lives by placing them within a scientific story of how we got here, we struggle to keep in mind that every moment of life’s deep past was intricately inhabited by lives-in-progress. It is so hard to imagine all those moments in all those lives, we settle for making them redundant, folding them into formulas of lawfulness and randomness, necessity and chance.

Nature took its course, we have imagined, indifferent to our ancestors’ purposeful efforts. Exaggerating the absence of purpose in our past, we threw out the baby of responsibility with the bathwater of a punishing God. We naturalized our dominion by different means but with similar ends. Shrinking our lives into molecular algorithms, these stories have done a different kind of disservice. We are more than this.

To get a clear view of how we got here and what we are doing here, we must hold in our mind’s eye a deep past of richly engaged lives (Shryock and Smail 2011). This is no easy matter. We will have to tolerate a lot of tickling of our imaginations.

Origin myths and human nature

When we talk about the role of our ancestors’ activities, which is to say animal behavior, in how we came to be, scientific theory becomes human nature mythology. Myth not as falsehood, but as “vital ingredient of human civilization … not an idle tale, but a hard-worked active force” (Malinowski 1948: 79).

Origin myths shape the kinds of people we become, by expressing a shared sense of who we are, in the telling of how we came to be. Telling of the past, they are aimed at the future.

By tradition the factual details of myths have been cooked up, knowingly, to get the story “right” in a moral sense. Intended to be forces of history more than sources of history, origin myths function as moral rudders, not archival records.

This is why literal readings of the Bible’s Genesis story, among believers and skeptics alike, miss the point. The story’s intent being allegorical, debating its historical accuracy does more to freeze moral rudders than to move them. We sway rudders better by contesting the messages within the allegory, for example: “… thy husband … shall rule over thee” (King James Bible).

Scientists aim to get the facts right, but can avoid neither social influences on their work nor social influences of their work. “Culture seeps into science unbidden” (de Waal 2001: 46). Intended or not, scientific origin theories also carry out cultural functions as origin myths, goading and curbing our moral imaginations.

So when Richard Leakey (2010) tells us that natural laws and chance are all we need to explain life’s evolution, this is an article of faith – more curb than goad – maintained in the secular culture within and around science, not a scientific finding of fact.

Whether allegory or science, we see ourselves in origin stories, the tellings of which are moral acts of historic significance (Bock 1994).

We tell two broad kinds of origin myths, presenting open or closed images of humanity. Open stories tell us that we are by nature free and therefore obliged to commit ourselves to courses of action for which we are responsible. According to these stories, history was made in part by the wits, determination and cooperation of our ancestors. The differences we make are partly of our own doing. It is possible to fail. We can also rise to challenges. Open stories remind us that we play a part on life’s stage.

Closed origin myths tell us we are born with good or bad moral qualities in our souls, hearts, bones, or more recently, genes. The past unfolded as a sequence of events caused by prior events or higher powers. When we make a difference, it is not our doing. Inevitability makes moral failings more likely but less painful, even less noticeable. Lulling our moral imaginations, these stories place us in balcony seats watching life play out (except those telling the story).

Evolution and ethics

Open versions of scientific origin myths are at home with Gould’s maxim “Moral inquiry is our struggle, not nature’s display” (1990: 12), or Simpson’s view that “ethics cannot be independent of evolution, but neither can it be derived from evolution” (1969: 142).

Closed versions channel Ruse’s view that belief in moral principles is “a collective illusion foisted upon us by our genes” (1986: 253). By assuming that ethics can be derived from evolutionary theory, these stories degrade what they are attempting to understand.

We can expect ethics to inform our understanding of life because ethics are part of human life.

For biology to inform our ethics without degrading it, we need a view of life that is also informed by ethics. We can expect ethics to inform our understanding of life because ethics are part of human life with beginnings in mammalian life. The moral imaginations of Abraham Lincoln, Mahatma Gandhi, Martin Luther King and their contemporaries were imaginary in the sense that they were of the imagination, fantastic in the sense of extraordinary goodness, and neither in the sense of being not real (Bromwich 2014).

And what does morality tell us about how we got here? Morality indicates a deeper history of its building blocks than is usually told. A short sketch of this history goes something like this (from Rosslenbroich 2014).

Life is inherently semi-autonomous

For 3.6 billion years, life has been an emergent and open process harnessing the reliabilities of physics and chemistry, in constant tension between its self-directed inside and dependence on what is outside. Living its freedom by degrees, life is semi-autonomous.

As a fundamental characteristic of life, autonomy is a mainspring of evolution, not a residue. Biology does not merely constrain autonomy. Biology – life – sustains autonomy, as it has from its beginning.

Autonomy has evolved

Capacities for self-direction and relative independence from the immediate surroundings have increased in some lines of descent. For two billion years, cells with special parts to make and store energy, keep the inside organized, and control give-and-take with the outside (eukaryotes) have been more autonomous than cells without these parts (prokaryotes).

It took eukaryotic cells a billion years to come together into multicellular organisms, each cell losing a measure of individual autonomy to gain greater overall autonomy. Exploiting the advantages of size and specialization, multicellular life (animals more so than plants) moved vital functions like breathing, digesting and eliminating waste from their surface to their inside, thus gaining further control of give-and-take with the outside.

The story of autonomy’s evolution will continue in Part 2 of this article.

References

Bock, K. 1994. Human Nature Mythology. Chicago: University of Illinois Press.

Bromwich, D. 2014. Moral Imagination. Princeton, NJ: Princeton University Press.

De Waal, F. 2001. Without walls. New Scientist 172: 46-49.

Gould, S. J. 1990. Darwin and Paley meet the invisible hand. Natural History 99 (11): 8-12.

King James Bible Online. http://www.kingjamesbibleonline.org/Genesis-Chapter-3/

Leakey, R. E. 2010. Why Our Origins Matter. Origins ’10 public lecture series, Florida State University, April 1.

Malinowski, B. 1948. Magic, Science and Religion. Glencoe, Il: The Free Press.

Rosslenbroich, B. 2014. On the Origin of Autonomy. Cham: Springer.

Ruse, M. 1986. Taking Darwin Seriously. Oxford: Blackwell.

Shryock, A. and D. L. Smail. 2011. Deep History. Berkeley: University of California Press.

Simpson, G. G. 1969. Biology and Man. New York: Harcourt, Brace and World.


Tom Clark is a psychologist who has been interested in the role of behavior in evolution since his graduate training at the University of South Florida.


© 2015, Thomas L. Clark. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. The statements and opinions expressed in this article are those of the author(s) and do not constitute official statements or positions of the Editors and others associated with SCIENCE DIALOGUES.

Zambia paleo dig yields new insights on Permian-Triassic environments

Mark Alvey


Please note: this news story, recovered on 28-Jan-2017, was originally published in Science Dialogues on 27-August-2014.


Ken Angielczyk in the Luangwa Basin of Zambia holding two specimens of the dicynodont Diictodon. Photo by Roger Smith.

Associate Curator Ken Angielczyk of The Field Museum was part of an international team of collaborators that conducted paleontological fieldwork in Zambia between June 22 and July 31. Ken and his collaborators focused on Middle Permian (~265 Mya) to Middle Triassic (~240 Mya) rocks in two areas of the country, the Zambezi Basin in southern Zambia and the Luangwa Basin in northeastern Zambia. The team had done preliminary work in the Zambezi Basin in 2011 and 2012, but only spent a total of about 5 days working there. This time, they spent about two weeks there and their discoveries include multiple species of archaic amphibians and dinocephalians and dicynodonts (both ancient mammal relatives) from the Middle Permian, extremely well preserved fossil wood, and evidence that two temporally-distinct faunas are preserved in the Permian rocks in the Zambezi Basin. They also collected a large amount of geological data that will help complete the picture of the environments in which the plants and animals were living.

Ken’s colleagues Sebastien Steyer and Charles Beightol excavate a dinocephalian skeleton preserved in Permian rocks in the Zambezi Basin of Zambia. Photo: Cristian Sidor.

The team had conducted more extensive fieldwork in the Luangwa Basin in 2009 and 2011, and this year their work focused on rounding out their previous collections and collecting more geological data to understand  paleoenvironments. Among their discoveries is evidence of strong associations of particular dicynodonts with specific environments in the Late Permian rocks of the Luangwa Basin, and strong evidence of increased aridity and changes in the nature of river systems in the area moving from the Late Permian to the Middle Triassic. Ken and his collaborators will use these data to investigate the role environmental changes played in shaping the end-Permian mass extinction (the largest extinction in Earth history) and the recovery following the event.

Ulemosaurus svijagensis – primitive tapinocephalian from Middle Permian of Tatarstan. Illustration by Dmitry Bogdanov. Source: https://en.wikipedia.org/wiki/Ulemosaurus#/media/File:Ulemosaurus22DB.jpg.

And one important result of fieldwork like that: scientific publications.  Ken and colleagues have a paper in the July issue of Journal of Vertebrate Paleontology describing fossils of tapinocephalids from Southern Zambia.  Tapinocephalids are hippo-sized, herbivorous mammal relatives that lived about 265 million years ago; the fossils were discovered by Ken and his collaborators during short exploratory trips to the Zambezi Basin in southern Zambia in 2011 and 2012. They are the oldest known tetrapod remains from Zambia, and demonstrated the potential of the area for further paleontological exploration (as in previous item). This is also the second time that Ken and his teammates have discovered tapinocephalids in an area from which they were previously unknown (the first time was in 2008 in Tanzania).

© 2014 Mark Alvey. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. The statements and opinions expressed are those of the author(s) and do not constitute official statements or positions of the Editors and others associated with SCIENCE DIALOGUES

Do men and women think differently?

Marc Kissel


Please note: this commentary, recovered on 28-Jan-2017, was originally published in Science Dialogues on 3-August-2014.


Years ago I mentioned to a group of female friends that I didn’t think men and women were really that different (well, besides the obvious ones). This caused quite the kerfuffle and led to the conclusion that I was an idiot. Yet, while it seems self-evident that men & women think differently this doesn’t mean that it is true . After all, it wasn’t too long ago were it was “obvious” that race was biology, that the sun circled the earth, and that jorts were a good idea.

A paper published last January caused quite the hubbub when it claimed to find significant differences between male and female brains (Ingalhalikar et al. 2014). Not tested in the paper, however, was whether those differences were cultural (in fact, the differences between sexes increased as the age of the children studied increased, which may suggest that something other than biology was at play).  A new study by Daniela Weber and colleagues (2014) investigates the role cultural factors may play in these apparent differences. They do so by examining cognitive task results from surveys of “nonindustrialized” men & women over 50 living in Europe, merging 13 countries into three regional groups and then comparing within and between these populations. The main results are shown in Figure 1.

Figure 1. Source: Webster et al. 2014.

For episodic memory (how well someone recalls a list of previously read words), women in Northern Europe have a higher average score than men, but the situation is more complex in other regions. Results differed in numeracy & category fluency categories based upon region as well. If you thought male/female difference were hard-wired, this shouldn’t be the case.

What causes these geographic differences? The Nick Wade’s of the world would probably suggest genetic differences are at the heart of the matter, but that does not seem to be the case. Instead access to education, along with other social factors, may be at the root of much of this.

Figure 2. Source: Webster et al. 2014.

This isn’t the clearest of figures. On the Y-axis is the average level of education for women minus that of men. When the number is negative, men on average spend a longer time in school than women do. On the X-Axis, is women’s cognitive performance minus men’s cognitive performance. I added colored lines at ‘0’ for each axis. Points to the right of the red line represent cohorts where women outperform men, while points above the blue line are when women have higher levels of education than men. As can be seen, in almost all cases men have reached higher education levels. It is interesting that, for episodic memory, as the mean years of differences in education years decreases, the difference between the sexes also decreases. Or as they put it: “These findings suggest that if women and men had equal levels of education, we should expect a female advantage in episodic memory, a male advantage in numeracy, and no gender differences in category fluency” (Weber et al. 2014:3).

In other words, reducing differences in access to education should lessen the differences in test scores.  Trying to discover sex-based differences without acknowledging the role cultural plays is always going to cause anthropologists to be wary so it is nice to see this acknowledged. As noted in the paper, there are many confounding variables that cannot be tested here and it is difficult to rule out  decline in mental acumen due to age-related cognitive decline. Further, I wonder about the geographic populations they define. What patterns would emerge if you didn’t group the 13 countries together in the same way as is done in this paper? Also interesting, though not really discussed, is that Northern Europeans (here represented by Denmark & Sweden) did better on all the cognitive assessments.

But it is always nice to see approaches that note that differences may be cultural rather than biological. Oh, and don’t get me  started on the blue = boys and girls =  pink nonsense.

References

Ingalhalikar, Madhura, et al. “Sex differences in the structural connectome of the human brain.” Proceedings of the National Academy of Sciences 111.2 (2014): 823-828.

Weber, Daniela, et al. “The changing face of cognitive gender differences in Europe.” Proceedings of the National Academy of Sciences (2014): 201319538.

Marc Kissel (Ph.D, University of Wisconsin-Madison) is a native New Yorker transplanted into the wilds of the Midwest. His dissertation examined genetic models that try to explain why humans are so inbred compared to the living apes and asks if these models conform to anthropological reality (spoiler alert: they don’t!). He is interested in human evolution and likes to apply mathematical models, genetic data, and anthropology to questions about our evolutionary history (especially Neandertals). Currently he is a postdoc at Notre Dame studying the evolution of wisdom. You can find him him on Twitter @MarcKissel
© 2014 Marc Kissel. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. The statements and opinions expressed are those of the author(s) and do not constitute official statements or positions of the Editors and others associated with SCIENCE DIALOGUES.

Reconfiguring biological diversity 2. Coming to grips with diversity

John Edward Terrell


This is part 2 of a two part article

Coming to grips with diversity

Perhaps the greatest stumbling block to deciphering how biological diversity is patterned, or structured, in space and time within any given species is that most existing ways of modeling such diversity presuppose that genes are nested in some fashion within demonstrable and persistent primary units that can be labeled as populations, subpopulations, demes, communities, stocks, races, and like. Yet is this how biological reproduction works? Aren’t genes perfectly capable of “escaping,” so to speak, from such allegedly defining and confining “boxes” through the very acts of reproduction, reassortment, growth, and development?

It could be argued that there is irony in the fact that molecular genetics now has made it possible for scientists to map diversity at the genetic level. Yet many are still given to thinking about diversity as if they were compelled by the old limitations of their laboratory techniques to lump this new fine-grained evidence into inclusive nested sets (e.g., Pritchard et al. 2000; Greenbaum et al. 2016; Skoglund et al. 2016).

Perhaps it is not surprising, therefore, that some have concluded that “the observed pattern of global gene identity variation was produced by a combination of serial population fissions, bottlenecks and long-range migrations associated with the peopling of major geographic regions, and subsequent gene flow between local populations” (Hunley et al. 2009).

All three of these identified processes are plausible reasons for biological diversity in time and space. But aren’t all three of these population-level explanations ignoring individual agency and decision-making? Not to mention love, lust, and human compassion?

Moving beyond population modeling

Current population-level modeling based on molecular genetics is arguably an advance over older metapopulation models framing diversity as an ever-changing flux within species among discrete subpopulations inhabiting separate habitat patches linked by migration and extinction (Fig. 2). Certainly few today would accept that diversity within any species can be adequately explained solely or even largely as the product of fluctuating colonization and extinction events.

Figure 2. A simple metapopulation model at two time periods (A and B) attributing spatial diversity to a shifting dynamic of colonization and extinction events.

Similarly, the concept of the fitness landscape (also known as as an adaptive landscape; see Fig. 3) introduced by the geneticist Sewell Wright in 1932 is another long-debated way of modeling the dynamic interplay—or balance—of a number of plausible determinants of genetic variation in space and time. As Wright explained in 1932:

The most general conclusion is that evolution depends on a certain balance among its factors. There must be gene mutation, but an excessive rate gives an array of freaks, not evolution; there must be selection, but too severe a process destroys the field of variability, and thus the basis for further advance; prevalence of local inbreeding within a species has extremely important evolutionary consequences, but too close inbreeding leads merely to extinction. A certain amount of crossbreeding is favorable but not too much. In this dependence on balance the species is like a living organism. At all levels of organization life depends on the maintenance of a certain balance among its factors. (Wright 1932)

Figure 3. “Field of gene combinations occupied by a population within the general field
of possible combinations. Type of history under specified conditions indicated by relation
to initial field (heavy broken contour) and arrow.” Source: Wright 1932, fig. 4.

A “balance of factors” sounds right and reasonable, but are the ones he mentions the only major factors that must be taken into account? Surely adaptation is not the only driving force of evolution?

Agency and social networks

Consider the observation that human beings are notably variable in stature, weight, and other characteristics of their appearance. Clearly the gene mutations supporting such phenotypic variation have not resulted in what Wright would describe as “an array of freaks.” Evidently such diversity is not selected against—to use Wright’s way of framing the discussion. Why? Because much of the burden of human adaptation does not need to be genetically endowed. Instead, as most social scientists would insist, much of what we do supporting our survival and reproduction is accomplished using socially learned skills rather than by genetically inherited biological means.

Recently Greenbaum and his colleagues observed that the research strategies and tools of modern network analysis are increasingly being used to explore genetics questions in genomics, landscape genetics, migration-selection dynamics, and the study of the genetic structure of species more generally speaking (Greenbaum et al. 2016).

Adopting a networks approach to genetics makes it possible to come to grips not only with the ways in which racism—to return to Roseman’s point raised earlier—has shaped human variation in the past few hundred years, but also how our species’ mobility, adaptive skills, technologies, and social behaviors have been configuring human variation throughout the history of our species.

Figures 4 and 5 illustrate the potential value of using of network analysis in the study of genetic diversity. The first figure is a network mapping of localities reported in a genome scan published in 2008. While the patterning is complex, there is an obvious geographic signal in the genetic linkages shown. Figure 5 resolves the relationships among a smaller subset of the localities that had been sampled, specifically those in the Bismarck Archipelago-North Solomons region of the southwest Pacific.

Figure 4. Spring-embedding network mapping of the localities sampled in a genome scan of autosomal markers (687 microsatellites and 203 insertions/deletions) on 952 individuals from 41 Pacific populations). Mapping derived from the mean STRUCTURE assignment probabilities when K = 10 reported by Friedlaender at al. (2008) color-coded by geographic location. Blue-white = Asia; blue = Taiwan; black = Europe; red = Polynesia; pink = Micronesia; yellow = New Britain; purple = New Guinea; dark green = North Solomons; green = New Ireland; light green = New Hanover; pale green = Mussau. Source: adapted from Terrell 2010b, fig. 3.

 

Figure 5. Nearest-neighbor structuring of interaction among the localities sampled in the Bismarck Archipelago and North Solomons color-coded to show genetic clustering (blue nodes represent locations not represented in the genetic scan). Source: Terrell 2010b, fig. 11.Both network mappings suggest that geography has influenced the structuring of genetic similarities among people living in the sampled localities shown. Yet it also is apparent that the linkages shown may often be closer than geographic distance alone would lead us to expect. Judging by figure 5, the effect of isolation by distance is evidently constrained by social networks (as projected in this figure using nearest-neighbor linkages). Hence while geographic distance may be contributing to the patterning of genetic diversity among people in this part of the world, geography is by no means the whole story.
Conclusions

The network analysis briefly introduced in figures 4 and 5 had two principal aims, one phylogenetic, the other tokogenetic (Terrell 2010b). Do people living today in the Pacific segregate genetically along lines concordant with the reputedly separate (i.e., cladistic) histories of languages spoken there, principally the divide drawn by linguists and others between speakers of Austronesian and non-Austronesian (Papuan) languages (Terrell 2006)? To what extent does the genetic similarity among people living in different residential communities correlate with the nearest-neighbor propinquity of these sampled places?

Neither of these aims presuppose that the research goal is to define genetically discrete human populations (or subpopulations, demes, groups, communities, races, and the like) either a priori or by using, say, individual-based clustering (IBC) methods (e.g., Ball et al. 2010).

These two aims have more in common with those of the emerging field of landscape genetics (Dyer and Nason 2004; Garroway et al. 2008) than with most previous research in population genetics. However, both of these aims focus more directly on the genetic consequences of the behavior of organisms in space and time—in this case, humans—than on the geography, ecology, and environmental history of the locales where the people in question reside.

Both can also be seen as stepping back from Roseman’s observations about the impact of racial politics and social practices on the human genome in the past few centuries to underscore a more general issue in evolutionary biology: How much do the mobility and social behavior of individuals within any given animal species structure the genetic variation of that species?

As Dyer and Nason (2004) have remarked: “The evolution of population genetic structure is a dynamic process influenced by both historical and recurrent evolutionary processes.” Using network theory and visualization techniques to map the genetic structure of a species in space and time is still in its infancy. Reconfiguring how science grapples with the inherent complexity of evolution as an ever unfolding process using network approaches has the promise of making it easier to explore how comparable or dissimilar species are in their strategies for survival and reproduction (Fortuna et al. 2009).

Looking long and hard at what other species do to survive and reproduce may make it easier for us to see just how toxic our own social strategies—and the assumptions supporting them—can be.

Acknowledgements

I thank Neal Matherne and Tom Clark for their comments on a draft of this commentary.

References

Ball, Mark C., Laura Finnegan, Micheline Manseau, and Paul Wilson. 2010. Integrating multiple analytical approaches to spatially delineate and characterize genetic population structure: An application to boreal caribou (Rangifer tarandus caribou) in central Canada. Conservation Genetics 11, 6: 2131-2143.

Dyer, Rodney J., and John D. Nason. 2004. Population graphs: The graph theoretic shape of genetic structure. Molecular ecology 13, 7: 1713-1727.

Fortuna, Miguel A., Rafael G. Albaladejo, Laura Fernández, Abelardo Aparicio, and Jordi Bascompte. 2009. Networks of spatial genetic variation across species. Proceedings of the National Academy of Sciences 106, 45: 19044-19049.

Friedlaender, Jonathan S., Françoise R. Friedlaender, Jason A. Hodgson, Matthew Stoltz, George Koki, Gisele Horvat, Sergey Zhadanov, Theodore G. Schurr, and D. Andrew Merriwether. 2007. Melanesian mtDNA complexityPLoS One 2, 2: e248.

Friedlaender, Jonathan S., Françoise R. Friedlaender, Floyd A. Reed, Kenneth K. Kidd, Judith R. Kidd, Geoffrey K. Chambers, Rodney A. Lea et al. 2008. The genetic structure of Pacific IslandersPLoS Genet 4, 1: e19.

Garroway, Colin J., Jeff Bowman, Denis Carr, and Paul J. Wilson. 2008. Applications of graph theory to landscape genetics. Evolutionary Applications 1, 4: 620-630.

Greenbaum, Gili, Alan R. Templeton, and Shirli Bar-David. 2016. Inference and analysis of population structure using genetic data and network theory. Genetics 202.4: 1299-1312.

Hellenthal, Garrett, George BJ Busby, Gavin Band, James F. Wilson, Cristian Capelli, Daniel Falush, and Simon Myers. 2014. A genetic atlas of human admixture history.” Science 343, 6172: 747-751.

Hunley, Keith, Michael Dunn, Eva Lindström, Ger Reesink, Angela Terrill, Meghan E. Healy, George Koki, Françoise R. Friedlaender, and Jonathan S. Friedlaender. 2008. Genetic and linguistic coevolution in Northern Island MelanesiaPLoS Genet 4, no. 10 (2008): e1000239.

Hunley, Keith L., Meghan E. Healy, and Jeffrey C. Long. 2009. The global pattern of gene identity variation reveals a history of long‐range migrations, bottlenecks, and local mate exchange: Implications for biological race. American Journal of Physical Anthropology 139, 1: 35-46.

Kelly, Kevin M.,  2002. Population. In Hart, J. P. & Terrell, J. E. (eds.) Darwin and Archaeology: A handbook of key concepts, pp 243–256. Westport, Ct: Bergin & Garvey.

Moore, John H. 1994. Putting anthropology back together again: The ethnogenetic critique of cladistic theory. American Anthropologist (1994): 925-948.

Posada, David, and Keith A. Crandall. 2001. Intraspecific gene genealogies: Trees grafting into networks. Trends in Ecology & Evolution 16, 1: 37-45.

Pritchard, Jonathan K., Matthew Stephens, and Peter Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics 155, 2: 945-959.

Rieppel, Olivier. 2009. Hennig’s enkaptic system. Cladistics 25, 3: 311-317.

Roseman, Chartes C. 2014. Troublesome Reflection: Racism as the Blind Spot in the Scientific Critique of Race” Human biology 86, 3: 233-240.

Roseman, Charles C. 2014. “Random genetic drift, natural selection, and noise in human cranial evolution. Human Biology 86, 3: 233-240.

Skoglund, Pontus, Cosimo Posth, Kendra Sirak, Matthew Spriggs, Frederique Valentin, Stuart Bedford, Geoffrey R. Clark et al. 2016. Genomic insights into the peopling of the Southwest Pacific. Nature 538: 510-513.

Terrell, John Edward. 2006. Human biogeography: Evidence of our place in nature. Journal of Biogeography 33, 12: 2088-2098.

Terrell, John Edward. 2010a. Language and material culture on the Sepik coast of Papua New Guinea: Using social network analysis to simulate, graph, identify, and analyze social and cultural boundaries between communities. Journal of Island & Coastal Archaeology 5, 1: 3-32.

Terrell, John Edward. 2010b. Social network analysis of the genetic structure of Pacific islanders. Annals of human genetics 74, 3: 211-232.

Terrell, John Edward. 2015. A Talent for Friendship: Rediscovery of a Remarkable Trait. Oxford University Press.

Terrell, John Edward, and Pamela J. Stewart. 1996. The paradox of human population genetics at the end of the twentieth century. Reviews in Anthropology 25, 1: 13-33.

Wade, Nicholas. 2014. A Troublesome Inheritance: Genes, Race and Human History. Penguin.

Wilson, David Sloan, and Edward O. Wilson. 2008. Evolution for the Good of the Group”: The process known as group selection was once accepted unthinkingly, then was widely discredited; it’s time for a more discriminating assessment. American Scientist 96, 5: 380-389.

Wright, Sewall. 1932. The roles of mutation, inbreeding, crossbreeding, and selection in evolution. Proceedings of the Sixth International Congress of Genetics , Vol. 1: 356-366.

© 2017 John Edward Terrell. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. The statements and opinions expressed are those of the author(s) and do not constitute official statements or positions of the Editors and others associated with SCIENCE DIALOGUES.

In the works: Mating, variation, and speciation: An interdisciplinary conversation

Source: https://commons.wikimedia.org/wiki/File:Limenitis_archippus_mating_2.jpg

While using network theory and visualization techniques to map the genetic structure of species in space and time is in its infancy, reconfiguring how science grapples with the inherent complexity of evolution as an ever unfolding process using network approaches has the promise of making it easier to explore how comparable or dissimilar species are in their strategies for survival and reproduction. Looking long and hard at what other species do to survive and reproduce may also make it easier for all of us to see just how toxic our own social strategies—and the assumptions supporting them—can be.

Reconfiguring biological diversity 1. Toxic and obsolete assumptions

John Edward Terrell


This is part 1 of a two part article

IN AN INSIGHTFUL REVIEW of Nicholas Wade’s recent book A Troublesome Inheritance: Genes, Race and Human History (Wade 2014), the anthropological geneticist Charles C. Roseman concluded that current scientific arguments against biological racism are weak and scattered. These failings—my word, not Roseman’s—are far more than just scientifically troubling. “To recuperate a useful scientific critique of race,” he argues, “we need to come to grips with ways in which the political processes of racism have shaped human organisms over the last few hundred years” (Roseman 2014).

As Roseman notes, nobody seriously contests that human variation “is structured in geographic space, through time, and across many social divisions.” What is still up for grabs is how to explain this observable diversity. And as Roseman emphasizes, how we explain human variation cannot ignore the divisive and often destructive power of racism as a potent driver of human evolution. “Without incorporating the effects of racism into models of human variation today, we will not be able to have a cohesive theory of genes and race, and the scientific critique of race will continue to have no teeth.”

While Roseman’s observations focus on human biological diversity, the weaknesses and uncertainties he has highlighted about our explanations for variation within our species apply also to modern science’s grasp of biological diversity more broadly speaking. From this more inclusive point of view, racism is just a particularly invidious human form of social behavior capable of patterning our genetic diversity in time and space. If so, what about other species? How does the patterning of their mobility and social behavior shape their genetic diversity?

“Populations,” “admixture,” and conventional wisdom

Although the human brain can be coaxed into paying close attention to detail and nuance,  as a thinking machine it generally favors expediency and the utility of knowledge over precision and accuracy.  It is not altogether surprising, therefore, that even scientists often still take it for granted that biological species are naturally subdivided into separate “populations” or “subspecies” that  may occasionally—say under changing demographic or environmental conditions—meet and mix, and thereby produce more or less isolated “admixed” new hybrids (e.g., Moore 1994; Hellenthal et al. 2014). The question being overlooked or at any rate downplayed is how real and persistent are these assumed “populations” (Terrell and Stewart 1996; Kelly 2002).

This question may sound academic, but it is not trivial, as Charles Roseman has underscored. When it comes to human beings, the favored word in scholarly circles may be the word population or perhaps deme, group, or community, but for the chap on the street, the more likely choice wouldn’t be one of these formal terms, but rather the more down-to-earth word race. (I still vividly remember being scolded by a famous biological anthropologist decades ago when I was an undergraduate for using this particular “r” word. “We don’t use that word anymore,” he told me. “We use the term stock  instead.”)

What’s at stake here

It has been a foregone assumption in most genetics research for years that different species are by definition and by their biology isolated reproductively from one another, i.e., individuals in different species cannot mate and give birth to viable offspring capable of sustaining life for longer than a single generation. However, even the most committed cladist accepts that biological relationships below the level of the species are tokogenetic, not phylogenetic (Posada and Crandall 2001; Rieppel 2009).

Figure 1. “Tokogeny versus phylogeny. (a) Processes occurring among sexual species (phylogenetic processes) are hierarchical. That is, an ancestral species gives rise to two descendant species. (b) Processes occurring within sexual species (tokogenetic processes) are nonhierarchical. That is, two parentals combine their genes to give rise to the offspring. (c) The split of two species defines a phylogenetic relationship among species (thick lines) but, at the same time, relationships among individuals within the ancestral species (species 1) and within the descendant species (species 2 and 3) are tokogenetic (arrows).” Source: Posada and Crandall 2001, fig. 1.

Here, therefore, is the conundrum. Call them what you want, populations within any given species are not inherently isolated reproductively either by definition and by their biology. Hence to treat populations as natural units, they must first be defined and demonstrated to be isolated and discernible as such in some other way, or ways. Can this be done?

Here is one favored way when the species in question is ourselves. Many people believe that the language you speak is a reliable sign or marker of your true ethnicity and even your race. Is this right?

Hardly. As both fable and risqué jokes alike would have it, any sailor arriving in a strange port of call is likely to discover soon enough that you don’t really need to speak the local language to enjoy a good time while ashore as long as you have a few coins in your pocket. Yet scholars have long written about people living in what some see as the “underdeveloped” regions of the world as being subdivided into recognizable ethnolinguistic groups, language communities, and the like despite the fact that such euphemisms for the old-fashioned word race pigeonhole rather than map the realities of their lives (Terrell 2010a).

But if neither biology nor language inherently—i.e., “naturally”—isolates and thereby subdivides human beings as a species into different populations, subpopulations, demes, communities, stocks, or races, is there anything that does? And what about other species on earth?

Competition and tribalism, or isolation-by-distance?

As Roseman has remarked: “All analyses of human variation make strong assumptions about the mode, tempo, and pattern whenever they interpret statistical results to make evolutionary conclusions” (Roseman 2016). Favored explanations for or against the assumption that our species can be subdivided into enduring natural populations largely fall into one or the other of two basic sorts.

On the one hand, there has long been anecdotal and scholarly evidence, too, that geography and topography can limit how well and how often people are able to stay in touch with one another socially and intellectually as well as sexually. As the authors of one recent study commented, research has shown that there is a strong positive correlation between global genetic diversity within our species and geographic distance. The correlations observed have often been interpreted “as being consistent with a model of isolation by distance in which there are no major geographic discontinuities in the pattern of neutral genetic variation” (Hunley et al. 2009).

As these same authors note, however, discordant gene frequency patterns are also common within our species. It is obvious, too, that physical and social impediments to gene flow have regularly produced both larger discontinuities as well as concordant allele frequency patterns than would be expected based solely on isolation-by-distance (clinal) models of variation (Ibid.).

Adding social impediments to the mix of possible explanations brings into play the second way many have tried to explain why people around the globe appear to be so diverse. While there are many variants of this alternative argument, the essential ingredients are the baseline assumptions that (a) competition between individuals and groups is the main driving force of evolution, (b) human beings are by nature selfish and aggressive creatures, and (c) until recently humans lived in small tribal groups that were not just suspicious of strangers and other communities near and far, but were frequently at war them them, too. All of these claims are not only questionable, but are arguably contrary to the fundamental evolved characteristics of our species (Terrell 2015).


Part 2: Coming to grips with diversity 


References

Ball, Mark C., Laura Finnegan, Micheline Manseau, and Paul Wilson. 2010. Integrating multiple analytical approaches to spatially delineate and characterize genetic population structure: An application to boreal caribou (Rangifer tarandus caribou) in central Canada. Conservation Genetics 11, 6: 2131-2143.

Dyer, Rodney J., and John D. Nason. 2004. Population graphs: The graph theoretic shape of genetic structure. Molecular ecology 13, 7: 1713-1727.

Fortuna, Miguel A., Rafael G. Albaladejo, Laura Fernández, Abelardo Aparicio, and Jordi Bascompte. 2009. Networks of spatial genetic variation across species. Proceedings of the National Academy of Sciences 106, 45: 19044-19049.

Friedlaender, Jonathan S., Françoise R. Friedlaender, Jason A. Hodgson, Matthew Stoltz, George Koki, Gisele Horvat, Sergey Zhadanov, Theodore G. Schurr, and D. Andrew Merriwether. 2007. Melanesian mtDNA complexityPLoS One 2, 2: e248.

Friedlaender, Jonathan S., Françoise R. Friedlaender, Floyd A. Reed, Kenneth K. Kidd, Judith R. Kidd, Geoffrey K. Chambers, Rodney A. Lea et al. 2008. The genetic structure of Pacific IslandersPLoS Genet 4, 1: e19.

Garroway, Colin J., Jeff Bowman, Denis Carr, and Paul J. Wilson. 2008. Applications of graph theory to landscape genetics. Evolutionary Applications 1, 4: 620-630.

Greenbaum, Gili, Alan R. Templeton, and Shirli Bar-David. 2016. Inference and analysis of population structure using genetic data and network theory. Genetics 202.4: 1299-1312.

Hellenthal, Garrett, George BJ Busby, Gavin Band, James F. Wilson, Cristian Capelli, Daniel Falush, and Simon Myers. 2014. A genetic atlas of human admixture history.” Science 343, 6172: 747-751.

Hunley, Keith, Michael Dunn, Eva Lindström, Ger Reesink, Angela Terrill, Meghan E. Healy, George Koki, Françoise R. Friedlaender, and Jonathan S. Friedlaender. 2008. Genetic and linguistic coevolution in Northern Island MelanesiaPLoS Genet 4, no. 10 (2008): e1000239.

Hunley, Keith L., Meghan E. Healy, and Jeffrey C. Long. 2009. The global pattern of gene identity variation reveals a history of long‐range migrations, bottlenecks, and local mate exchange: Implications for biological race. American Journal of Physical Anthropology 139, 1: 35-46.

Kelly, Kevin M.,  2002. Population. In Hart, J. P. & Terrell, J. E. (eds.) Darwin and Archaeology: A handbook of key concepts, pp 243–256. Westport, Ct: Bergin & Garvey.

Moore, John H. 1994. Putting anthropology back together again: The ethnogenetic critique of cladistic theory. American Anthropologist (1994): 925-948.

Posada, David, and Keith A. Crandall. 2001. Intraspecific gene genealogies: Trees grafting into networks. Trends in Ecology & Evolution 16, 1: 37-45.

Pritchard, Jonathan K., Matthew Stephens, and Peter Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics 155, 2: 945-959.

Rieppel, Olivier. 2009. Hennig’s enkaptic system. Cladistics 25, 3: 311-317.

Roseman, Chartes C. 2014. Troublesome Reflection: Racism as the Blind Spot in the Scientific Critique of Race” Human biology 86, 3: 233-240.

Roseman, Charles C. 2014. “Random genetic drift, natural selection, and noise in human cranial evolution. Human Biology 86, 3: 233-240.

Skoglund, Pontus, Cosimo Posth, Kendra Sirak, Matthew Spriggs, Frederique Valentin, Stuart Bedford, Geoffrey R. Clark et al. 2016. Genomic insights into the peopling of the Southwest Pacific. Nature 538: 510-513.

Terrell, John Edward. 2006. Human biogeography: Evidence of our place in nature. Journal of Biogeography 33, 12: 2088-2098.

Terrell, John Edward. 2010a. Language and material culture on the Sepik coast of Papua New Guinea: Using social network analysis to simulate, graph, identify, and analyze social and cultural boundaries between communities. Journal of Island & Coastal Archaeology 5, 1: 3-32.

Terrell, John Edward. 2010b. Social network analysis of the genetic structure of Pacific islanders. Annals of human genetics 74, 3: 211-232.

Terrell, John Edward. 2015. A Talent for Friendship: Rediscovery of a Remarkable Trait. Oxford University Press.

Terrell, John Edward, and Pamela J. Stewart. 1996. The paradox of human population genetics at the end of the twentieth century. Reviews in Anthropology 25, 1: 13-33.

Wade, Nicholas. 2014. A Troublesome Inheritance: Genes, Race and Human History. Penguin.

Wilson, David Sloan, and Edward O. Wilson. 2008. Evolution for the Good of the Group”: The process known as group selection was once accepted unthinkingly, then was widely discredited; it’s time for a more discriminating assessment. American Scientist 96, 5: 380-389.

Wright, Sewall. 1932. The roles of mutation, inbreeding, crossbreeding, and selection in evolution. Proceedings of the Sixth International Congress of Genetics , Vol. 1: 356-366.

© 2017 John Edward Terrell. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. The statements and opinions expressed are those of the author(s) and do not constitute official statements or positions of the Editors and others associated with SCIENCE DIALOGUES.