Monday/Start of the semester links

During the break I was busy with typical holiday/break activities (including the first half of my daughter’s improbably exciting U11 girls’ basketball season) as well as a lot of intense reading/writing/research related activities. I’ll hopefully be blogging more about the latter in the next several months, but in the midst of them and out of the typical classroom teaching routine, blogging kind of fell by the wayside. Hopefully it will resume at a normal pace starting this week.

In the meantime, here are some good/interesting reads to get the week and semester started:

* Genomic analysis results: understanding, or Fairy dust? – Ken Weiss, writing at the Mermaid’s Tale, gives his latest on GWAS, “missing heritability,” and the reality of biological/genetic complexity:

In the face of this apparent complexity–many argue that life can’t really be that complex. One may feel that it’s just not plausible that hundreds or thousands of genes can be the explanation for traits that show orderly value distributions in populations. That orderliness, and the relatively orderly nature of evolution, and the fact that a trait can be knocked out by single genes, all might be seen as indicating that life must have been able to evolve our complex traits in a way that is not so complex after all. We’re just not understanding–yet!

* Our paper: Assemblathon 2 and pizza – Keith Bradnam provides some discussion of his recent paper at Haldane’s Sieve. It includes a fantastic use of pizza-making as a metaphor for genome assembly (the focus of their paper):

What is true for ‘making pizzas’ is also largely true for ‘making genome assemblies’. There are probably as many genome assemblers out there as there are pizza establishments in Davis, and people clearly want to know which one is the best. But how do you measure the ‘best’ genome assembly? Many published genome sequences result from a single assembly of next-generation sequencing (NGS) data using a single piece of assembly software. Could you make a better assembly by using different software? Could you make a better assembly just from tweaking the settings of the same software? It is hard to know, and often costly — at least in terms of time and resources — to find out.

* Starchy diet may have transformed wolves to dogs – The typical caveats of headlines apply, but this Science News piece blurbs a recent interesting (and not surprising!) paper about the co-evolution of domesticated canine diets:

Dogs can digest carbohydrates better than wolves can, and gaining that ability may have been an important step in taming the animals, evolutionary geneticist Erik Axelsson of Uppsala University in Sweden and his colleagues report online January 23 in Nature. As humans settled into farming communities, wolves may have given up their meat-only diets to scavenge carbohydrate-rich food from garbage dumps. Animals that could best make use of the starchy food may gradually have morphed over generations into man’s best friend.

As humans went through the ecological shift associated with intensified agricultural production and sedentism, a number of genetic variants associated with changing dietary practices because established and more widespread in human populations. The same seems to have occurred during the domestication of dogs (not surprisingly!). This is yet another example of evolution in action and a caution to not treat living things as representative of prehistoric realities. Humans, and human diet have evolved from the Paleolithic. There is a lot to learn about human diet through understanding the evolutionary process specific to human populations and regions, but living humans are not paleo-humans and trying to re-create paleo dietary practices as a health goal is a complicated and, I think, often misguided quest. Dogs have evolved…so have humans.

* Thanks for the Mutations, Dad – Peter Gray, in his latest post at The Evolving Father, talks about the importance of high rates of paternally-derived do novo mutations.

Various studies have suggested that fathers in higher primates (such as humans, apes, Asian and African monkeys) provide 4-6 times as many point mutations as do mothers. In other words, a gorilla baby could trace the vast majority of any novel mutations in its genome to its father rather than mother. In a recent study from Iceland, researchers provided the most rigorous study yet quantifying the sex-specific human parental mutation contribution. Employing whole genome scans of some 78 mothers, fathers, and their children, it turned out that fathers, on average, introduced 55 new mutations, mothers providing 14 new mutations. In other words, fathers provided about 4 times as many new mutations as mothers to their progeny.

* Ruth Benedict, Patterns of Culture: From Culture to cultures and…
* Eric Wolf, Europe and the People Without History – Geography, States, Empires – Jason Antrosio does double-duty with excellent posts on Benedict and Wolf.

UPDATE: And for something a little fun, I recently stumbled upon the WTFevolution tumblr…which is pretty great.

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Spring Syllabi

Today marks the beginning of the Spring semester at Wellesley. I am teaching two courses this semester, Introduction to Physical Anthropology (Anth 204), which I teach every Spring, and Human Biology and Society (Anth 314), a new upper level seminar that will be focused on personal genomics this semester. As I did in the Fall, here is a brief description of the two courses with links to the preliminary syllabus for each.

This is my fourth go-round with the intro class, and for the first time, I have not made major changes to it. For the second time in a row I am using two books for the course (in addition to an assortment of articles), Jonathan Marks’ “Alternative Introduction to Biological Anthropology” and “Evolution in Four Dimensions” by Eva Jablonka and Marion Lamb. I try to structure the intro course around several related questions:

* How does evolution operate?
* How do we understand human variation from an evolutionary perspective?
* How can the study of humans inform us as to how evolution works?

In reality, the course gets split roughly equally between four subject areas; straight evolutionary theory, human behavior and biology, primates and comparative perspectives, and the human fossil record. Jon Marks’ book covers the basic material associated with the subjects in what I find an insightful and pretty irreverent sort of way. It lacks the basic pedagogical tools that go along with a lot of more traditional textbooks (e.g. charts, tables, pictures), but with the advantage of being both cheaper and more on focus. The absence of these more traditional tools force/allow me to create my own supplementary material.

I like Jablonka and Lamb’s book primarily as a tool to get students thinking about how evolution operates in the specific case of humans, and how the study of humans can help elucidate the evolutionary processes somewhat unique to human prehistory. Their book puts a strong emphasis on so-called “non-Darwinian” mechanisms of inheritance (epigenetic, behavioral, symbolic), something that has gotten some push back from some prominent evolutionary biologists (see Jerry Coyne, here). Whether or not the mechanisms outlined by Jablonka and Lamb are significant operators in the larger biological world is somewhat irrelevant to me, though, as in the course, and personally, I am solely interested in the evolution of humans. And there are a number of strange things about human evolution, many of them focused on the development of the human brain as an adaptive structure that can accomodate really interesting and complex evolutionary dynamics.

My other course, Human Biology and Society, is new and, I think, will be quite interesting. I outlined the basics of the course a couple of weeks ago as I was finalizing my reading list for the semester. Patricia Williams, a law professor at Columbia (and a Wellesley alum!), had a nice essay last month that covers a lot of the issues I hope we will cover in the course (h/t Jennifer Wagner for the original link). Given the increasing availability of personal genetic/genomic data, how does this affect our understanding of the human condition? How does DNA technology change our understandings of the boundaries of an individual in space and time? How does genetic sequencing tell us not only about who we are, but who we might be come as a predictive mechanism of human health and disease? Students will have the opportunity, as one of the “texts” for the course, to get personal sequencing through 23andme.com, something that I hope will add a new level of pedagogical engagement to the course.

Hopefully it will all go well. The fun starts tomorrow. Here are the two syllabi:

* Introduction to Physical Anthropology (Anthropology 204)
* Human Biology and Society (Anthropology 314)

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“with a morphology similar to present-day humans”

Hominins with morphology similar to present-day humans appear in the fossil record across Eurasia between 40,000 and 50,000 y ago.

That is the opening line of an abstract from Fu, et al. (2013) detailing ancient DNA from ~40,000 year old fossil human remains in China. The paper, which was teased yesterday in the press, is up today at PNAS and is likely to generate lots of discussion. Before all that begins, I just wanted to point out how refreshing it is to see a 40,000 year old fossil described the way they do in the opening line. The number of publications that describe fossils affiliated with living humans, but existing tens of thousands of years in the past, as “modern humans” is more than I could possibly ever count (and yes, I know the very next line in the abstract refers to these specimens as “early modern humans”). It might be more cumbersome, but the description above is more accurate and a worthwhile change in the paleoanthropological lexicon.

*****

1. Qiaomei Fu, Matthias Meyer, Xing Gao, Udo Stenzel, Hernán A. Burbano, Janet Kelso, and Svante Pääbo (2013)
DNA analysis of an early modern human from Tianyuan Cave, China
PNAS; published ahead of print January 22, 2013, doi:10.1073/pnas.1221359110

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Got Anthropology?

Ever find yourself wishing you could read more Anthropology? Wishing there were more places to hear from anthropologists about what they do? If so, Jason Antrosio has put together a truly impressive list of current Anthropology blogs.

Check out the complete list here

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Crowd-sourcing my reading list

I am finalizing a new course for this upcoming semester that is focused on personal genomics. The class aims to simultaneously address two questions:

What can personal genomic data tell us?
What do we do with that information?

The course is an upper-level seminar, and I am hoping to incorporate personal genotype testing as a pedagogical element in the course using 23andme (which is why weeks 12-14 are blank in the syllabus). What I am interested in right now, though, is feedback on my reading list, pasted below. I have limited the course to just two books–Misha Angrist’s “Here lies a human being,” and Thomas Goetz’s “The Decision Tree”–but I am going pretty heavy on additional reading ranging from news reports, blogs, anthropological and medical texts. What am I missing? What should I change?

SYLLABUS (subject to change)

Week 1: (Jan. 28-Feb. 1) Introduction
Tuesday – How does genetic knowledge alter what it means to be human?
Friday – Your genes are not your own: genetics, kinship and family history

Readings:
• Goetz, chapters 1-2 (1-49)
• Angrist, chapter 1 (1-9)
• Ashley, et al. (2010), “Clinical assessment incorporating a personal genome, ” The Lancet 375:1525-1535
• Guttmacher, et al. (2004), “The family history—more important than ever,” The New England Journal of Medicine 351(22):2333-2336

Week 2: (Feb. 4-8): Background Genetics
Tuesday – Genetics 101 and 201: How do genes shape phenotypic variability?
Friday – Genetics 301: Genes, environment and determinism

Readings:
• Goetz, chapters 3-5 (50-115)
• Buchanan, “Why does genetic determinism persist, in spite of the evidence?” – http://ecodevoevo.blogspot.com/2010/02/why-does-genetic-determinism-persist-in.html

Week 3: (Feb. 11-15): Genomics and Consent
Tuesday – The scope of genomic information
Friday – What constitutes consent?

Readings:
• Goetz, chapters 6-7 (116-168)
• Angrist, chapters 2-3 (10-53)
• Harmon, “Indian Tribe wins fight to limit research of its DNA, “NY Times 4/21/10 – http://www.nytimes.com/2010/04/22/us/22dna.html?hp=&pagewanted=all&_r=0
• Vorhaus, “The Havasupai Indians and the Challenge of Informed Consent for Genomic Research” – Genomics Law Report – http://www.genomicslawreport.com/index.php/2010/04/21/the-havasupai-indians-and-the-challenge-of-informed-consent-for-genomic-research/#more-3201
• 23andMe consent document – https://www.23andme.com/about/consent/

Week 4: (Feb. 18-22): Legal genetics
Tuesday – (NO CLASS, MONDAY SCHEDULE)
Friday – Legal issues surrounding the use and control of genetic data

Readings:
• Angrist, chapter 4 (54-77)
• Feero, et al. (2011), “Genomics, health care, and society,” The New England Journal of Medicine 365(11):1033-1041
• Wright, “Responsible and effective use of personal genomes” – Genomes Unzipped http://www.genomesunzipped.org/2011/06/responsible-and-effective-use-of-personal-genomes.php#more-3620
• Conley & Vorhaus, “Supreme court to rule on patentability of human genes” – Genomics Law Report – http://www.genomicslawreport.com/index.php/2012/11/30/supreme-court-to-rule-on-patentability-of-human-genes/#more-6923 (click through to earlier links!)

Week 5: (Feb. 25-March 1): Prediction, risk and uncertainty
Tuesday – Probability theory and hazard ratios
Friday – Pleiotropy, penetrance, polygenic traits and effect size

Readings:
• Angrist, chapters 5-8 (99-168)
• Wiszmeg, et al. (2012), “Difficult questions and ambivalent answers on genetic testing, “ Culture Unbound-Journal of Current Cultural Research 4:463-480
• Cooper & Shendure (2011), “Needles in stacks of needles: Finding disease-causal variants in a wealth of genomic data” Nature Reviews Genetics 12:628-640

Week 6: (March 4-8): Human genomics, case study #1 – Genetic ancestry
Tuesday – Who are your ancestors? Single-system ancestry estimates
Friday – Whole genome ancestry estimation and challenges

Readings:
• Angrist, chapter 9-10 (169-221)
• Plagnol, “Exaggerations and errors in the promotion of genetic ancestry testing,” Genomes Unzipped – http://www.genomesunzipped.org/2012/12/exaggerations-and-errors-in-the-promotion-of-genetic-ancestry-testing.php
• Bolnick, et al. (2007), “The science and business of genetic ancestry testing,” Science 318(5849):399-400

Week 7 (March 11-15): Human genomics, case study #2 – Huntington’s Disease
Tuesday – Genetic epidemiology of Huntington Disease
Friday – Certain diagnosis, uncertain future

Readings:
• Goetz, chapters 9-10 (191-242)
• Block & Hayden (1990), “Predictive testing for Huntington’s Disease in childhood: challenges and implications” American journal of human genetics 46(1):1-4
• Cox & McKellin (1999), “There’s this thing in our family: predictive testing and the construction of risk for Huntington Disease” Sociology of Health & Illness 21(5):622-646.

Week 8 (March 18-22): SPRING BREAK – No Class

Week 9 (March 25-29): Human genomics, case study #3 – BRCA1, BRCA2 and breast cancer
Tuesday – The functional and epidemiological role of BRCA1 and BRCA2
Friday – Preventative medical intervention

Readings:
• Ellisen, et al. (1998), “Hereditary breast cancer” Annual review of medicine 49(1):425-436
• Finkler (2004), “Illusions of controlling the future: risk and genetic inheritance,” Anthropology & Medicine 10(1):51-70.
• Schwartz, et al. (2011) “Long-term outcomes of BRCA1/BRCA2 testing: risk reduction and surveillance” Cancer 118(2):510-517
• Werner-Lin, et al. (2012) “My funky genetics: BRCA1/2 mutation carriers’ understanding of genetic inheritance and reproductive merger in the context of new reprogenetic technologies” Families, Systems & Health 30(2):166-180

Week 10 (April 1-5): Human genomics, case study #4 –ApoE, heart disease and Alzheimer’s
Tuesday, April 2 – The ApoE gene cluster and variants
Friday, April 5 – ApoE and Alzheimer’s

Readings:
• Angrist, chapters 12-13, epilogue (239-284)
• Chilibeck, et al. (2011), “Postgenomics, uncertain futures, and the familiarization of susceptibility genes,” Social Science & Medicine 72(11)1768-1775
• Lock (2006), “Living with uncertainty: The genetics of late onset Alzheimer’s Disease” General Anthropology 13(2):1-9

Week 11 (April 8-12): Personal Genomics, week 1
Tuesday – An introduction to the discussion of personal genomic data
Friday – Personal genomic project work day (no class – AAPA conference)

Readings:
• Callier (2012) “Swabbing students: should universities be allowed to facilitate educational DNA testing?” American Journal of Bioethics 12(4):32-40.
• Hughes, “It’s Time To Stop Obsessing About the Dangers of Genetic Information” Slate (1/7/2013) – http://www.slate.com/articles/health_and_science/medical_examiner/2013/01/ethics_of_genetic_information_whole_genome_sequencing_is_here_and_we_need.single.html
• Dunsworth (2012), “Your genome is showing” (video) – http://fora.tv/2012/11/29/Your_Genome_is_Showing_Human_Origins_Gets_Personal (California Academy of Sciences)

Week 12 (April 15-19): Personal Genomics, week 2
Tuesday – Topic, TBD
Friday – Topic, TBD

Readings:
• TBD

Week 13 (April 22-26): Personal Genomics, week 3
Tuesday – Topic, TBD
Friday – Topic, TBD

Readings:
• TBD

Week 14 (April 29-May3): Personal Genomics, week 4
Tuesday – Topic, TBD
Friday – Topic, TBD

Readings:
• TBD

Week 15 (May 6-10): Conclusions
Tuesday – The ethics and practice of personal genomics

Readings:
• Kolor, et al. (2012) “Public awareness and use of direct-to-consumer personal genomic tests from four state population-based surveys, and implications for clinical and public health practice.” Genetics in Medicine 14:860-867

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The rise and fall of hominid genera

Erin Wayman, blogging for the Smithsonian at Hominid Hunting, has had a series on species of Homo you have probably never heard of. That post got me thinking about the rise and fall in commonly accepted taxa, particularly at the Genus level. Google’s Ngram viewer is a nice tool for visualizing some of the less frequently used generic designations that were formerly more popular. Behold:

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Online courses everywhere

On the same day my current employer announces its partnership with edX, my undergraduate alma mater, Emory University, announces its participation in a consortium of schools putting together a “semester online” via the 2U platform.

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It is official: Wellesley is partnering with edX (updated)

Apparently my ruminations this semester about online education have not been pointless. Wellesley announced this morning that they are partnering with edX, and will begin the process by producing four courses through edX in the 2013-2014 academic year.

I am excited by the news. I think it will be interesting to see how it all plays out and how aggressive and creative Wellesley and edX are in conceptualizing a liberal arts education in an online, and potentially massive-scale, learning environment. The College has not announced which four courses will be included in WellesleyX next year (or even how they will be chosen), but obviously the individual courses will play a large role in shaping what WellesleyX looks like. My previous thoughts on online learning are linked below:

> Between Two Professors: Pros and cons to online undergraduate education
> More thoughts on Wellesley College and online learning

UPDATE:
Wellesley College’s president, Kim Bottomly, has an
op-ed on the decision up at the Huffington Post

In the piece, President Bottomly provides a fairly concise summary of some of the criticisms of online education:

Ultimately, our mission is not merely to train students in the skills necessary for entry-level jobs, but rather to educate students to become lifelong learners and to have the skills for a lifetime of jobs. We believe that face-to-face interaction in the classroom and on campus is an essential part of the educational experience. Each class is an intellectual and interactive experience in which the teacher is responding continually to the students’ ability to understand and be excited about the topic, and the student is learning how to learn. Because of this, we have been skeptical about the current hype surrounding online education.

So why is Wellesley joining edX? What follows in the piece is a fairly standard set of positives; creative pedagogy development, expanded opportunities, alumnae connectivity…etc. But what strikes me as the most interesting and challenging is this:

We have also joined edX because we believe that the transformative experience of a liberal arts education, which has been so successful at Wellesley for generations, can contribute important value to the online learning space. Through edX and its partners, we will strive to develop the highest quality online education possible.

What does it mean to put a liberal arts education online, as opposed to simply putting an array of liberal arts courses online?

UPDATE 2: The Harvard Crimson called me earlier and their story on the announcement is now up, as well.

What I mean by “productive inefficiency” is the kind of community learning environment that is only possible when their are multiple contributors to the classroom content. I have a set of things that I want my students to learn throughout any given semester. If I only wanted the students to learn those things, I would spend most of my time lecturing, interspersing learning activities when appropriate. But I don’t want my students to just learn what I want them to learn. I want them to contribute their own learning goals as they become familiar with the course content. This is a difficult thing to achieve, but ultimately a much richer outcome, as students take responsibility not only of learning the content but for furthering the learning process itself. But there is no magic bullet for achieving this in a classroom and it often depends on understanding the perspectives and approaches individual students take towards the class material. I am not sure how this can be achieved in online learning settings. Many of the online platforms, including edX, have sophisticated systems for tracking specific learning goals, potentially making teaching very efficient with respect to a prior goals. Part of the value of a liberal arts classroom are the goals that are not established by me in advance.

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Paleoanthropology Picture of the Day

Continuing an occasional series…this is a picture of Lake Baringo, Kenya, taken from the shoreline of Betsy’s Campground in Kampi Ya Samaki (late 2004).

Lake Baringo sits in the central Rift Valley and is surrounded by fossiliferous exposures in pretty much every direction, spanning a huge time range from the earliest Miocene up to recent deposits. A number of interesting, though perhaps under discussed hominin fossils have been found in the region, including the Pliocene Tabarin mandible, several mandibles from the Pleistocene Kapthurin formation (with a large archaeological assemblage), the earliest argued Chimpanzee fossil, and the Orrorin Tugenensis material from the terminal Miocene/early Pliocene. The paleontological record of fossils from the region is vast.

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It’s a scale, scale, scale, scale world (part 2)

Following on my post from yesterday, I wanted to write a little more specifically about the significance of scale and our session at the AAAs.

Paleoanthropological data are produced and address questions at different scales. Consider the following:

Fossil – Fossils provide data at two ends of the scalar spectrum. First, fossils provide fine-grained data about the life-events of individual specimens. For example, the sub-adult fossils from Dmanisi (D2700+associated mandible and post-cranial elements) provides a lot of information specific to that individual. We can infer patterns of dental eruption, epiphyseal fusion, osteologically-preserved life-history events, dental and skeletal pathologies and possibly behavioral features such as the individuals diet. That is a lot of potential fine-scale data. Fossils also provide coarse-grained data about population/species level patterns of variation. We use fossils as not just individual specimens, but as representatives for fossil populations and/or fossil species. Here, the fine-grained individual data can translate directly into more coarse-grained species/population data, such as individual dental eruption serving as a proxy for population or species-specific patterns of eruption. The coarseness in the data are the result of the uncertainty in translating from the individual to the population or species level. Individuals vary. In lots of ways populations vary, too. In some ways, species vary. How these three levels relate in living populations is something that can be observed and recorded, but in the fossil record is a hypothesis that can (and should) be tested.

Adding additional coarseness to fossil data, at both the individual and population/species level is the temporal uncertainty associated with any given find. Unfortunately we do not have direct dates on a large fraction of the fossil record. Even those that do have directly dated contexts, do so with a methodologically-associated degree of uncertainty. Depending on the questions of interest, this temporal uncertainty is important.

Archaeology – Archaeological data is generally finer in scale than fossil data, spanning a successive range of time-sequenced layers. These layers generally represent a time-averaged accumulation of materials, whose temporal precision is a product of the specific site formation and sedimentological processes. In rare instances, archaeological data might provide fine-scale data approaching an instantaneous view of a horizontal spatial expanse, or so-called “living surface” (though the interpretations of sites as living surfaces likely outnumbers the reality of living surfaces by a large margin). Compared to fossils, however, archaeological data typically provide a view of an evolutionary sequence of time rather than a single point in time.

Genetics – Genetic data are interesting because the scalar perspective they provide depends on their source. Genetic data drawn from living people provide a window on our evolutionary past by revealing a complex pattern of inheritance going back in time. Using coalescent methods, this pattern can be seen as a semi-scaled, probabilistic window into the past, one that becomes fuzzier the deeper into the past you try to look. I say semi-scaled because the data represent genealogical relationships that require some calibration, usually an empirically-derived or estimated mutation rate (and/or recombination rate).

Increasingly, genetic material derived from prehistoric skeletal and fossil remains inform our understanding of human evolution. These data are particularly interesting because they can be used to look backwards (as we do with contemporary DNA) or forwards, providing an alternative evolutionary scaling mechanism by which to assess genetic variation in living humans. Much of the support for the Neandertal Genome Project, for example, was to narrow the range of evolutionary time encompassed by “human-specific” lineage changes to the period of time following a human-Neandertal divergence rather than the much larger window reflecting the divergence of fossil hominins from our (terminal Miocene/Pliocene) Pan-Homo ancestor.

There are many other lines of evidence I could mention (climatic, environmental, behavioral…), but even drawing from just the three above the potential complications associated with integrating these data, and the potential rewards for doing so, can become clear.

Getting back to our session, several of our presenters made scale an explicit focus. Jamie Clark, for example, talked about the differing interpretations of environmental change at Sibudu Cave, South Africa, depending on the scale at which you divide the data. Sibudu encompasses a long Middle to Late Pleistocene archaeological sequence that includes the appearance of a complex Howiesons Poort industry and the subsequent rapid demise and replacement of this industry by a less complex, more MSA-typical assemblage. This loss of complexity has been argued to be the result of an environmental change at the site, and viewed at a coarse scale, this argument is supported by the faunal and paleobotanical remains. If the data are examined at a level by level scale, however, it can be seen that the Howiesons Poort disappearance precedes the most dramatic environmental shift, presumably supporting a very different kind of argument for the archaeological transition.

More broadly, many of the talks (mine included), focused on the benefits from looking at Pleistocene evolutionary questions from a population, rather than paleontological, perspective. Such a view emphasizes the importance of community niche construction (Agustín Fuentes’ talk), population expansion and contraction (Luke Premo’s talk), and population structure (John Hawks’ talk).

My head is swirling in a bunch of nascent Thanksgiving Day preparations, so I will cut myself off now. But I would just like to conclude by saying that these issues of scale are a challenge. As Steve Kuhn wrote recently, the scale of our explanations needs to match the scale of the phenomena we are observing in the evolutionary record. But these issues of scale also represent an opportunity. They represent an opportunity to add greater strength to evolutionary arguments by creatively using scale, particularly changing scales of perspective, to circumvent problems of equifinality. In my talk, one of my conclusions was that the pattern of morphological variation in Neandertals and fossil humans provides support for very few speciation events in our recent (i.e. the Pleistocene) evolutionary past. But I also argued that such a view emphasizes population-level processes that cannot be adequately addressed with single lines of evidence but instead demand validation from different sources of data and perspective.

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