A new method for analyzing growth in extinct animals (dissertation summary 1)

The last year and a half was a whirlwind, and so I never got around to blogging about the fruits of my dissertation: Mandibular growth in Australopithecus robustus… Sorry! So this post will be the first installment of my description of the outcome of the project. The A. robustus age-series of jaws allowed me to address three questions: [1] Can we statistically analyze patterns of size change in a fossil hominid; [2] how ancient is the human pattern of subadult growth, a key aspect of our life history;  and [3] how does postnatal growth contribute to anatomical differences between species? This post will look at question [1] and the “zeta test,” new method I devised to answer it.

Over a year ago, and exactly one year ago, I described some of the rational for my dissertation. Basically, in order to address questions [2-3] above, I had to come up with a way to analyze age-related variation in a fossil sample. A dismal fossil record means that fossil samples are small and specimens fragmentary – not ideal for statistical analysis. The A. robustus mandibular series, however, contains a number of individuals across ontogeny – more ideal than other samples. Still, though, some specimens are rather complete while most are fairly fragmentary, meaning it is impossible to make all the same observations (i.e. take the same measurements) on each individual. How can growth be understood in the face of these challenges to sample size and homology?

Because traditional parametric statistics – basically growth curves – are ill-suited for fossil samples, I devised a new technique based on resampling statistics. This method, which I ended up calling the “zeta test,” rephrases the question of growth, from a descriptive to a comparative standpoint: is the amount of age-related size change (growth) in the small fossil sample likely to be found in a larger comparative sample? Because pairs of specimens are likelier to share traits in common than an entire ontogenetic series, the zeta test randomly grabs pairs of differently-aged specimens from one sample, then two similarly aged specimens from the second sample, and compares the 2 samples’ size change based only on the traits those two pairs share (see subsequent posts). Pairwise comparisons maximize the number of subadults that can be compared, and further address the problem of homology. Then you repeat this random selection process a bajillion times, and you’ve got a distribution of test statistics describing how the two samples differ in size change between different ages. Here’s a schematic:

1. Randomly grab a fossil (A) and a human (B) in one dental stage (‘younger’), then a fossil and a human in a different dental stage (‘older’). 2. Using only traits they all share, calculate relative size change in each species (older/younger): the zeta test statistic describes the difference in size change between species. 3. Calculate as many zetas as you can, creating a distribution giving an idea of how similar/different species’ growth is.

The zeta statistic is the absolute difference between two ratios – so positive values mean species A  grew more than species B, while negative values mean the opposite. If 0 (zero, no difference) is within the great majority of resampled statistics, you cannot reject the hypothesis that the two species follow the same pattern of growth. During each resampling, the procedure records the identity and age of each specimen, as well as the number of traits they share in common. This allows patterns of similarity and difference to be explored in more detail. It also makes the program run for a very long time. I wrote the program for the zeta test in the statistical computing language, R, and the codes are freely available. (actually these are from April, and at my University of Michigan website; until we get the Nazarbayev University webpage up and running, you can email me for the updated codes)

The zeta test itself is new, but it’s based on/influenced by other techniques: using resampling to compare samples with missing data was inspired by Gordon et al. (2008). The calculation of ‘growth’ in one sample, and the comparison between samples, is very similar to as Euclidean Distance Matrix Analysis (EDMA), devised in the 1990s by Subhash Lele and Joan Richtsmeier (e.g. Richtsmeier and Lele, 1993). But since this was a new method, I was glad to be able to show that it works!

I used the zeta test to compare mandibular growth in a sample of 13 A. robustus and 122 recent humans. I first showed that the method behaves as expected by using it to compare the human sample with itself, resampling 2 pairs of humans rather than a pair of humans and a pair of A. robustus. The green distribution in the graph to the left shows zeta statistics for all possible pairwise comparisons of humans. Just as expected, that it’s strongly centered at zero: only one pattern of growth should be detected in a single sample. (Note, however, the range of variation in the green zetas, the result of individual variation in a cross-sectional sample)

In blue, the human-A. robustus statistics show a markedly different distribution. They are shifted to the right – positive values – indicating that for a given comparison between pairs of specimens, A. robustus increases size more than humans do on average.

We can also examine how zeta statistics are distributed between different age groups (above). I had broken my sample into five age groups based on stage of dental eruption – the plots above show the distribution of zeta statistics between subsequent eruption stages, the human-only comparison on the left and the human-A. robustus comparison on the right. As expected, the human-only statistics center around zero (red dashed line) across ontogeny, while the human-A. robustus statistics deviate from zero markedly between dental stages 1-2 and 3-4. I’ll explain the significance of this in the next post. What’s important here is that the zeta test seems to be working – it fails to detect a difference when there isn’t one (human-only comparisons). Even better, it detects a difference between humans and A. robustus, which makes sense when you look at the fossils, but had never been demonstrated before.

So there you go, a new statistical method for assessing fossil samples. The next two installments will discuss the results of the zeta test for overall size (important for life history), and for individual traits (measurements; important for evolutionary developmental biology). Stay tuned!

ResearchBlogging.org Several years ago, when I first became interested in growth and development, I changed this blog’s header to show this species’ subadults jaws – it was only last year that I realized this would become the focus of my graduate career.

Gordon AD, Green DJ, & Richmond BG (2008). Strong postcranial size dimorphism in Australopithecus afarensis: results from two new resampling methods for multivariate data sets with missing data. American journal of physical anthropology, 135 (3), 311-28 PMID: 18044693

Richtsmeier JT, & Lele S (1993). A coordinate-free approach to the analysis of growth patterns: models and theoretical considerations. Biological Reviews, 68 (3), 381-411 PMID: 8347767

Updated note on jaw growth in Australopithecus robustus

A few weeks ago I posted some early observations I’ve made about mandible growth in Australopithecus robustus compared with humans. My dissertation tests the null hypothesis that overall mandible growth is identical in the two species. This is complicated by the fact that there are many aspects of jaw growth (i.e. lots of variables) and not all fossils preserve the same parts. In these early preparatory stages I’m looking only at the height and width of the jaw at the second baby molar (in kids) and the second permanent premolar that replaces this baby tooth in older individuals, since this is something most of the fossils have. This work will get me ready for the hard comparisons, where the fossils aren’t so kind.

One concern I had in the earlier post was that my human sample was (and still is) fairly small, making comparisons rather tentative. Since then, I have about doubled my human sample (but I still have lots of work to do), so it’s timely to see if my earlier observations have held up. AND THEY DO!

To the right is a plot of jaw height at said tooth position across the growth period, humans being the black circles and A. robustus the thick red ones. Note that measures are standardized, taken relative to the smallest (not necessarily the youngest) individual in each sample. Before, I’d found that the two samples overlapped up to dental stage 4 (when the first permanent tooth comes in). After this point, the A. robustus jaw gets much larger through early adulthood, whereas in humans the height increase isn’t so drastic. With a larger sample, there is a bit more overlap in relative jaw height (especially early on), but the overall result is the same as I found earlier. Neat!

To the left is a similar plot, this time looking at width of the jaw across the growth period (these are also size-standardized as above, colors are the same). What’s remarkable is that the width of the human jaw is pretty much the same from infancy to adulthood. I remember thinking this when I first started looking at human jaws early last summer, but I’d never looked at how they compare with A. robustus, whose jaw continues to increase in absolute and relative width with age (and possibly even through adulthood; Lockwood et al. 2007). This plot is admittedly a bit confusing, as sizes are measured relative to the smallest and not youngest individuals, and the narrowest human jaw is in dental stage 4. The A. robustus sample also includes a very old adult (the highest point on the plot) while the human sample only goes to early adulthood. But the basic patterns are still pretty different: A. robustus jaws get wider up to dental stage 5 (you could think of it as pre- or early adolescence) then level out (not including our large older adult), but humans’ average jaw width is fairly constant throughout ontogeny. Of course, this is at only one position along the jaw, and others will probably different.

The fragmented jaws of the youngest A. robustus (i.e. SK 63 and SK 438) do not look too different from their human counterparts, but adults are very different. Here we can see part of the reason why. Bear in mind, though, that other aspects of mandible shape do differ between these species from birth. For example, humans have a bony chin from infancy, whereas A. robustus always lacks a true chin (SK 74 is an older, probably female adult A. robustus that does have a rather anomalous “chin” but it is not homologous to ours). Not all aspects of species-specific mandible shape arise during postnatal growth!

But there you go, an enlarged human sample produces a result consistent with my earlier observation. Note that these pictures do not represent statistical tests of my hypothesis! Yes, a visual inspection of the plotted numbers suggests the two species differ in how jaw height and width grows. But saying something statistical and “definitive” is difficult. In terms of height, growth does seem pretty much the same during childhood, but then divergent later on. Width growth in the two species seems totally different. To further complicate things, a “shape” ratio of jaw width divided by height (not shown) suggests parallel (but not identical) growth trajectories in the two species. What do these observed differences mean for the null hypothesis? Which and how many variables can differ before I can feel confident about whether to reject the hypothesis? Oy, I have my work cut out for me. Stay tuned!

That paper I referenced
Lockwood, C., Menter, C., Moggi-Cecchi, J., & Keyser, A. (2007). Extended Male Growth in a Fossil Hominin Species Science, 318 (5855), 1443-1446 DOI: 10.1126/science.1149211

Variation: a blessing and a curse

Trying to start on finishing my dissertation, I’m thinking about the issue dental development and how it relates to skeletal growth. Specifically I’m trying to decide whether I want to analyze my human and Australopithecus robustus samples based on estimates of “dental age,” or if I want to be a bit more cavalier and divide the sample into rougher age categories.

To avoid copyright issues, here’s a crappy picture I drew a few years ago, of the youngest A. robustus jaws. The youngest, “SK 438” is erupting its last baby tooth (bottom right), while the others have their full set of baby teeth, and none of them has its first adult tooth yet. I don’t think I can estimate ages accurately enough to capture the true chronological difference between SK 438 and the rest. Would I be better off just dividing the group into “younger” (SK 438) and “older” (the rest) infants, or even lumping them all together as simply “infants”?

On the one hand, I could assign individuals a chronological age based on a modern referent of known age, at similar stages of dental development. This could allow me to get more fine-scale glimpses into patterns of growth in my samples, but that’s assuming I’ve accurately estimated their ages. Individuals vary in the ages and sizes at which their teeth erupt; a person’s first molar, for example, may erupt at anywhere from 4-8 years of age. How can I estimate an individual’s age in light of such variation? And what if I’m as poor a judge of ages as Dennis Duffy?! Conceivably I could program my analysis to account for error estimation (which in itself could be educational and interesting, but is it worth the trouble?), but this would also add a further source of uncertainty. And it’s like Dwight Schrute said (Michael Scott said), “K-I-S-S: keep it simple, stupid. Great advice, hurts my feelings every time.”

On the other hand, I could divide my sample into coarse age categories – say, putting specimens who’ve attained a given level of dental development in the same group, such as ‘infant, child, juvenile, adolescent, and young adult.’ This method loses the temporal resolution of the first method, but also avoids the possible errors of assigning strict ages I’m pretty sure I would not infer accurately. But, tooth development does not show a clean 1-to-1 relationship with other systems in the body, such as hormonal axes or the bony skeleton. It’s uncertain how accurately kids can be put in any of the above categories (based on general life history variables; Bogin 1999) based on dental development.

Choices, choices.

Variation is a problem for biologists. The theory of evolution was conceived as a way to explain the conundrum of why there is such remarkable variation in the forms of life that Earth is lucky to have harbored. The problem of within-species variation in the relative timing of skeletal and dental development isn’t just a bug-bear for paleoanthropologists. It’s important to medical doctors and pathologists investigating genetically-based developmental disorders, and to epidemiologists looking at aspects of population health, such as the prevalence of growth stunting. It’s also important for forensics specialists who need to use biological clues about the age and identity of crime victims and defendants. I mean, how else would we know whether Jon Voight bit both Kramer and this pencil?

The silver lining, I suppose, on this storm-cloud of biological of variation is that without variation there cannot be evolution. And stasis is boring. If nothing changed since the Cambrian, none of us would be here today. We’d probably be some gross stupid monstrous thing, like this Hallucigenia to the right. It’s the quirks and weird variants that arise randomly, that make evolution possible. If individuals all developed exactly the same, then all organisms through all time would be the exact same, and probably all would have gone extinct as they succumbed to some sinister fate, no new variants would have arisen that may have been able to survive the devastation.

So variation is a blessing and a curse. Individual and population variation make it difficult to state norms such as what is “average” or “healthy,” and nothing to be concerned about. Variation is also the magic ingredient of adaptation, without which Life could not survive the randomness inherent in any environment.

Things I cited
Bogin, B. (1999). Evolutionary perspective on human growth Annual Review of Anthropology, 28 (1), 109-153 DOI: 10.1146/annurev.anthro.28.1.109

Also 30 Rock, The Office and Seinfeld. Well done, NBC.

New beef with boisei – maybe the dingo ate their babies?

ResearchBlogging.orgUnfortunately, the title is not in reference to a study demonstrating that early hominids fell prey to wild dogs. But Elaine Benes would have appreciated it.

As part of my Latitudes Tour, I’m in Nairobi for a couple of days, hoping to spend some quality time with the young Australopithecus boisei kids at the Nairobi National Museum. Recall (that is, if I’ve mentioned it here?) that my dissertation research is on growth of the lower jaw, in Australopithecus robustus as compared to modern humans. The study of growth obviously requires analyzing individuals across different age groups (an “ontogenetic series” is the fancy term). Admittedly, then, the focus on A. robustus is chiefly because this species has the largest ontogenetic sample of any early hominid (tho at nearly 15 subadults, it’s still not as large as one could hope). Also because A. robustus was totally badass.

Australopithecus boisei makes an important comparison for A. robustus, because the two species are allegedly evolutionary ‘sisters’ – the “robust” australopithecines (though I’m personally not convinced that these two are each other’s closest relative). So their growth should be pretty similar. At the same time, though, A. boisei shows much greater adaptations to heavy chewing – they’ve been referred to as “hyper-robust.” So comparing growth in these species should elucidate how their differences arise.
Problem is, there just aren’t enough kids! It’s like that song by Arcade Fire. Wood and Constantino (2007) published a pretty comprehensive review of A. boisei, including a 1.5-page table of the skulls and teeth attributed to the species. So far as I know, only 4 specimens in this table are subadult mandibles, and so far as I can tell, they’re all about the same age (right around the age that the first permanent molar comes in). There are so many jaws of adult A. boisei (although many of these are abraded mandibular bodies lacking teeth) – so how can there be fewer subadults?!?!

A very preliminary observation of infant-child pairs in the two species suggests they both increase in size fairly dramatically between when they only have baby (a.k.a. “deciduous” or “milk”) teeth and when the first permanent molar comes in. But this is just a preliminary observation based on 2 specimens of each species! Take with a grain of salt!
On second thought, maybe I’ll propose the nearly untestable hypothesis that bone-eating hyenas ate the boisei babes, and that’s why we don’t have their jaws. What could have been nicely preserved subadult boisei bones are instead coprolites (fossilized poops). A little spectacular, yes, but it’s also been hypothesized that many of the A. robustus fossils we know and love came to us as carnivores’ scraps.
further reading:
Wood, B., & Constantino, P. (2007). Paranthropus boisei: Fifty years of evidence and analysis American Journal of Physical Anthropology, 134 (S45), 106-132 DOI: 10.1002/ajpa.20732


I’m going to do my best to keep up with the blog during by Big Summer Adventure, and one thing I’d like to do is “F-ing Fossil Friday!” in which I focus on fossils for a bit. We’ll see if I can make this pan out.
Today I got out the rest of the Australopithecus robustus mandibles at the Transvaal Museum (above), save for I think maybe 1. As you can see from the picture, taphonomy (what happens to an animal’s remains between death and our digging them up) creates a serious challenge for the study of variation in this species. I’m focusing on ontogenetic variation – differences associated with growth and development. In spite of its fragmentary nature, so far as I know this is the best ontogenetic series of any fossil hominid (I should probably look more into A. afarensis here, too). In the bottom left you’ll see SK 438, the youngest in the sample, whose baby teeth haven’t quite come in all the way. Poor little guy! At the top right corner is SK 12, probably the oldest individual and also a big bugger.
One thing that I’ve noticed so far, only a preliminary observation that I need to actually run some numbers on, is that as individuals get older, the length of their tooth row (molars and premolars) gets shorter. This is because of the tendency for teeth to move forward during growth – “mesial drift” – and for adjacent teeth to literally wear into one another, their ends becoming flatter and flatter. While I should have realized this, it was surprising at first to find some dimensions of the lower jaw actually decreasing during growth. Now, I still have to run some tests to see if this is a biologically significant phenomenon. But it’s always nice to learn something new, even after just 2 days back with my best extinct buddies.
Stay tuned to future eFfing fossil Fridays!

Big trip 2011

It’s dawning on me now that I leave the country for the rest of the summer in just over 24 hours. First I’ll be in Pretoria for a few weeks studying Australopithecus robustus fossils at the Transvaal Museum. Then I’m off to Nairobi for a few days to check out some fossils at the Natural History Museum there. I’ve never been to Nairobi, and I’ll admit I’m a little nervous; I’ll keep you posted as to how it goes. Then right before my mum’s birthday I head to Tbilisi, Georgia for the 2nd annual Dmanisi Paleoanthropology Field School, until the end of August. Here’s a schematic of what my trip will look sorta like, starting from bottom to top.:
My whole life was up in the air for most of the first half of the year. But everything seems to have come together, so hopefully the second half of 2011 will be better than the first. That said, I don’t think I’m ready to go yet!


Some fun new things in anthropology of late. For starters, friend and colleague Adam Van Arsdale co-authored a paper recently released in Journal of Human Evolution about variation in the Dmanisi mandibles <!–[if supportFields]> ADDIN EN.CITE Rightmire19819817Rightmire, G. PhilipVan Arsdale, Adam P.Lordkipanidze, DavidVariation in the mandibles from Dmanisi, GeorgiaJournal of Human EvolutionJournal of Human EvolutionIn Press, Corrected ProofSystematicsRandom resamplingDimorphismPeriodontal diseaseSpeciesHomo erectushttp://www.sciencedirect.com/science/article/B6WJS-4S9R84K-2/1/805607b801be11bd456682d5a01816b2 <![endif]–>(Rightmire et al.)<!–[if supportFields]><![endif]–>. Dmanisi, in the Republic of Georgia and dating to about 1.77 mya, is interesting because the human fossils (Homo erectus) there represent the earliest definite excursions of hominins outside of Africa. Also interesting is the fact that the assemblage very likely represents a “paleodeme,” i.e. an actual living population. It was recently reported <!–[if supportFields]> ADDIN EN.CITE de Lumley200815015017de Lumley, Marie-AntoinetteBardintzeff, Jacques-MarieBienvenu, PhilippeBilcot, Jean-BaptisteFlamenbaum, GuyGuy, ChristopheJullien, Michelde Lumley, HenryNabot, Jean-PhilippePerrenoud, ChristianProvitina, OlivierTourasse, MartineImpact probable du volcanisme sur le décès des Hominidés de DmanissiComptes Rendus PalevolComptes Rendus Palevol61-7971DmanissiGéorgieHomo georgicusÉruption volcaniqueTéphrasÉtiologie des décèsVictimes du volcanismeDmanisiGeorgiaHomo georgicusVolcanic eruptionTephrasDeath aetiologyVictims of volcanism2008http://www.sciencedirect.com/science/article/B6X1G-4RR8D7V-1/1/015a368361815b7255927993ac9444a7 <![endif]–>(de Lumley et al. 2008)<!–[if supportFields]><![endif]–> that the Dmanisi hominins were probably a single group that was trapped quickly in a volcanic catastrophe—bad for them, good for paleontologists. So, Philip Rightmire, our friend Adam and David Lordkipandize have written a paper in response to an earlier paper suggesting that the size variation in the Dmanisi mandibles was so great that it represents more than one taxon. Rightmire and colleagues demonstrated, I think convincingly, that much of this ‘dimorphism’ is likely the result of taphonomic (the D2100 mandible is broken inferiorly), pathological and ontogenetic factors (the D2600 mandible is huge, possibly due to its advanced age and “pathology associated with dental wear”). So Dmanisi is pretty sweet: very early Homo all the way out in Georgia at least 1.7 mya, and we have a good collection of what probably represents not just a single, dimorphic species, but an actual (sub)population. Kudos, Adam!

What else…Oh yes! Another recent study suggests that vertical climbing costs the same energy per unit of body-weight in primates <!–[if supportFields]> ADDIN EN.CITE Hanna200820420417Hanna, Jandy B.Schmitt, DanielGriffin, Timothy M.The Energetic Cost of Climbing in PrimatesScienceScienceScience898-32058782008May 16, 2008http://www.sciencemag.org/cgi/content/abstract/320/5878/898 10.1126/science.1155504<![endif]–>(Hanna et al. 2008)<!–[if supportFields]><![endif]–>. Jandy Hanna (no—apparently it’s not a pseudonym) and team MacGyvered a vertical climbing treadmill that also recorded energy expenditure (they had more than just a coat hanger, hock of Silly Putty and a tube sock), and subjected some small-bodied primates to some bouts of vertical climbing (man, anthropology can be sweet). They somehow also included humans in this study, but I’m not exactly clear on how yet, maybe I’ll consult their Supporting Material and get back to you on that. Anyway, they found that across the body sizes (from .17 kg to 1.4 kg) vertical climbing efficiency is more or less equal; humans fall within the confidence limits. Which is cool because as primates increase in body size they become more efficient at walking. This is because increased body size is associated with longer legs, requiring less muscle activity to keep moving. What does this mean? This suggests to the authors that the very earliest primates (Back to the Eocene) were probably very, very small-bodied, and this small size allowed them to move into a vertical-climbing niche with little to no energetic cost. It would be really interesting to see this study performed on more primate taxa, especially larger body sizes, maybe comparing monkeys to apes.

Finally, apparently the verdict is in: “Great Apes prefer cooked food” <!–[if supportFields]> ADDIN EN.CITE Wobber20320317Wobber, VictoriaHare, BrianWrangham, RichardGreat apes prefer cooked foodJournal of Human EvolutionJournal of Human EvolutionIn Press, Corrected ProofCookingDietHominid evolutionTubersMeathttp://www.sciencedirect.com/science/article/B6WJS-4SHN0B6-1/1/682f7743b00dd6a621c64bf00467be64 <![endif]–>(Wobber et al.)<!–[if supportFields]><![endif]–>. I could have told you that, I mean think: a delicious medium steak vs. crappy, uncooked, parasite-teeming jungle fruit? The point was to test the hypothesis that food preparation in the form of cooking probably occurred and was widely accepted quickly after hominins garnered control of fire. Richard Wrangham (3rd author on the paper) has been into the idea that cooked food was superlatively important in the course of human evolution (see “Out of the Pan and into the fire” in Tree of Origin, edited by Franz de Waal (2001)), and I suppose here he set out to examine the issue scientifically. I’m not terribly informed about or interested in this issue, though it is a bit neat. Basically they went to the Yerkes primate research facility in Hottlanta and the Leipzig Zoo and gave chimps, bonobos, gorillas, and orangutans free-will choices between raw and cooked tubers processed various ways. Most of the time the cooked tuber (or apples or beef, in some cases) was selected, and eureka there’s proof that early hominins had this inherent preference for something about cooked food, appeasing the Chef Boyardee inside them. They end with, “Overall, our findings conform to evidence that wild chimpanzees choose seeds that have been heated by wild fires (Brewer, 1978), demonstrating that great apes possess a preference for cooked items” (Wobber et al., in press). Well, maybe. I think cooked seeds are a bit different from cooked tubers and meat. Plus, these tests were all conducted on captive apes, many of whom had eaten cooked food before, sometimes regularly. I know it’s less feasible, but it would be more convincing if somehow wild apes could have been tested with foods they’d be most likely to encounter in the wild.

What the paper didn’t address, and which I think is much more interesting, is how (and when) exactly these early hominins would have cooked food. Bear with me. So you’re a hominin with fire—did you make it or did you find it naturally somehow?—and you know that it’s super effing hot, it can harden sticks, it scares away some predators, and that generally when things go into it they don’t come out of it. Why the hell would you throw your hard-earned food into it? Perhaps the earliest chefs noticed that wild-fire heated foods (cf. the chimps, above) were preferable to raw ones, for whatever reason, and maybe they started trying it with multiple foods. Ok, but how did they cook? In Wobber et al.’s experiment the tubers were oven-baked, but I don’t think they had Kenmore ovens in the Pleistocene. I don’t know, maybe I’m over-thinking this (I usually do), but I think what’s much more interesting, and admittedly more difficult to find out and test, is how the earliest cooking would have been done. Honestly I thought this paper was a bit silly. I mean if you want to go to the zoo, you don’t have to come up with an experiment. The Lincoln Park Zoo in Chicago is free—and they have a one-armed gibbon that is super sweet.

Anyway, that’s the news hereabouts. Oh, Jerry De Silva just successfully defended his PhD dissertation, and his talk was really cool and informative (it was about climbing and feet, and you know how I love climbing). This Wednesday Robin Nelson will be defending her dissertation, and although I’m no psychic, no Johnny Carson, I’m pretty confident that her talk will be interesting and that she will defend successfully. So congratulations to Jerry and (prematurely) to Robin! Oh, and Kristen got a job and her research grant, so Kudos to her, too. And I’m gonna run my first half-marathon in a week and a half. Sweet.


<!–[if supportFields]> ADDIN EN.REFLIST <![endif]–>de Lumley M-A, Bardintzeff J-M, Bienvenu P, Bilcot J-B, Flamenbaum G, Guy C, Jullien M, de Lumley H, Nabot J-P, Perrenoud C, Provitina O, Tourasse M (2008) Impact probable du volcanisme sur le décès des Hominidés de Dmanissi. Comptes Rendus Palevol 7(1):61-79

Hanna JB, Schmitt D, Griffin TM (2008) The Energetic Cost of Climbing in Primates. Science 320(5878):898-

Rightmire GP, Van Arsdale AP, Lordkipanidze D Variation in the mandibles from Dmanisi, Georgia. Journal of Human Evolution In Press, Corrected Proof

Wobber V, Hare B, Wrangham R Great apes prefer cooked food. Journal of Human Evolution In Press, Corrected Proof<!–[if supportFields]><![endif]–>