Did Neandertal brains grow like humans’ or not?

July 26, 2016July 26, 2016 / zcofran / 1 Comment

According to Marcia Ponce de Leon and colleagues, “Brain development is similar in Neandertals and modern humans.” They reached this conclusion after comparing how the shape of the brain case changes across the growth period of humans and Neandertals. This finding differs from earlier studies of Neandertal brain shape growth (Gunz et al. 2010, 2012).

Although Neandertals had similar adult brain sizes as humans do today, the brains are nevertheless slightly different in shape:

Endocranial surfaces of a human (left, blue) and Neandertal (right, red), from Gunz et al. (2012). These surfaces reflect the size and shape of the brain, blood vessels, cerebrospinal fluid, and meninges.

Gunz et al. (2010, 2012) previously showed that endocranial development in humans, but not in Neandertals or chimpanzees, has a “globularization phase” shortly after birth: the endocranial surface becomes overall rounder, largely as a result of the expansion of the cerebellum:

Endocranial (e.g., brain) shape change in humans (blue), Neandertals (red) and chimpanzees (green), Fig. 7 from Gunz et al. (2012). Age groups are indicated by numbers. The human “globularization phase” is represented by the great difference in the y-axis values of groups 1-2 (infants). The Neandertals match the chimpanzee pattern of shape change; Neandertal neonates (LeM2 and M) do not plot as predicted by a human pattern of growth.

Ponce de Leon and colleagues now challenge this result with their own similar analysis, suggesting similar patterns of shape change with Neandertals experiencing this globularization phase as well (note that endocranial shapes are always different, nevertheless):

Endocranial shape change in humans (green) and Neandertals (red), from Ponce de Leon et al. (2016). Note that the human polygons and letters represent age groups, whereas the Neandertal polygons and labels are reconstructions of individual specimens.

The biggest reason for the difference between studies is in the fossil sample. Ponce de Leon et al. have a larger fossil sample, with more non-adults including Dederiyeh 1-2, young infants in the age group where human brains become more globular.

Comparison of fossil samples between the two studies.

But I don’t think this alone accounts for the different findings of the two studies. Overall shape development is depicted in PC 1: in general, older individuals have higher PC1 scores. The globularization detected by Gunz et al. (2010; 2012) is manifest in PC2; the youngest groups overlap entirely on PC1. The biggest difference I see between these studies is where Mezmaiskaya, a neonate, falls on PC2. In the top plot (Gunz et al., 2012), both Mezmaiskaya and the Le Moustier 2 newborn have similar PC2 values as older Neandertals. In the bottom plot (Ponce de Leon et al., 2012), the Mezmaiskaya neonate has lower PC2 scores than the other Neandertals. Note also the great variability in Mezmaiskaya reconstructions of Ponce de Leon et al. compared with Gunz et al.; some of the reconstructions have high PC2 values which would greatly diminish the similarity between samples. It’s also a bit odd that Engis and Roc de Marsal appear “younger” (i.e., lower PC1 score) than the Dederiyeh infants that are actually a little bit older.

Ponce de Leon et al. acknowledge the probable influence of fossil reconstruction methods, and consider other reasons for their novel findings, in the supplementary material. Nevertheless, a great follow-up to this, to settle the issue of Neandertal brain development once and for all, would be for these two research teams to join forces, combining their samples and comparing their reconstructions.

REFERENCES

Gunz P, Neubauer S, Maureille B, & Hublin JJ (2010). Brain development after birth differs between Neanderthals and modern humans. Current Biology : 20 (21) PMID: 21056830

Gunz P, Neubauer S, Golovanova L, Doronichev V, Maureille B, & Hublin JJ (2012). A uniquely modern human pattern of endocranial development. Insights from a new cranial reconstruction of the Neandertal newborn from Mezmaiskaya. Journal of Human Evolution, 62 (2), 300-13 PMID: 22221766

Ponce de León, M., Bienvenu, T., Akazawa, T., & Zollikofer, C. (2016). Brain development is similar in Neanderthals and modern humans Current Biology, 26 (14) DOI: 10.1016/j.cub.2016.06.022

Osteology Everywhere: Ilium Nublar

June 30, 2015 / zcofran / 1 Comment

Jurassic Park is objectively the greatest film ever made, so I don’t need to explain why I recently watched it for the bajillionth time. Despite having seen this empirically excellent movie countless times, I finally noticed something I’d never seen before.

Hold on to your butts. What's that on the screen in front of Ray Arnold?

Hold on to your butts – what’s that on the screen in front of John Arnold? (image credit)

The film takes place on the fictitious island “Isla Nublar,” a map of which features prominently in the computer control room when s**t starts to go down. Here’s a clearer screenshot of one of Dennis Nedry‘s monitors:

Isla Nublar from the JP control room. Quiet, all of you! They’re approaching the tyrannosaur paddock…. (image credit)

It dawned on me that the inspiration for this island is none other than MLD 7, a juvenile Australopithecus africanus ilium from the Makapansgat site in South Africa:

Figure 1 from Dart, 1958. Left side is MLD 7 and right is MLD 25. Top row is the lateral view (from the side) and bottom row is the medial view (from the inside). These two hip bones are from the left side of the body (see the pelvis figure in this post). Note the prominent anterior inferior iliac spine on MLD 7, a quintessential feature of bipeds.

Isla Nublar is basically MLD 7 viewed at an angle so that appears relatively narrower from side to side:

MLD at a slightly oblique view (or stretched top to bottom) magically transforms into Isla Nublar.

MLD 7 at a slightly oblique view (or stretched top to bottom) magically transforms into Isla Nublar.

It’s rather remarkable that some of the most complete pelvic remains we have for australopithecines are two juveniles of similar developmental ages and sizes from the same site. In both, the iliac crest is not fused, and joints of the acetabulum (hip socket) hadn’t fused together yet. The immaturity of these two fossils matches what is seen prior to puberty in humans and chimpanzees. Berge (1998) also noted that MLD 7, serving as an archetype for juvenile Australopithecus, is similar in shape to juvenile humans, whereas adult Australopithecus (represented by Sts 14 and AL 288) are much flatter and wider side to side. Berge took this pattern of ontogenetic variation to match an ape-like pattern of ilium shape growth. This suggests a role of heterochrony in the evolution of human pelvic shape, or as Berge (1998: 451) put it, “Parallel change in pelvic shape between human ontogeny and hominid phylogeny.” In layman’s terms, ‘similar changes in both pelvic growth and pelvis evolution.’

eFfing Fossil Friday: resurrected

June 20, 2014June 20, 2014 / zcofran / 2 Comments

It’s been a quiet month here at Lawnchair, as I’ve just returned from the Rising Star Workshop, taking part in the analysis and description of new hominin remains from South Africa. We’ll have some exciting announcements to make in the near future.

Also, I petted a ferocious, bloodthirsty lion!

To ease back into the Lawnchair, I thought I’d resurrect eFfing Fossil Friday, a short-lived series from when I was collecting data for my dissertation three years ago (speaking of which, a paper related to my dissertation came out in AJPA during the Workshop, as well). A lot has happened since the last installment of FFF, so whose heads will be on the chopping block today?

Crania 9, 15 and 17 (clockwise from top left). Cranium 9 is an early adolescent and the other two are adults - lookit how the facial anatomy changes with age!

Crania #s 9, 15 and 17 (clockwise from top left). Cranium 9 is an early adolescent and the other two are adults – lookit how the facial anatomy changes with age! (Fig. 1 from Arsuaga et al., 2014)

It’s new crania from Sima de los Huesos, Atapuerca! These are published today in the journal Science by Juan L. Arsuaga and colleagues. Sima de los Huesos is a pretty remarkable site in Spain dating to the Middle Pleistocene; the site is probably at least 400,000 years old, and the remains of at least 28 individuals. These specimens show many similarities with Neandertals who later inhabited the area, but don’t have all of the ‘classic’ Neandertal features.

What I like about this figure from the paper is that the comparison of the adolescent (top left) with adults (the other two) shows how the skull changes during growth. The major visible difference is that the face sticks out in front of the brain case more in the adults than the adolescent. As a result, the adolescent lacks a supraorbital torus (“brow ridge”), but this would have developed as the face grew forward and away from the brain. Ontogeny!

Friday excitement: Panoramic data inspection

February 7, 2014February 7, 2014 / zcofran / Leave a comment

I teach Tuesdays and Thursdays this year, leaving Fridays welcomely wide open for non-teaching related productivity. Today’s task is arguably the most exhilarating aspect of doing Science – inspecting raw data to make sure there are no major errors or problems in the dataset, so I can then analyze it and change the world. The excitement is truly hard to contain.

Delectable dog food is the dataset; I’m the dog.

No, it’s not the funnest, but it’s an important part of doing Science. To make your life easier, you should inspect data daily as you collect them. This way, you can identify mistakes and make notes about outliers early on, so that you are not stupefied and stalemated by what you see when you sit down to begin analysis.

You (corgi) are getting ready to analyze and you find an anomalous observation (door stop) you didn’t notice when you were collecting data.

Today I’m looking at measurements I took from ape mandibles housed in an English museum last summer; I inspected data before I left the UK for KZ, so today should be a breeze. But no matter how meticulous you are in the field/museum, you still need to inspect your data before analyzing them, just to be safe. If you’re as disorganized as I am, there will be lots of programs each with lots of windows. Here’s a tip: plug into multiple monitors (or at least one big ass monitor), so you can easily espy all open windows and programs in prodigious panorama.

Using two monitors helps when checking data for errors and patterns. On my left screen I’m using R to visualize and examine the raw data open in Excel on the right screen. If something seems off on the left screen, I can quickly consult the original spreadsheet on the right.

Barely visible in the above screenshot, these are chimpanzee (red) and gorilla (black) mandible measurements plotted against a measure of body size, preliminarily described in this post from last August. I’m looking at whether any mandibular measurements track body size across the subadult growth period, in hopes that bodily growth can be studied in fossil species samples dominated by kid jaws. As you can (barely) see, some jaw measurements correlate with body size better than others, and sometimes the apes follow similar patterns but other times they don’t.

The data look good, so now I can go on to examine relationships between mandible and body size in more detail. Stay tuned for results!

Osteology everywhere: A sign I might have a problem

January 14, 2014January 14, 2014 / zcofran / 2 Comments

Over the holiday break I was working at a cafe, and was shocked to find the upholstery besprinkled with bones. Looking at this seatback, can you tell what kinds of bones, and from whom, adorn this food establishment?

Of course there’s no one right answer, but what I saw were the undeveloped shafts of infant limbs. Infants?! Mildly morbid, mayhap, but one of the distinguishing features of juvenile limb bones compared with adults is that babies’ epiphyses (joint ends) are not fused to the shafts. Observe:

From left to right, human perinatal humerus, femur and tibia (from Scheuer and Black, 2000).

Each of the newborn bones pictured above is comprised of a shaft (diaphysis) that flares proximally and distally into a ‘metaphysis.’ In adults, the epiphyses are completely fused to the metaphyses, but in juveniles the epiphyses are separated from metaphyses by a growth plate made of cartilage. Different epiphyses tend to fuse at characteristic ages, and when fusion occurs bone growth ceases.

Functionally, this cartilage growth plate allows the bones to increase in length, as multiplying cartilage cells are replaced by bone cells. Because the epiphyses of different limbs fuse at different times, this means that limb proportions change subtly over the course of growth. Practically, this means that if an archaeologist (or forensic scientist or paleontologist) finds a limb shaft with unfused ends, he or she can estimate the age at which the individual may have died:

Standards for epiphyseal fusion. Same bones in same order as in previous figure (also from Scheuer and Black, 2000). “A” refers to the age (years) when the epiphysis firsts appears, and “F” to when it fuses to the shaft.

So if we assume the bones in the second figure are from the same person, we see a humerus, femur and tibia with completely unfused epiphyses. If we refer to our aging standards (third figure), we can see that the first epiphysis to fuse is the proximal humerus, between 2-6 years, and the next epiphyses to fuse are the distal humerus and femur head/proximal tibia between 12-14 years. So we could conclude that this poor kid was certainly younger than 12, years, if not even younger than 2 years. Again, having more of the skeleton (especially jaws with developing teeth) would help us make a more precise estimation.

Baby bones all over the place?! Shame on you, Panera.

GET THIS BOOK: Scheuer L and Black S. 2000. Juvenile Developmental Osteology. Academic Press.

Mandible as a measure of overall body size?

August 4, 2013February 2, 2014 / zcofran / 2 Comments

I’m currently in Kent, United Kingdom, examining African ape jaws to follow up on my dissertation research comparing jaw growth in humans and Australopithecus robustus (having a tough time writing this stuff up for journal publication, but hopefully things’ll start coming out soon). One thing I’d assumed (with evidence, of course), was that aspects of mandibular size could serve as a proxy for body size, to make inferences about body growth. Now that I’m in Kent, I’m hoping to get good evidence of this in the non-human African apes.

The Powell Cotton Museum in Kent has an awesome collection of chimpanzees and gorillas (see the Human Origins Database by Adam Gordon and Bernard Wood for more information on these samples). This collection was accumulated during a time last century when explorers would go out and collect specimens from the wild, usually by finding and killing them. Now, when Major Percy Powell-Cotton was out doing this, he or some of his assistants actually collected measurements on some of the corpses – arm span, height, head+body length, and chest girth. This means we can see which aspects of the mandible correlate with body size, which is important since the fossil record usually affords us mandibles more than any other part of the skeleton.

Length of the back of the ramus to the P4, plotted against measures of body size. Colors/shapes represent 1 of 5 dental eruption age groups.

There aren’t body size measurements for all individuals, and I’ve been biasing my own sampling toward subadults. So I only have body size data for up to 15 of the 70+ gorillas I’ve been able to look at. From this meager sample, though, it looks like many aspects of mandible size may well end up correlating with aspects of body size. For instance, the distance from the back of the mandibular ramus to the front of the P4 is highly correlated with all 4 of Powell-Cotton’s bodily measures (right).

Will an expanded sample size uphold these high correlations? Will we see major differences between the sexes, or between different age groups? Will chimpanzees follow the same rules as gorillas? Hopefully I’ll be able to let you know by the time I’m done working in the museum!

Pre-publication: Brain growth in Homo erectus (plus free code!)

April 16, 2013August 4, 2013 / zcofran / 1 Comment

The annual meetings of the American Association of Physical Anthropologists were going on all last week, and I gave my first talk before the Association (co-authored with Jeremy DeSilva). The talk focused on using resampling methods and the abysmal human fossil record to assess whether human-like brain size growth rates were present in our >1 mya ancestor Homo erectus. This is something I’ve actually been sitting on for a while, and wanted to wait til after the talk to post for all to see. I haven’t written this up yet for publication, but before then I’d like to briefly share the results here.

Background: Humans’ large brains are critical for giving us our unique capabilities such as language and culture. We achieve these large (both absolutely, and relative to our body size) brains by having really high brain growth rates across several years; most notable are exceptionally high, “fetal-like” rates during the first 1-2 years of life. Thus, rapid brain growth shortly after birth is a key aspect of human uniqueness – but how ancient is this strategy?

Materials: We can plot brain size at birth in humans and chimpanzees (our closest living relatives) to visualize what makes humans stand out (Figure 1).

Figure 1. Brain size (volume) at given ages. Humans=black, chimpanzees=red. Ranges of brain size at birth, and the chronological age of the Mojokerto fossil, in blue.

Human data come from Cogueugniot and Hublin (2012), and chimpanzees from Herndon et al. (1999) and Neubauer et al. (2012). The earliest fossil evidence able to address this question comes from Homo erectus. Because of the tight relationship between newborn and adult brain size (DeSilva and Lesnik 2008), we can use adult Homo erectus brain volumes (n=10, mean = 916.5 cm^3) to predict that of the species’ newborns: mean = 288.9 cm^3, sd = 17.1). An almost-recent analysis of the Mojokerto Homo erectus infant calvaria suggests a size of 663 cm^3 and an age of 0.5-1.25 years (Coqueugniot et al. 2004; this study actually suggests an oldest age of 1.5 years, but the chimpanzee sample here requires us to limit the study to no more than 1.25 years). Because we have a H. erectus fossil less than 2 years of age, and we can estimate brain size at birth, we can indirectly assess early brain growth in this species.

Methods: Resampling statistics allow inferences about brain growth rates in this extinct species, incorporating the uncertainty in both brain size at birth, and in the chronological age of the Mojokerto fossil. We thus ask of each species, what growth rates are necessary to grow one of the newborn brain sizes to any infant between 0.5-1.25 years? And from there, we compare these resampled growth rates (or rather, ‘pseudo-velocities’) between species – is H. erectus more similar to modern humans or chimpanzees? There are 294 unique newborn-infant comparisons for humans and 240 for the chimpanzee sample. We therefore compare these empirical newborn-infant pairs from extant species to 7500 resampled H. erectus pairs, randomly selecting a newborn H. erectus size based on the parameters above, and randomly selecting an age from 0.5-1.25 years for the Mojokerto specimen. This procedure is used to compare both absolute size change (the difference between an infant and a newborn size, in cm^3/year), and and proportional size change (infant/newborn size).

Results: Humans’ high early brain growth rates after birth are reflected in the ‘pseudovelocity curve’ (Figure 2). Chimps have a similar pattern of faster rates earlier on, but these are ultimately lower than humans’. Using the Mojokerto infant’s brain size (and it’s probable ages) and the likely range of H. erectus neonatal brain sizes (mean = 288, sd = 17), it is fairly clear that H. erectus achieved its infant brain size with high, human-like rates in brain volume increase.

Figure 2. Brain size growth rates (‘pseudo-velocity’) at given ages. Humans=black, chimpanzees=red, and Homo erectus,=blue.

However, if we look at proportional size change, the factor by which brain size increases from birth to a given age, we see a great deal of overlap both between age groups within a species, and between different species. Cross-sectional data create a great deal of overlap in implied proportional size change between ages within a species; it is easier to consider proportional size change between taxa, conflating ages, then (Figure 3). Humans show a massive amount of variation in potential growth rates from birth to 0.5-1.25 years, and chimpanzees also show a great deal of variation, albeit generally lower than in the human sample. Relative growth rates in Homo erectus are intermediate between the two extant species.

Figure 3. Proportional brain size increase (infant/newborn size).

Significance: Brain size growth shortly after birth is critical for humans’ adaptative strategy: growing a large brain requires a lot of energy and parental (especially maternal) investment (Leigh 2004). Plus, in humans this rapid increase may correspond with the creation of innumerable white-matter connections between regions of the brain (Sakai et al. 2012), important for cognition or intelligence. The H. erectus fossil record (1 infant and 10 adults) provides a limited view into this developmental period. However, comparative data on extant animals (e.g. brain sizes from birth to adulthood), coupled with resampling statistics, allow inferences to be made about brain growth rates in H. erectus over 1 million years ago.

Assuming the Mojokerto H. erectus infant is accurately aged (Coqueugniot et al. 2004), and that Homo erectus followed the same neonatal-adult scaling relationship as other apes and monkeys (DeSilva and Lesnik 2008), it is likely that H. erectus had human-like rates of absolute brain size growth. Thus, the energetic and parental requirements to raise such brainy babies, seen in modern humans, may have been present in Homo erectus some 1.5 million years ago or so. This may also imply rapid white-matter proliferation (i.e. neural connections) in this species, suggesting an intellectually (i.e. socially or linguistically) stimulating infancy and childhood in this species. At the same time, relative brain size growth appears to scale with overall brain size: larger brains require proportionally higher growth rates. This is in line with studies suggesting that in many ways, the human brain is a scaled-up version of other primates’ (e.g. Herculano-Houzel 2012).

This study was made possible with published data, and the free statistical programming language R.

Contact me if you want the R code used for this analysis, I’m glad to share it!!!

References
Coqueugniot H, Hublin JJ, Veillon F, Houët F, & Jacob T (2004). Early brain growth in Homo erectus and implications for cognitive ability. Nature, 431 (7006), 299-302 PMID: 15372030

Coqueugniot H, & Hublin JJ (2012). Age-related changes of digital endocranial volume during human ontogeny: results from an osteological reference collection. American journal of physical anthropology, 147 (2), 312-8 PMID: 22190338

DeSilva JM, & Lesnik JJ (2008). Brain size at birth throughout human evolution: a new method for estimating neonatal brain size in hominins. Journal of human evolution, 55 (6), 1064-74 PMID: 18789811

Herculano-Houzel S (2012). The remarkable, yet not extraordinary, human brain as a scaled-up primate brain and its associated cost. Proceedings of the National Academy of Sciences of the United States of America, 109 Suppl 1, 10661-8 PMID: 22723358

Herndon JG, Tigges J, Anderson DC, Klumpp SA, & McClure HM (1999). Brain weight throughout the life span of the chimpanzee. The Journal of comparative neurology, 409 (4), 567-72 PMID: 10376740

Leigh SR (2004). Brain growth, life history, and cognition in primate and human evolution. American journal of primatology, 62 (3), 139-64 PMID: 15027089

Neubauer, S., Gunz, P., Schwarz, U., Hublin, J., & Boesch, C. (2012). Brief communication: Endocranial volumes in an ontogenetic sample of chimpanzees from the taï forest national park, ivory coast American Journal of Physical Anthropology, 147 (2), 319-325 DOI: 10.1002/ajpa.21641

Sakai T, Matsui M, Mikami A, Malkova L, Hamada Y, Tomonaga M, Suzuki J, Tanaka M, Miyabe-Nishiwaki T, Makishima H, Nakatsukasa M, & Matsuzawa T (2012). Developmental patterns of chimpanzee cerebral tissues provide important clues for understanding the remarkable enlargement of the human brain. Proceedings. Biological sciences / The Royal Society, 280 (1753) PMID: 23256194

Avoid the Noid… I mean Noise

March 27, 2012August 4, 2013 / zcofran / Leave a comment

As alluded to yesterday, my dissertation compares growth in an extinct animal with growth in living humans; this study is necessarily cross-sectional, meaning that it examines individuals at a single point in time. Alternatively, longitudinal data sample individuals from several points in time. So for instance if I constructed a growth curve by measuring the stature of a bunch of people of different ages in just a day, that would be cross-sectional. But if I had the time and wherewithal to measure some people’s heights once a year from birth to adulthood, well that’d be longitudinal. Cross-sectional data lack the resolution of longitudinal data, whereas longitudinal data can be prohibitively difficult to collect (such as in long-lived, slow-maturing animals like humans, or in extinct animals like Australopithecus robustus).

Some researchers abhor cross-sectional data, pointing out that the intricacies of individuals’ longitudinal growth will not be adequately captured in with cross-sectionally. American anthropology founder Franz Boas himself discussed this in a paper nearly 82 years ago. Anyway, I was reminded of this dichotomy today when perusing a paper that examined longitudinal brain activity in a cohort of adolescent kids (right, from Campbell et al. in press). The mess of jagged lines are individuals’ measurements from age 9-18, and the smoothed blue and red curves are the cross-sectionalized curves calculated from these kids. Oy, look at all that variation and caprice that gets left out in the cross-sectionalized curves!

Of course, this doesn’t mean that we should never use cross-sectional data to study growth – like I’d mentioned above, the fossil record necessitates a cross-sectional approach to the study of growth. As always, you have to understand and acknowledge the limits of your data.

Read on
Boas, F. (1930). OBSERVATIONS ON THE GROWTH OF CHILDREN Science, 72 (1854), 44-48 DOI: 10.1126/science.72.1854.44

Campbell, I., Grimm, K., de Bie, E., & Feinberg, I. (2012). Sex, puberty, and the timing of sleep EEG measured adolescent brain maturation Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1120860109

Updated note on jaw growth in Australopithecus robustus

November 26, 2011August 4, 2013 / zcofran / 1 Comment

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

Data, development and diets

October 23, 2011August 4, 2013 / zcofran / 2 Comments

As mentioned briefly but repeatedly on this blog, my dissertation is about growth of the lower jaw in Australopithecus robustus (right), comparing it with jaw growth in recent humans. This is important because we don’t really know exactly how skeletal-dental (especially skeletal) maturation of our fossil relatives compares with us today. From a developmental perspective, it is also important to know how and when adult form arises during growth, and how these processes vary within and between species.

It’s not easy to examine ontogeny in fossil samples. In a post a few weeks ago I included a drawing of some of the A. robustus juvenile jaws. At the time, I was pointing out variation in dental maturity (which is a nice thing when studying growth), but the picture also reveals a bigger bugbear – variable preservation of features (which is a terrible thing if you’re trying to study growth).

For example, the youngest individual in the fossil sample (right, viewed from above, front is at the top of the picture) includes only the second baby molar tooth, a bit of the bone surrounding the sides and back of the tooth, and a small portion of the ascending ramus. The oldest subadult in the sample (SKW 5), on the other hand, is almost entirely complete. In between these ages, jaws variously preserve different parts. Under these circumstances (i.e. lots of missing data), growth cannot be studied by traditional (namely, multivariate) methods (how I will deal with this is a topic for another day).

So while studying the fossils in South Africa, in order to maximize the number of comparisons I could possibly make, I measured just about every single linear dimension conceivable on these jaws. I thus have a spreadsheet with 300 columns of measurements I could take on each specimen. Most of the cells are empty : (

What’s a boy to do?! In order to compare A. robustus with humans, I need to take the same measurements on a growth series of human jaws, too. But life is short, and if I want to finish this project before I succumb to some sinister signature of senescence, I really can’t take hundreds of measurements on a human sample which is much larger than the fossils. Plus, a lot of the individual measurements are a bit redundant: some of the distances overlap, many of the variables can be taken on the right and the left sides, etc.

If I am to finish collecting data in a reasonable time frame, I need to cull my variables from 300 to however many (a) maximizes the comparisons I can make within the less-complete A. robustus sample, and (b) are not too repetitive. Boo. Plus I have to get these spreadsheets ready to be read and analyzed in the program R, which for whatever reason is always a pain in the ass.

Again, the statistics of the overall comparisons is a topic for another day, and I haven’t had the opportunity yet to write the analytical program(s). But I have looked at some individual traits in A. robustus compared with a subsample of humans. For example, at the left is a plot of changes in height of the jaw at the baby second molar or adult second premolar (which replaces the baby molar). Obviously my human sample is way to small at the moment to make any really meaningful statements about how growth compares between the two species. Note also that these are absolute measures and not size-corrected, and that these are stages of dental eruption rather than chronological ages. But from this preliminary view, the two species are very similar up to around when the first adult molar comes in (“stage 4” here). Thereafter, the A. robustus individuals dramatically increase in size rather fast, whereas humans only slowly increase in size.

Again, this is a very preliminary result, and only for a single measurement. But it is interesting in light of a recent study by Megan Holmes and Christopher Ruff (2011). These researchers compared jaw growth recent humans who differed in the consistency of their diets. They found that kids in the two populations were not too different, but the samples became more different with age to become fairly different as adults. Now, A. robustus seems to have eaten a diet with lots of hard objects (see recent review by Peter Ungar and Matt Spohneimer), but humans’ diet (and technology) really obviates the need for chewing as powerful as seen in A. robustus. So this dietary divergence may well be reflected in the growth difference suggested above, but it may not be the sole factor. PLUS I NEED TO INCREASE MY HUMAN SAMPLE.

Stay tuned for more analyses and results!

References to make you smarter and stronger
Holmes, M., & Ruff, C. (2011). Dietary effects on development of the human mandibular corpus American Journal of Physical Anthropology, 145 (4), 615-628 DOI: 10.1002/ajpa.21554

Ungar, P., & Sponheimer, M. (2011) The Diets of Early Hominins. Science 334(6053), 190-193. DOI: 10.1126/science.1207701

Lawn Chair Anthropology

Biological anthropology, paleontology, evolution, and development, by Dr. Zachary Cofran

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