Can ‘ape-like’ actually be ‘human-like’?

I’m reading up on life history in Homo erectus for a few projects I’m working on, and something’s just caught my eye. A 2012 issue of Current Anthropology presents a series of papers from the 2011 symposium, “Human Biology and the Origins of Homo.” This issue is full of great stuff, and to top it all off, it can be accessed online for free! (here’s the JSTOR link)

Gary Schwartz has a paper here recounting what is known (or as he stresses, what is still largely unknown) about growth and life history in early Homo. Dental evidence accumulated over the past 30 years has pointed to a rapid (ape-like) life cycle for fossil hominins, in comparison with a slow, long and drawn out human pattern. But much of the evidence against a human-like pattern is somewhat indirect. For instance, Holly Smith (1991) has shown that there’s a pretty tight relationship between brain size and age at first molar (M1) eruption in Primates:

M1 crancap

Fig. 1 from Schwartz (2012). “Bivariate plot of ln M1 emergence age in months (y) versus ln cranial capacity in cubic centimeters (x) for a sample of anthropoids.” The hominins and humans are the open shapes, to which I’ve visually fitted the red line.

It’s a very high correlation (r=0.98). This means that armed with simply an animal’s cranial capacity, which is fairly easy to estimate given complete enough fossils, one can estimate with a bit of confidence its likely age range for M1 emergence. With brain sizes between apes’ and ours, fossil hominins can be estimated to have erupted their M1s at younger ages than us. Many subsequent studies of tooth formation, based on the microscopic remnants of tooth development, have supported these inferences. So presumably, faster, ape-like dental development could be extrapolated to mean ape-like body growth rates and other aspects of life history as well.

But although this is a tight relationship, there are deviations. As Schwartz notes in the article, and others have noted before, high correlations found when examining large interspecific groups (e.g., primates as a whole) often break down when the focus is on smaller groups of more closely related species (e.g., just apes). Based on the relationship figured above, humans are expected to erupt M1 around 7 years of age, but nearly all humans erupt M1 closer to 6 years (hence the open diamond for humans is below the regression line). What hominins appear to share in common with humans is a younger age at M1 eruption than expected for primates of their brain sizes (the red line I’ve added to the figure).

Hominins’ faster dental development and eruption may be ape-like in absolute terms, but eruption ages may be human-like when their brain size is taken to account. As with many life history variables, the significance of this similarity (if anything) is difficult to ascertain.

eFfing Fossil Friday: Frozen Femur

A 45,000 year old human femur from Siberia provides new information about genetic mutation rates and modern human origins. As Quiaomei Fu and colleagues report in this week’s issue of Nature, this seemingly simple leg bone carries so much information, not because of its gross anatomy, but because of the ancient DNA it preserves.

The femur wasn’t discovered by paleontologists, but by an artist/historian looking for fossils around the Irtysh River. The bone came from from a site called Ust’-Ishim, only some 650 km north of the snowy capital where I work in Kazakhstan:

Ust'-Ishim

The site in question, Ust’-Ishim is marked by the yellow star. The red and blue sites to the southeast are other Upper Paleolithic sites. Okladnikov (3) and Denisova (4) have also yielded fossils preserving ancient DNA. Modified from Fu et al. figure 1.

The bone was directly radiocarbon dated to around 45,000 years ago. With a fairly precise age of the bone, Fu et al. could estimate the rate at which genetic mutations arise, by counting the number of new mutations in recent humans that aren’t shared by the Ust’-Ishim femur. This led to an estimate of around 0.43×10−9  new mutations per site per year. This is a relatively low rate compared to estimates based on geologically older fossils, but consistent with more recent estimates that directly compare parents and offspring.

The Ust’-Ishim individual had levels of Neandertal ancestry comparable to living Eurasians (~2.3% of the genome), but there is no evidence of any Denisovan ancestry. Because this individual lived closer to the date of modern-Neandertal admixture, the Neandertal segments of its genome are longer than in modern people (recombination over generations breaks these regions apart into shorter segments). Knowing about recombination rates, Fu et al. could infer that admixture between Neandertal and modern human populations occurred between 50-60,000 years ago.

This eFfing Friday fossil provides more tantalizing evidence for DNA-bearing human fossils just across the Kazakhstan border. With Ust’-Ishim to the north, Denisova and Okladnikov caves to the east, and Teshik Tash to the south, my colleagues and I are very keen to find similar sites here on the KZ side.

Reference: Fu et al. 2014. Genome sequence of a 45,000-year-old modern human from Siberia. Nature 514: 445–449. doi:10.1038/nature13810.

Osteology everywhere: Pollicem verte(b)r(a)e [Latin puns are hard]

I just got back from the meetings of the European Society for the Study of Human Evolution in Florence. As you can guess, bones and genes and anatomy and apes and biomechanics and energetics and everything were on everyone’s minds. Even in the midst of an unseasonal surprise typhoon of lunch time ice:

Ambush of hail.

Aw hail no.

Along the way, I passed a gift shop window and this book cover immediately caught my eye:helert

No, it’s not an ancient Roman gladiator’s helmet. It’s clearly a lumbar vertebra, probably of some quadruped. We’re looking down onto the top (or front of it) from the cranial view. The body or centrum is the rounded part toward the bottom of the picture, the short transverse processes jutting off to the sides. The spinous process, pointing toward the top, is even thick and blunt distally as is characteristic of lumbar verts. Here’s a comparison:

Middle lumbar vertebrae, from the cranial view (modified from Figs. 3-4 of Moyà-Solà et al., 2004). 0=modern baboon, A=Proconsul nyanzae (KNM-MW 13142-J)(B) P. catalaunicus (IPS-21350.59). (C) Cast of Morotopithecus bishopi (UPM 67.28) from Moroto (Uganda). (D) D. laietanus (IPS-18000) from Can Llobateres (Spain). (E) Pongo pygmaeus

Middle lumbar vertebrae of various Miocene apes (A-D) in cranial view (modified from Figs. 3-4 of Moyà-Solà et al., 2004). 0=modern baboon, A=Proconsul nyanzae (KNM-MW 13142-J), B=Pierolapithecus catalaunicus (IPS-21350.59), C=Morotopithecus bishopi (UPM 67.28), D=Hispanopithecus laietanus (IPS-18000), and E= modern orangutan.

Modern apes use an upright posture more frequently than living monkeys, who are quadrupedal. An anatomical correlate of these postures is the position of the transverse processes. Compare the baboon (0 in the figure above) with the orangutan (E). In the monkey the transverse processes come off the sides of the centrum (below the horizontal line), while in the orangutan the processes come off the pedicle further back. In your lumbars the transverse processes arise a little bit more toward the back than in the orangutan.

This is a pretty characteristic pattern, meaning that we can reconstruct the habitual posture of an animal based on a single bone – even just part of a single bone as in the case of Hispanopithecus (D, above). Proconsul nyanzae (A), dating to around 19 million years ago and therefore one of the earliest apes, has a monkey-like lumbar vert; the rest of its skeleton is monkey-like and so we think many of the earliest apes moved around like modern monkeys. In contrast, Morotopithecus bishopi (C), at 20.6 million years ago, is also one of the earliest apes but has a more modern-ape-like lumbar. And so with Pierolapithecus and Hispanopithecus.

The vertebra gracing the cover of our gift shop book is clearly more monkey-like, presumably from a simian who long ago walked on all fours across the blood-soaked floors of a cacophonous Colosseum.

My ESHE poster is Gona blow your mind

I’m in Italy for the annual meeting of the European Society for the Study of Human Evolution. It’s been a great conference, seeing interesting talks (check out #eshe2014 on Twitter), meeting old friends and meeting new ones, and enjoying excellent food and espresso. Here’s the poster I presented yesterday (download pdf):Screen Shot 2014-09-20 at 9.33.38 AM

It’s a follow-up to posts here and here. The long and short of it is, there was a substantial amount of body size variation (i.e., between males and females) in Homo erectus, on par with levels seen in modern day gorillas. This is interesting because H. erectus brain size (and brain size growth) would have required massive amounts of energy, so some have hypothesized a cooperative breeding strategy; sexually dimorphic species generally do not engage in such cooperative behavior. So I suggest that body size variation in H. erectus is an ecological strategy, with small female body size reducing the metabolic burden on mothers.

Osteology Everywhere: Literally

Last weekend, Kazakhstan celebrated Constitution Day. Rather than stick around for the festivities in the florid Capital city, some friends and I ventured out West to Mangystau, to the deserts flanking the Caspian Sea. Although much of the area is sprawling, barren desert, it’s geologically much more interesting than my home here in the White Tomb.

2014-08-30 17.31.29

A perfect camping spot here on Mars.

The purpose of the trip was ostensibly holiday, but in landscapes such as this my field training kicks in. While I made sure to take in the scenic views, my gaze was mostly directed downward, as on survey, in search for bones, lithics and other signs of paleontological promise.

One thing about Life is that it teems. I don’t mean the obvious, ubiquitous microbes or infinitesimal infestations on all our faces. Even the big stuff can thrive, even in seemingly inhospitable places.

This little buddy wants nothing to do with everything.

This curmudgeon puts the ‘turd’ in ‘turtle.’

Some buddies on their way to work.

These buddies are on their way to an important meeting at the office.

But what goes up must come down, the only promise is The End. As a result of this shared fate, many of the landscapes we encountered were literally littered with the bony remnants previous denizens. Sun-scorched and bleached, the calling cards of Tetrapods stuck out like sore thumbs among the dirt and scrub.

Hip off the old block.

Hip off the old block.

A horse doing its best impression of SK 46.

A horse doing a good impression of SK 46.

Mangystau boasts an embarrassment of turtle bones and shells.

Mangystau boasts an embarrassment of turtle bones and shells.

A small, noble beast.

Alas, this was a noble little buddy.

I will admit I have no idea what animal this comes from, but I would guess some small mammal. If you know, please tell!

I will admit I have no idea what animal this comes from, but I would guess some small mammal. If you know, please tell me.

But this surface smorgasbord of bones will not translate into a future fossil festival. Sitting on the surface, bones like these are likely to be scattered, trampled, disturbed by anthropology nerds. Most will not get the chance to sink into the Earth, soak up leaching minerals, and lie in wait for paleontologists of the future. In desert landscapes such as in Mangystau, ‘osteology everywhere’ is an ephemeral description.

A picture is worth a thousand datapoints in #rstats

I’m finally about to push my study of brain growth in H. erectus out of the gate, and one of the finishing touches was to make pretty pretty pictures. Recall from the last post on the subject that I was resampling pairs of specimens to compute how much proportional brain size change (PSC) occurred from birth a given age in humans and chimpanzees (and now gorillas). This resulted in lots of data points, which can be a bit difficult to read and interpret when plotted. Ah, cross-sectional data. “HOW?!” I asked, “HOW CAN I MAKE THIS MORE DIGESTIBLE?” Having nice and clean plots is useful regardless of what you study, so here I’ll outline some solutions to this problem. (If you want to figure this out for yourself, here are the raw resampled data. Save it as a .csv file and load it into R)

All

Ratios of proportional size change from birth to a later age. Black/gray=humans, green=chimpanzees, red=gorillas. Left are all 2000 resampled ratios, center shows the medians (solid lines) and 95% quantiles of the ratios for each species at a given age (the small gorilla sample is still data points), and right are the loess regression lines and (shaded) 95% confidence intervals. Blue lines across all three plots are the H. erectus median (solid) and 95% quantiles (dashed).

The left-most plot above shows the raw resampled ratios: you can see a lot of overlap between humans (black), chimpanzees (green) and gorillas (red). But all those points are a bit confusing: just how extensive is the overlap? What is the central tendency of each species?

The second plot shows a less noisy way of displaying the results. We can highlight the central tendencies by plotting PSC medians for each age (I used medians and not means since the data are not normally distributed), and rather than showing the full range of variation in PSC at each age, we can simply highlight the majority (95%) of the values.

To make such a plot in R, for each species you need four pieces of information, in vector form: 1) the unique (non-repeated) ages sorted from smallest to largest, and the 2) median, 3) upper 97.5% quantile, and 4) lower 0.025% quantile for each unique age. You can quickly and easily create these vectors using R‘s built-in commands:

R codes to create the vectors of points to be plotted in the second graph. Note that vectors are not created for gorillas because the sample size is too small, or for H. erectus because the distribution is basically the same across all ages.

R codes to create the vectors of points to be plotted in the second graph. Note that vectors are not created for gorillas because the sample size is too small, or for H. erectus because the distribution is basically the same across all ages.

With these simple vectors summarizing humans and chimpanzees variation across ages, you’re ready to plot. The medians (hpm and ppm in the code above) can simply be plotted against age using the plot() and lines() functions, simple enough. But the shaded-in 95% quantiles have to be made using the polygon() function, which creates a shape (a polygon) by connecting sets of points that have to be entered confusingly: two sets of x-coordinates with the first in normal order and the second reversed, and two sets of y-coordinates with the first in normal order and the second reversed.

Plot yourself down and have a beer.

Plot yourself down and have a beer.

In our case, the first set of x coordinates is the vector of sorted, unique ages (h and p in the code), and the second set is the same vector but in reverse. The first set of y coordinates is the vector of 97.5% quantiles (hpu and ppu), and the second set is the vector of 0.025% quantiles in reverse. You can play around with ranges of colors and transparency with “col=….”

What I like about the second plot is that it clearly summarizes the ranges of variation for humans and chimps, and highlights which parts of the ranges overlap: the human and ape medians are comparable at the youngest ages, but by 6 months the human median is pretty much always above the chimpanzee upper range. The gorilla points are generally close to the chimpanzee median until around 2 years after which gorilla size increase basically stops but chimpanzees continue. Importantly, we can also see at what ages the simulated H. erectus values are most similar to the empirical species values, and when they fall out of species’ ranges. As I pointed out a bajillion years ago, the H. erectus values (based on the Mojokerto juvenile fossil) encompass most living species’ values around six months to two years.

I also like that second plot does all the above, and still honestly shows the jagged messiness that comes with cross-sectional, resampled data. Of course no individual’s proportional brain size increases and decreases so haphazardly during growth as depicted in the plot. It’s ugly but it’s honest. But if you like lying to yourself about the nature of your data, if you prefer curvy, smoothed inference to harsh, gritty reality, you can resort to the third plot above: the loess regression lines calculated from the resampled data.

Loess and lowess (not to be confused with loess) refer to locally weighted regression scatterplot smoothing, a way to model gross data like we have, but with a nice and smooth (but not straight) line. Because R is awesome, it has a loess() function built right in. The function easily does the math, and you can quickly obtain confidence intervals for the modelled line, but plotting these is another story. After scouring the internet, coding and failing (repeatedly) I finally came up with this:

Screen Shot 2014-07-26 at 6.57.01 PM

Creating vectors of points makes your lines clean and smooth.

If you simply try to plot a loess() line based on 1000s of unordered points, you’ll get a harrowing spider’s web of lines between all the points. Instead, you need to create ordered vectors of the non-repeated modelled points (hlm, plm, glm, above) and their upper and lower confidence limits. Once modelled, you can simply plot the lines and create polygons based on the confidence intervals as above.

The best way to learn to do stuff in R is to just play around with data and code until you figure out how to do whatever it is you have in mind. If you want to recreate, or alter, what I’ve described here, you can download the resampled data (link at the beginning of the post) and R code. Good luck!

eFfing Fossil Friday: Feathers & Ink

I’ve been traveling here and there lately, so I’ve missed a fortnight’s FFFs. So to atone, this post is a threefer.

Last week I was visiting my family in Kansas City, and was debating whether to get a badass dinosaur tattoo. Right on cue, the cover of last week’s Nature featured this feathery friend (right): the 11th Archaeopteryx skeleton. From the previous 10 skeletons, we know that this 150 million year old dinosaur had feathers on its upper limbs and tail. But this new specimen from China, described by Foth and colleagues, also has plush pennaceous plumage bedazzling its neck, lower legs and feet. So decked in down, this new fossil suggests that Archaeopteryx and other dinos originally evolved feathers for some function besides flight, such as social displays (some living birds have taken this to ridiculous extremes). Later species of winged theropods (i.e., birds) eventually adapted feathers for flying (the concept of exaptation).

Also, this closeup, under ultraviolet light, of the specimen’s wing (impressions) and phalanges shows how badass and clawed birds used to be. They just don’t make them like they used to.

Extended Data Fig. 4a-b from Foth et al., 2014.

Taking this Nature cover as a sign, I went ahead and got a different fossil permanently etched somewhere on my person:

Fig. 1a from Rauhut et al., 2012.

This, as described in the title of the 2012 paper, is an “exceptionally preserved juvenile” of the dinosaur species Sciurumimus albersdoerferi. This little buddy is one of the most complete dinosaur skeletons in existence, and even preserves some skin and “protofeathers” (not as full and feathery as in the Archaeopteryx described above). And that little bar beneath the lower jaw is the hyoid bone. THEY HAVE ITS HYOID! If only more hominin fossil juveniles were so well preserved (and badass).

Finally, although CNN is usually insufferable, Thursday they reported that more than 18 dinosaur skeletons that had been smuggled out of Mongolia and into the U.S. have been returned to where they belong. The coverage doesn’t really get into it, but for me this highlights a major paleontological problem – private collectors (and often a black market) make scientifically important fossils unavailable to researchers (many of the Mongolian fossils were very complete skeletons). Fossils are the only direct evidence of life in the past (would you ever believe that this was a real animal if there wasn’t physical evidence?), so the theft and private trade of such important evidence is problematic. This hit home in paleoanthropology with the announcement of Darwinius masillae five years ago (the fossil was purchased for scientific study for a large sum of money). I don’t know what the Mongolian government will do with their returned fossils, but their repatriation is probably good for paleontologists.