Yi qi: Another fossil from The Dark Crystal

It was a good week for weird dinosaurs. On Monday scientists published Chilesaurus, “an enigmatic plant-eating [dino] from the Late Jurassic period of Chile” (from the paper title). Even more curious, Xing Xu and colleagues announced Yi qi, a Skeksis-like nightmare from the Jurassic of what is now China.

Yi qi on its deathbed, refusing to go quietly.

Here’s the fossil itself:

The Yi qi partial skeleton (Figure 1 from Xu et al.). Inset c is a closeup of the skull, and e a closeup of the elongated finger bones on the right side. Lookit that majestic mane of feathers flowing from the back of its head and down its neck.

The Yi qi partial skeleton (Figure 1 from Xu et al.). Inset c is a closeup of the skull, and e a closeup of the elongated finger bones. Lookit that majestic mane of feathers flowing from the back of its head and down its neck.

Yi qi is Mandarin for “strange wing.” Why “strange”? Here’s the cleaned up schematic of the fossil above:

The rest of Figure 1 from Xu et al. Important for flight are the structures labeled "ldm4/rdm4" and "lse/rse."

The rest of Figure 1 from Xu et al. Key wing structures are labeled “ldm4/rdm4″ and “lse/rse.” Light gray shading represents feathers in the fossil, while dark gray appears to be some sort of membrane.

The right side of the figure, depicting the left side of this monster, shows the wing anatomy nicely. Bones with “md,” for “manual digit,” in the label are the homologues (or anatomical equivalents) of your fingers. Notice that the fourth one (“ldm4″) is drastically longer than other digits. This alone suggests some special function for this digit. Emanating from the wrist is another structure, “lse,” for “left styliform element.” In anatomy, “styl-” refers to a structure that sticks out; your skeleton is littered with “styloid processes.” Unlike digits, which are a line of several bones (“phalanges”), this styliform element is a single, rod-like structure made of bone. If you look at the “rse” above, beneath it you’ll see a dark patch running its length, which the researchers identified as “sheet-like soft tissue,” or membrane. These membranes are also found by the elongated md4s.

This all indicates an animal with a thin membrane (kind of like skin, I suppose?) between elongated fourth digits, styliform elements, and probably other parts of the body. Researchers then use the comparative anatomy to reconstruct and interpret the function of this unique wing. Here’s what homologous structures look like in flying animals:

Extended Data Figure 8 from Xu et al. Comparison of the wing structure of different flying/gliding animals.

Extended Data Figure 8 from Xu et al. Comparison of the wing structure of different flying/gliding animals. The yellow segment is the styliform element. Note it comes from the wrist in Yi qi and the Japanese giant flying squirrel, but from the ankle in the bat. Birds and pterosaurs apparently lacked such an accessory structure.

Although media generally report this animal’s wings were like bats’, the authors point out that the placement of this styliform element, at the base of the wrist, is actually most comparable to the Japanese giant flying squirrel (Petaurista leucogenys). Nevertheless, the the construction of the wing, with a membrane between long finger elements, is unlike the wings that other dinosaurs and later birds evolved for flight. This highlights the many ways that flight has evolved – independently – in different kinds of vertebrates over the past 200 million years.

Now, even though these were not giant animals, I think they still would have been terrifying. Not scary in the same way as building-sized theropods like T. rex, 

or Spinosaurus.

No, there is just something a bit creepy about a creature like this. Here is the skeletal reconstruction from the paper:

The dinosaur version of Edward Scissorhands.

Like a dinosaur Edward Scissorhands.

If Yi qi Scissorhands doesn’t drive home just how nightmarish this dinosaur was to behold, check out this uncanny resemblance:

YiQiSkeksis

Yi qi (top) and an Skeksis (bottom). Not the first time The Dark Crystal has predicted important fossils.

Yet again, paleontology shows that fact can be stranger than fiction.

Virtual paleontology activity

Last week Nazarbayev University hosted an Instructional Technology Showcase, in which professors demonstrated some of the ways we use technology in the classroom. This was the perfect venue to show off the sweet skeletal stuff we study in Biological Anthropology, through the use of pretty “virtual” fossils. In the past year I’ve started using CT and laser scans of skeletal remains to make lab activities in a few classes (I’ve posted two here and here). Such virtual specimens are especially useful since it is hard to get skeletal materials and casts of fossils here in the middle of the Steppe. These scans are pretty accurate, and what’s more, 3D printing technology has advanced such that physical copies of surface scans can be created from these virtual models. So for the Showcase, I had a table where passersby could try their hand at measuring fossils both in hand and in silico.

Lower jaw of an infant Australopithecus boisei (KNM ER 1477). Left is the plastic cast printed from the laser scan on the right.

Lower jaw of an infant Australopithecus boisei (KNM ER 1477). Left is the plastic cast printed from the laser scan on the right.

The Robotics Department over in the School of Science and Technology was kind enough to print out two fossils: KNM ER 1477, an infant Australopithecus boisei mandible, and KNM KP 271 a distal humerus of Australopithecus anamensis. They used a UP Plus 2 printer, a small desktop printer that basically stacks layers of melted plastic to create 3D models; they said it took about 9 hours to print the pair. Before the Showcase, I measured the computer and printed models on my own for comparison with published measurements taken on the original fossils (KP 271 from Patterson and Howells, 1967; ER 1477 from Wood, 1991). The virtual fossils were measured using the free program Meshlab, while basic sliding calipers were used to measure the printed casts.

I was pleasantly surprised at how similar my measurements were to the published values (usually within 0.1 mm), since it means that the free fossil scans provided by the National Museums of Kenya are useful not only for teaching, but potentially also for research.

The Virtual Paleontology Lab

The Virtual Paleontology Lab. The Kanapoi distal humerus is held in the foreground while the A. bosei jaw rests on the table. Yes, those are real palm trees.

Knowing that these models are pretty true to life (well, true to death, since they’re fossils), I was curious how students, faculty and staff would do. I picked two fairly simple measurements for each fossil. None of the people that came by to participate had any experience with bones or fossils, or measuring these in person or on a computer. Here are their results:

Boxplots showing participants' data, for two measurements on each of the fossils. The blue stars mark the published values. The red rugs on either side indicate measurements taken on the scans (left side) or printed casts (right).

Boxplots showing participants’ data, for two measurements on each of the fossils. The blue stars mark the published values. The red rugs on either side indicate measurements taken on the scans (left side) or printed casts (right).

For the most part, the inexperienced participants’ measurements are not too far off from the published values. There’s not really an apparent tendency for either cast or computer measurements to be more accurate, although measurements of the Kanapoi humerus are closer than the computer measurements (third and fourth boxes above). In my personal opinion, nothing beats handling fossils (or casts of them) directly, but this little activity suggests students can still make reliable observations using 3D scans on a computer.

Sweet free stuff:
Meshlab software
3D scans of fossils from the National Museums of Kenya

Brain size growth in wild and captive chimpanzees

I’m back in Astana, overcoming jet lag, after the annual conference of the American Association of Physical Anthropologists, which was held in my home state of Missouri. I’d forgotten how popular ranch dressing and shredded cheese is out there; but hey, at least you can drink the tap water! It was also nice to be immersed in a culture of evolution, primates and fossils, something so far lacking at the nascent NU.

Although I usually present in evolution and fossil-focused sessions, my recent interest in brain growth landed me in a session devoted to Primate Life History this year. The publication of endocranial volumes (ECVs) from wild chimpanzees of known age from Taï Forest (Neubauer et al., 2012) led me to ask whether this cross-sectional sample displays the same pattern of size change as seen in captive chimpanzee brain masses (Herndon et al., 1999). These are unique datasets because precise ages are known for each individual, and this information is generally lacking for most skeletal populations. We therefore have a unique opportunity to estimate patterns and rates of growth, and to compare different populations. Here are the data up to age 25 (the oldest known age of the wild chimps):

fig2 raw data copy

Brain size plotted against age in chimpanzees. Blue Ys are the Yerkes (captive) apes and green Ts are the Taï (wild) chimps. Note that Yerkes data are brain masses while the Taï data are endocranial volumes (ECVs). Mass and volume – as different as apples and oranges, or as oranges and tangerines? Note the relatively high “Y” at 1.25 years, who was omitted from the subsequent analysis.

This is an interesting comparison for a few reasons. First, to the best of my knowledge brain size growth hasn’t been compared between chimp populations (although it has been compared between chimps and bonobos: Durrleman et al., 2012). Second, many studies have found differences in tooth eruption, maturation and skeletal growth and development between wild and captive animals, but again I don’t think this has been examined for brain growth. Finally, and most fundamentally, it’s not clear whether ECV and brain mass follow the same basic pattern of change (brain mass but not ECV is known to decrease at older ages in humans and chimps, but at younger ages…?.

So to first make the datasets comparable, I used published data to examine the relationship between brain mass and ECV in primates, to estimate the likely ECV of the Yerkes brain masses. Two datasets examine adult brain size across different primate species (red and blue in the plot below), and one looks at brain mass and ECV of individuals for a combined sample of gorillas (McFarlin et al., 2013) and seals (Eisert et al., 2013). In short, ECV and brain mass in these datasets give regression slopes not significantly different from 1. One dataset has a negative y-intercept significantly different from 0, meaning that ECV should actually be slightly less than brain mass, but I think this pattern is driven by the really small-brained animals like New World Monkeys).

Untitled

The relationship between endocranial volume and brain mass in primates (and Weddell seals). Solid lines and shaded confidence intervals are given for each regression, and the dashed line represents isometry, or a 1:1 relationship (ECV=brain mass). The rug at the bottom shows the range of the Yerkes masses. Note that the red and black regressions are not significantly different from isometry, while the blue regression is shifted slightly below isometry.

So let’s assume for now that the ECVs of the Yerkes apes are the same as their masses, meaning the two datasets are directly comparable. There are lots of ways to mathematically model growth, and as George Box famously quipped, “All models are wrong, but some are useful.” Here, I wanted to use something that explained the greatest amount of ontogenetic variation in ECV while also levelling off once adult brain size was reached (by 5 years based on visual inspection of the first plot above). This led me to the B-spline. With some tinkering I found that having two knots, one between each 0.1-2.5 and 2.6-5, provided models that fit the data pretty well, and I resampled knot combinations to find the best fit for each dataset. The result:

B-splines describing the relationship between ECV (or brain mass) and age in the TaÏ (green) and Yerkes (blue) data. Although resampling identified different knots for each sample, the regression coefficients are not significantly different.

B-splines describing the relationship between ECV (or brain mass) and age in the TaÏ (green) and Yerkes (blue) data. Note that although the Yerkes line is elevated above the Taï line after 4 years, the confidence intervals (shaded regions) overlap at all ages.

These models fit the data pretty well (r-squared >0.90), and nicely capture the major changes in growth rates. Resampling knot positions reveals best-fit models with different knots for each sample, but otherwise the two models cannot be statistically distinguished from one another: the 95% confidence intervals of both the model coefficients and brain size estimates overlap. So statistical modelling of brain growth in these samples suggests they’re the same, but there are some hints of difference.

Growth rates at each age calculated from the B-spline regressions. Note these are arithmetic velocities and not first derivatives of the growth curves.

Growth rates at each age calculated from the B-spline regressions. Note these are arithmetic velocities and not first derivatives of the growth curves. The dashed horizontal line at 0 indicates the end of brain size growth.

Converting the growth curves to arithmetic velocities we see what accounts for the subtle differences between samples. The velocity plot hints that, in these cross-sectional data, brain size increases rapidly after birth but growth slows down and ends sooner in Taï than among the Yerkes apes. I’m cautious about over-interpreting this difference, since there is great overlap between growth curves, and there is only one Taï newborn compared to about 20 in Yerkes: even just a few more newborns from Taï might reveal greater similarity with Yerkes.

So there you have it, it looks like the wild Taï and captive Yerkes chimps follow basically the same pattern of brain growth, despite living in different environments. Whereas the generally greater stressors in the wild often lead to different patterns of skeletal and dental development in wild vs. captive settings, brain growth appears pretty robust to these environmental differences. That brain growth should be canalized is not too surprising, given the importance of having a well-developed brain for survival and reproduction. But it’s cool to see this theoretical expectation borne out with empirical observations.

#AAPA2015

Tomorrow I’m heading to St. Louis, MO for the annual meeting of the American Association of Physical Anthropologists. I’ll be giving a talk on Saturday presenting results of a comparison of brain size growth between captive and wild chimpanzees. Some recent work has highlighted differences between captive and wild animals in terms of bodily growth and maturation, but so far as I know brain development has not been part of this. Here’s a teaser plot, showing how the captive (blue) and wild (green) datasets deviate from a piecewise linear regression of brain size against age (for the combined wild+captive sample):

Rplot copyThe dashed black line is zero, or no deviation from the model. This plot shows that each dataset deviates little from the model at younger ages (when the brain is growing rapidly), but at older ages the captive animals have larger brains, and the wild animals have smaller brains, than predicted by the model. What’s the meaning of this? Find out Saturday afternoon at 3 pm…

Talk at UW Madison tomorrow

I’ve just flown some 7,000 miles for a 2-week stint in the USA. I’m first spending a week in Madison, WI as part of the faculty exchange between Nazarbayev University and the Unversity of Wisconsin Madison. Next week I will be in St. Louis for the AAPA conference, catching up with colleagues and presenting an analysis of brain growth in chimpanzees. Highlight of the trip so far: potable tap water (I can’t stress enough the importance of staying hydrated).

Image from Wolfram Alpha.

Image from Wolfram Alpha. Actual route is through Frankfurt, Germany.

Tomorrow I will be giving a talk here at UWM about wrangling important information out of a secretive fossil record. If you’re in the area, please come check it out! Here’s a flier with more info:

CAOkjksUUAA0Lxf

Australopithecus boisei bites

I always wondered what our extinct relative, Australopithecus boisei tasted like, until I moved to Kazakhstan.

2015-03-11 21.38.26

Mini calotte, or manti?

Here, dumplings with various fillings are called “manti” and usually have a distinct crimping running across the top. Along with their broad flaring bases and dome-like shapes, this gives manti the appearance of miniature A. boisei brain cases replete with sagittal crests:

They all look so delicious!

They all look so delicious! Fillings from left to right: lamb, pumpkin+lamb, mushrooms ewwwww.

In case you had trouble discerning braincase from блюдо, calotte from закуски in the pic, check out africanfossils.org and see if their handy, free 3D scans of fossils OH 5 and ER 406 help you figure it out.

Shockingly alarming pedagogical discovery

You heard it here first: class attendance is correlated with test performance. The discovery was made in two undergraduate anthropology courses in Astana, Kazakhstan, though the findings can probably be replicated elsewhere. This result runs counter to the widely held consensus among undergraduate students, that it is not important to attend lectures.

Midterm exam scores (out of 32 points) plotted against class attendance (left) and participation grades (right). Participation is based on in-class quizzes over readings, and so measures students exposure to both lecture and reading.

Figure 1. Midterm exam scores (out of 32 points) plotted against class attendance (left) and participation grades (right), for one biological anthropology class. Correlations and regressions slopes are significantly higher than zero.

Highly paid scientists collected data on students’ midterm exam scores, the number of sessions students were physically present at a lecture (“attendance”), and how they performed on in-class quizzes (“participation”). As quizzes are based on course readings, participation measures active investment beyond simply attendance.

Figure 2. Same variables plotted as in the previous figure, but for a second class.

Figure 2. Same variables plotted as in the previous figure, but for a second class (exam out of 25 points). In addition to linear regression lines (solid black), polynomial regressions (dashed red) were also fit for this class. Polynomial regressions have slightly lower standard errors and slightly higher coefficients of determination. Linear regressions have slopes significantly different from zero while polynomial coefficients are not statistically significant. Either way, more investment generally translate into higher grades.

The researchers were shocked to find positive relationships between students’ exam performance and measures of course participation and active participation. “With the rise of unsourced information on the internet, we assumed students didn’t need to go to class – what could a professor possibly say in lecture that can’t hasn’t already been said on ‘the Net’,” said an out of touch analyst who wasn’t involved in the analysis. The lead investigator of the study remarked, “All college students are hard-working and motivated, so we figured they would read and come to lectures if they knew they’d benefit. Our findings hint that maybe they don’t know everything after all.”

Scientists think these findings have important implications for students everywhere. An empirical link between active participation in class and grades mean that a student’s chances of doing passing or even excelling in a class can improve dramatically with increased attendance. So take note, students: read and go to class! Who knows, you might even learn something from it.

* These are my students’ actual grades and attendance this semester. No undergraduates were harmed in this study.