Bioanthro lab activity: Primate proportions

My Intro to Bio Anthro course, focusing on human uniqueness, has moved from the brain to bipedalism. After the abysmally big brain, perhaps the most grotesque aspect of the human species is our wont to walk on two legs. It’s just not natural.

Image credit.

What a terrible biped. Image credit.

Seriously, why would an animal do such a horrid thing?

Image credit.

Most animals need extra help to stay upright on just two limbs. Image credit.

This peripatetic penchant is apparent in our skeletons, most visibly in our long-ass legs. And indeed, species’ limb lengths and proportions generally reflect how they tend to move around. Quadrupeds, animals that walk on four legs, tend to have roughly equally-lengthed arms and legs. Gibbons, notorious ricochetal brachiators, have insanely long arms. So for lab this week, students measured surface scans of different primates’ long bones to see if form really follows function.

Here, students try their hands at measuring long bones on surface scans of primate skeletons, and use their data to calculate indices reflecting the relative lengths of limb segments. These data will be used to test whether limb proportions can be used to distinguish different locomotor types, and to hypothesize how fossil species might have moved about.

Measuring siamang (Symphalangus syndactylus) limb lengths with Meshlab. Data credit.

Measuring siamang (Symphalangus syndactylus) limb lengths with Meshlab. Data credit.

Since this is my students’ introduction to primate skeletons and analysis software, I only had them measure three specimens: a siamang (above), a squirrel monkey, and a grivet.  But of course you can have students look at more if you wish. This activity uses the free Meshlab software  and surface scans made from CT scans in the KUPRI database (surface scans are much smaller files than CT scans, making for easier dissemination to swarms of students). If you’re interested in using or modifying this activity in your class, here are the lab handout and datasheet I created for it:

Lab 2-Primate proportions
Lab 2-Primate limb data sheet

Info about, and materials for, other lab activities can be found on my Teaching page.

Lessons from limb lab (activity)

This semester I have added a lab component to my Introduction to Biological Anthropology class. Lab activities and assignments provide students with opportunities to gather data, to think about them in the context of various theories, and to learn about how to analyze them. This past week’s lab looked at limb proportions within our classroom, in the context of “Allen’s rule” – in colder climates, animals tend to have relatively shorter distal limbs (radius+ulna and tibia+fibula). Allen’s rule, along with “Bergmann’s rule,” describe ecogeographic variation in humans and other animals: body size (i.e., mass) and shape (i.e., limb proportions) tend to vary with climate, such that populations living in colder environments tend to have less surface area relative to body mass, as an adapation to retain body heat.

A simple and effective way to quantify the relative lengths of limbs is through ratios: in this case we examined the crural and brachial indices. Here I’ve plotted average human indices against latitude as reported in a recent paper by Helen Kurki and colleagues (2008):

Left: Crural index (tibia length/femur length) related to latitude, as a proxy for climate. Right: Brachial index (radius length/humerus length) plotted against latitude. Data from Kurki et al. (2008). Black=female, red=male. Dashed lines are  regression slopes for each sex, and solid lines indicate the 95% confidence limits of the regression lines.

Human limb proportions related to latitude, as a proxy for climate. Left: Crural index (tibia length/femur length). Right: Brachial index (radius length/humerus length). Higher indices mean relatively longer tibia or radius. Data from Kurki et al. (2008). Black=female, red=male. Dashed lines are least squares regression lines for each sex, and solid lines indicate the 95% confidence limits of the regression lines. How well will our class’s data fit these models?…

These plots are consistent with Allen’s rule – the distal limb segments become relatively shorter with increasing latitude. In lab, we test whether our limb proportions reflect this presumably ecogeographic pattern. Here in Astana we are at 51ºN latitude, so these regressions predict that our class should have crural indices between 0.82-0.84, and brachial indices between 0.72-0.79. How well does our class fit these model’s predictions?

Pretty terribly.

…Pretty terribly. Plots are same as above, except with our class’s data added at 51º N latitude (vertical lines). In each, the vertical lines span the class’s 95% range (black=females, red=males), with the dots marking each sex’s average. Kazakhstan is huge, and students could have grown up in latitudes from 42º-55º N, but even assuming students had all come from Shymkent their distal limbs still appear much longer than expected.

These plots show that students in the class have longer distal limbs than expected – both for our latitude, and for humans generally. The poor fit of my students’ limb proportions probably doesn’t mean they’re bad humans. Instead, we probably deviate because we compared apples to oranges: the Kurki data were dry long bones measured on an osteometric board, whereas I had my students do their best to palpate and measure the maximum lengths of their own bones beneath layers of fat, muscle, skin, and clothing. Our high indices probably reflect the underestimation of humerus and femur lengths, whose most proximal points that can be palapated (greater tubercle and trochanter, respectively) lie a bit lower than the respective heads, which would have been included in the Kurki measurements.

It was interesting to review these plots with students. Even though they’re fairly new at reading graphs like these, there was an audible gasp and bewildered muttering when their own data went up on the board. I myself was surprised at these results, but I’m happy with how the exercise went. This particular ‘study’ helps students learn about ecogeography, adaptation and human variation, as well as the importance of homology and comparing like with like.

Arm and leg modelling

No, I’m not looking for people with lithe limbs to be photographed for money. Much more sexily, I’m referring to a recent paper (Pietak et al., 2013) that’s found that the relative length of the segments of human limbs can be modeled with a log-periodic function:

Figure 2 from Pietak et al. 2013. Human within-limb proportions are such that the length of each segment (e.g., H1-6) of a limb, from  fingertip to shoulder (A) and to to hip (B), can be predicted by a logarithmic periodic function (C).

In other words, within a limb, the length of each segment is mathematically fairly predictable on the basis of the segment(s) before and after it. As the authors state, “Being able to describe human limb bone lengths in terms of a log-periodic function means that only one parameter, the wavelength λ, is needed to explain the proportional configuration of the limb.”

The biological significance of this pattern is difficult to discern. The length of a limb segment is determined by a number of factors, including the spacing between the initial limb condensations embryonically, and thereafter the growth rates and duration of growth at proximal and distal epiphyses. As a result, limb proportions aren’t static throughout life, but change from embryo to adult. For instance, here are limb proportion data for the coolest animal ever – gibbons! – from the great anatomist Adolph Schultz.

ResearchBlogging.orgAn important question, and follow-up to Pietak et al’s study, is whether human limb proportions can be described by such log-periodic functions throughout ontogeny, and if so how these change. Plus, it’s also not clear to what extent human proportions might happen to be describable by log periodic functions, simply because each segment is shorter than the one preceding it proximally. In short, this study raises really interesting and pursuable questions about how and why animal limbs grow to the size and proportions that they do.

Pietak A, Ma S, Beck CW, & Stringer MD (2013). Fundamental ratios and logarithmic periodicity in human limb bones. Journal of anatomy, 222 (5), 526-37 PMID: 23521756

Schultz, A. (1944). Age changes and variability in gibbons. A Morphological study on a population sample of a man-like ape American Journal of Physical Anthropology, 2 (1), 1-129 DOI: 10.1002/ajpa.1330020102