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.

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Bioanthro lab activity: Estimating Miocene ape body mass

We’ve arrived at the Planet of the Apes, also known as the Miocene, in my “Bones, Stones and Genomes” course. The living apes are but a small remnant of what was a pretty successful radiation starting around 20 million years ago. There were so many apes that it can be a bit confusing for students, but it’s important for setting up the biological and ecological contexts of hominin origins.

Possible evolutionary relationships of myriad Miocene apes and subsequent hominins. From Harrison (2010)

Possible evolutionary relationships of myriad Miocene apes and subsequent hominins. From Harrison (2010)

This week also marks my students’ first lab assignment, analyzing CT scans of bones. Here, we looked at how we estimate body size in extinct animals, using the KUPRI database and the free CT analysis software InVesalius. Because some of the KUPRI primates have body masses recorded, students can examine the relationship between animals’ weight and skeletal dimensions. The purpose of the assignment is to help familiarize students with skeletal anatomy, CT data and principles of linear regression.

One of the KUPRI specimens, an old female gorilla, with known weight.

One of the KUPRI specimens, an old female gorilla, with known weight.

I selected a few specimens for students to examine. After students download the massive files, they can load them into InVesalius for analysis. This program allows students to easily identify bone versus other tissues, and to create a 3D surface rendering of a highlighted region (tissue) of interest.

A grivet, Chlorocebus aethiops, with bone highlighted in 2D sections and as a 3D model.

A grivet, Chlorocebus aethiops, with bone highlighted in 2D sections and as a 3D model. This little guy weighs only 4 kg!

It’s pretty easy to take simple linear measurements (and angles), assuming students can get oriented within the skeleton and identify the features they need to measure. It can be a little tricky to measure a femur head if it’s still in the acetabulum (below). Luckily, InVesalius lets you take measurements on both 2D slices or the 3D volume.

Let's measure that femur head diameter.

Let’s measure that femur head diameter.

So students do this for a few specimens and enter the data into Excel, which can then easily plot the data and provide a regression equation. They then use this equation to estimate masses of the specimens – if there’s a good relationship between mass and skeletal measures, then the estimates should be close to the observed values. Students use their equation to predict body mass of some Miocene apes based on femur head diameter and femur midshaft diameter, noting how confident they feel in their estimates given how well their regression performed on the training dataset. They also compare their mass estimates to those using another equation generated by Christopher Ruff (2003).

It might be a little intense for students totally unfamiliar with apes, bones and CT scans, but it should be a good way for them to learn lots of concepts we’ll revisit over the semester.

Here’s the lab assignment, in case you want to use it in your own class: Lab 1-Miocene masses

A new year of bioanthro lab activities

One of my goals in teaching is to introduce students to how we come to know things in biological anthropology, and lab activities give students hands-on experience in using scientific approaches to address research questions. Biological anthropology (really, all biology) is about understanding variation, and I’ve created some labs for students to scrutinize biological variation within the classroom.

In my Introduction class, the first aspect of human uniqueness we will focus on is the brain. To complement readings and lectures, we’ll also investigate variation in brain size among students in class. Of course, measuring their actual brain sizes is impossible without either murdering them (unethical and messy) or subjecting them to CT or MRI scanning (costly and time-consuming). Instead, it’s fast and easy to measure head circumference, so we’ll estimate just how brainy they are in a way that will also introduce them to data collection, measurement error, and the regression analysis.

The lab activity is based on a paper by Bartholomeusz and colleagues (2002), who used CT scanning to measure the external head circumferences and brain volumes of males ranging from 1-40 years. Focusing on the adults of this sample, there are several possible regression equations that students could use to estimate their brain size from their head circumference:

The relationship between head circumference and brain volume in adult humans. Note each regression line is based on different age groups.

The relationship between head circumference and brain volume in adult humans. Note each regression line is based on different age groups. Data from Bartholomeusz et al. (2002).

Bartholomeusz et al. divided their sample into age groups, and students will learn that the relationship between the two variables differs subtly depending on the age group. Students will therefore have to decide (and justify) which equation they will use – should they pick the one based on their own age group, or the one with the lowest prediction error?

Once students have estimated their brain sizes, I’ll enter the data into R and we’ll look at how (estimated) brain size varies within the classroom, looking also at possible covariates including sex and region of birth. After discussing our data in class, students have to write up a brief report describing our research question and proposing additional hypotheses about brain size variation.

So that’s this week’s lab in Introduction to Biological Anthropology. There will be four more this semester, in three of which students will collect data on themselves, as well as four other labs for my Human Evolution course. In case you’re interested in using this activity for your class, I’m including the lab handout here. I’ll also try to post lab assignments to the blog (as I’ve done here) as the semester progresses.

Activity handout: Lab 1 Instructions and report

ResearchBlogging.orgReference

Bartholomeusz, H., Courchesne, E., & Karns, C. (2002). Relationship Between Head Circumference and Brain Volume in Healthy Normal Toddlers, Children, and Adults Neuropediatrics, 33 (5), 239-241 DOI: 10.1055/s-2002-36735

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

Results of the toe-tally easy lab activity

Alternate title: Dorsal canting in primate PPP4s

Earlier this year I suggested a classroom activity in which students can scrutinize the evidence used to argue that the >5 million year old (mya) Ardipithecus kadabba was bipedal. To recap: Ar. kadabba is represented by some teeth, a broken lower jaw, and some fragmentary postcrania. The main piece of evidence that it is a human ancestor and not just any old ape is from a single toe bone, and the orientation of its proximal joint. In Ar. kadabba and animals that hyperdorxiflex their toes (i.e., humans and other bipeds when walking), this joint faces upward, whereas it points backward or even downward in apes. This “dorsal canting” of the proximal toe joint has also been used as evidence that the 4.4 mya Ardipithecus ramidus and 3.5 mya owner of the mystery foot from Burtele are bipedal hominins. A question remains, though – does this anatomy really distinguish locomotor groups such as bipeds from quadrupeds?

Use ImageJ to measure the canting angle between the proximal joint and plantar surface. Proximal to the right, distal to the left.

STUDENT SCIENTISTS TO THE RESCUE! Use ImageJ to measure the canting angle between the proximal joint and plantar surface, as I’ve done on this Japanese macaque monkey (they are not bipedal). Proximal to the right, distal to the left Note I changed the measured angle from the March post.

I sicked my students in Ant 364 (Human Evolutionary Developmental Biology) here at NU on this task. I had students look at only 11 modern primates from the awesome KUPRI database. Most groups are only represented by 1 (Homo sapiens, Hylobates lar and Macaca fuscata) or two (Pongo species and Gorilla gorilla) specimens, all adults. For chimpanzees (Pan troglodytes) there is one infant and four adults. The database has more individuals, and it would be better to include more specimens to get better ideas of species’ ranges of variation, but this is a good training sample for a class assignment. The fossil group includes one Ardipithecus ramidus, one Ar. kadabba, one Australopithecus afarensis, and the PPP4 of the mystery foot from Burtele. The human and all fossils except Ar. kadabba are based off of lateral photographs and not CT scans like for the living primates, meaning there may be some error in their measurements, but we’ll assume for the assignment this is not a problem. Here are their results:

Dorsal canting angle of the fourth proximal pedal phalanx in primates.

Dorsal canting angle of the fourth proximal pedal phalanx in primates. The lower the angle, the more dorsally canted the proximal joint surface. The “Fossil” group includes specimens attributed to ArdipithecusAustralopithecus and something unknown.

Great apes have fairly high angles, meaning generally not dorsally canted proximal joint surfaces. The two gorillas fall right in the adult chimpanzee (adult) range of variation, while chimp infant and orangutans have much higher angles (≥90º means they’re actually angled downward or plantarly). The gibbon (Hylobates) is slightly lower than the chimpanzee range. The macaque has an even more dorsally canted joint, and the human even more so. The fossils, except the measurement for Ar. ramidus (see note above), have lower angles than living apes, but higher than the human and the monkey. If dorsal canting really is really a bony adaptation to forces experienced during life, then the fossil angles suggest these animals’ toes were dorsiflexed more so than living great apes (but not as much as the single monkey and human).

This lab helps students become familiar with CT data, the fossil record, taking measurements (students also measure maximum length of the toe bones and look at the relationship between length and canting), analyzing data, and hypothesis testing. You can also have fun exploring inter-observer error by comparing students’ measurements.

Here’s the full lab handout if you want to use or modify it for your own class: Lab 5-Toe instructions and report

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.