Amanda Rodriguez, Forensic Anthropology Center at Texas State

This spring semester, I completed an internship at the Forensic Anthropology Center at Texas State (FACTS) with Dr. Cunningham as my supervisor. I met Dr. Cunningham at an Anthropology meet-and-greet luncheon with faculty and students and was thoroughly interested in her research regarding body size estimation methods for Homo erectus. I knew I had a passion for paleoanthropology – the study of ancient human ancestors – and asked her if I could assist in her next project. What I didn’t realize at the time was that I would walk away with much more from this internship than I had ever imagined. 

The main objective of my internship research was to estimate body size (body mass and stature) in Homo erectus, an extinct hominin. For the majority of the semester, I measured the distal humerus, or upper arm bone, in order to estimate body mass. I presented a poster of the findings at the Undergraduate Research Conference and Honors Thesis Forum at Texas State on this portion of my internship research. Towards the end of the semester, Dr. Cunningham asked me to be involved in data collection on the femur in order to estimate stature.  

Homo erectus is credited as the earliest hominin with body and limb proportions similar to modern humans. According to Larsen (2017), its purported stature ranged between 148-185 cm, with a body mass range of 46-68 kg, but these higher estimates are controversial (Cunningham et al. 2018; Graves et al. 2010; Ruff and Burgess 2015; Ruff and Walker 1993).

Body size estimation is key in most paleoanthropological investigations. Body mass can help predict the brain size, energy usage and dispersal rate (i.e., migration patterns) of hominins.  Additionally, accurate body mass estimations are integral to understanding the behavioral ecology, or the evolutionary basis of behavior in response to environmental pressures, of each species (Fellmann 2006). Estimating body mass frequently relies on stature estimations which are estimated using femoral length.

One Homo erectus fossil, MK3 (Fig. 1), provided the inspiration for this project. MK3 is a single left distal humerus and was found in 1976 during excavations at Gombore I, an area of Melka Kunture – a well-known paleolithic site – located in the Upper Awash basin of Ethiopia (Di Vincenzo et al. 2015). Due to the robusticity of MK3, the individual was thought to be male and had an estimated body mass of 90 kg.  This high estimate falls outside the range of typical Homo erectus specimens (Di Vincenzo et al. 2015). 

Figure 1. Anterior and posterior view of MK3; scale bar is 3.0 cm. From Di Vincenzo et. al (2015).

At the end of the semester, Dr. Cunningham asked me to contribute to a collaborative project that a former intern had worked on a few semesters ago. This project’s main goal is to estimate stature of Homo erectus based on femoral fragments. This portion of my internship involved learning new methods of skeletal data collection, learning how to use the NextEngine Laser Scanner, and learning a computer program called 3D Slicer.

Methods and Materials 

For the body mass estimation portion of the internship, I measured the distal humerus of skeletons from the Texas State Donated Skeletal Collection (TXSTDSC). The project was inspired by Di Vincenzo et al.’s 2015 research in which he estimated the body mass of purported hominin MK3 to be approximately 90 kg using a well-known distal humerus regression equation (McHenry 1992). Our objectives were to evaluate the accuracy of his estimation, test the accuracy of the distal humerus regression equation and see how well this method performed when compared to three well-known equations estimating body mass from femoral head diameter (Grine et al. 1995; McHenry 1992; Ruff et al. 1991).  Body mass at-death is known for all individuals, and we only included individuals with a normal body mass index or BMI (18.5-24.9). This is because skeletal measurements predict lean body mass only. I took two separate measurements of the distal humerus from 120 human males of the TXSTDSC. I measured the capitular height (Fig. 2a) and the distal articular width (Fig. 2b) using digital spreading calipers (Fig. 3). These two variables were then used to estimate body mass using McHenry’s 1992 distal humerus regression formulae. Furthermore, we wanted to use the known body masses of the TXSTDSC specimens to evaluate that same regression equation for accuracy.  Finally, we compared body mass estimates from the distal humerus to those from three well-known equations that used femoral head diameter.

[Figure 2. Measurements of the distal humerus: capitular height (a) and distal articular width (b).]
[Figure 3. A digital spreading caliper.]

For the femoral stature project, I learned how to measure the femoral neck shaft angle (NSA), how to render objects using NextEngine and how to analyze femoral data using 3D slicer. Since the femoral head is used to transfer weight from the hip, its orientation is important in consideration of bipedal behavior among fossil hominins (Ruff et al. 2013). All early Homo have relatively long femoral shafts and reduced NSAs,  ranging from 114-125 degrees, as opposed to modern humans with an average NSA of 128 degrees (Ruff et al. 2013). Neck shaft angle measures “the medial inclination of the femoral head and neck,” and therefore can be used to look at bipedal adaptation in fossil hominins, as individuals that share similar NSA values are thought to exhibit similar gait and locomotive behaviors (Child & Cowgill 2017). In order to estimate femur stature of Homo erectus, we selected several femora from the Texas State Donated Skeletal collection with low NSAs and measured them with a goniometer to find human specimens with comparable NSA values. Dr. Wescott was tasked with teaching me how to measure NSA using the goniometer, an instrument used to measure angles, by finding the vertical midshaft axis of the femur and recording the angle of its intersection with the midshaft axis of the femoral head and neck. It proved challenging finding and marking each midshaft point but with practice, I became very comfortable with it. I then recorded the approximate angles of each shaft and separated them into two groups depending on if they were below or exceeded 117 degrees.   

NextEngine is a desktop 3D Laser Scanner used to render objects digitally by taking multiple scans, while rotating the object 360 degrees and stitching the scans together digitally. Via structured light scanning, NextEngine uses a triangulation technique to calculate the distances between each point on the object before rendering it in 3D (White 2015). The goal of learning to use NextEngine was to enable me to render femoral specimens in 3D in order to estimate stature. While I did learn how to use the program to render a small sample object, I didn’t end up rendering any femora due to time constraints. Each  

3D slicer is an accompanying software platform that is used for digital image processing and 3D visualization, while allowing the user to place landmark coordinates in 3D. I was tasked with learning Harmon’s 17 femoral landmarks (2005), placing them on 30 digitally-rendered femora from the Hamann-Todd collection, recording those landmark coordinates and calculating inter-landmark distances in Excel. The objective of Harmon’s 17 femoral landmarks was to facilitate femoral measurements that are not possible to obtain by linear measurement by dividing the femur into equal anterior and posterior portions, and recording extreme points defining maximum curvature and boundaries of anatomical structures (Harmon 2005). In addition to calculating the inter-landmark distances in Excel, I recorded the known stature of these individuals in order to evaluate the accuracy of the femoral stature estimation method. 

Results & Discussion

For the distal humerus project, we created three bivariate plots. We wanted to compare McHenry’s (1992) distal humerus regression equation with the three well-known femoral head regression equations (Fig. 4) (Grine et al. 1995; McHenry 1992; Ruff et al. 1991), look at how each of the two distal humerus measurements correlated with known body mass (Fig. 5), and to investigate what the ratios looked like in human males, female gorillas and MK3 (Fig. 6). A bivariate plot, I learned, is jargon for a typical X and Y plot used to compare the relationships between the two variables. Because McHenry’s (1992) distal humerus equation lined up almost perfectly with his (1992) femoral head equation in terms of accuracy, we can say that his estimate of 90kg for MK3 was reasonable, even if it fell out of the typical body mass range for Homo. Looking at how each distal humerus measurement, capitular height and distal articular width, correlated with the known body masses of individuals from the TXSTDSC (Fig. 5) produced no significant findings. I did learn about statistical analysis and that the rvalue represents a percentage of correlation between two values. Finally, when looking at the ratios of capitular height and distal articular width in MK3, modern human males and female gorillas (Fig. 6), we found that MK3 fell within the range of female gorillas implying a similar allometry. Allometry can be defined as the growth rate of different body parts, or in our case, different features of the humerus. Though MK3 shows similar allometry to female gorillas, according to Di Vincenzo et al. (2015), a comparative analysis of the overall shape and structure of the humerus is much more congruent to the genus Homo than that of Gorilla.

[Figure 4. Bivariate plot comparing the distal humerus (HDM) and the femoral head (FHD) body mass estimation accuracy.]

[Figure 5. Bivariate plot comparing known body mass to capitular height (CPSI) and distal articular width (HDML).]

[Figure 6. Bivariate plot displaying HDML to CPSI ratios of MK3, female G. gorilla, and male TXSTDSC H. sapiens.]

[Figure 7. A picture of me presenting my poster at the Undergraduate and Honors Thesis Research Conference.]

While I began collecting data for the femur stature project, we are still figuring out the logistics of the exact specimens that will be used and by what methods we will use to analyze that data. I will continue to contribute during the summer working with Dr. Cunningham and also with Dr. McCarthy, a collaborator, later on in the fall. 


While this internship began with the idea of data collection and presentation of results for a research project I was passionate about, it’s provided me with numerous opportunities to advance my career in Anthropology. During the course of the semester, I became very familiar with the Grady Early Forensic Anthropology Research Lab (GEFARL). I solidified my abilities taking skeletal measurements and was able to measure the same features of elements with precision down to the hundredth of a millimeter after a few months. Because part of my internship required I work eight hours a week, I supplemented with time spent volunteering at the Osteological Research and Processing Lab (ORPL) and GEFARL. I had never volunteered at GEFARL before the internship and was tasked with documenting new donations brought in from ORPL. This included laying the skeletal elements out in anatomical order, which in addition to being very rewarding, taught me the nuances of each element. I also learned how to use the Canon digital camera and Adobe Photoshop to take pictures of the donation and edit them to be inventoried in the system. 

Dr. Cunningham has been a fabulous mentor and has really encouraged me to branch out academically as much as possible. Halfway through the semester, an opportunity to apply for a paid Biological Anthropology Internship at the Field Museum in Chicago came along. I wasn’t sure how qualified I would be, but she pushed me to apply anyway. I’m so glad she did. About a week later I found out that I got the position which was more than I ever could have asked for from this semester. In fall, I’ll be working at the Field Museum under an Institute of Museum and Library Services (IMLS) Bioarchaeologist, helping to inventory North American skeletal remains, re-house those remains, and assist in data collection and entry. To say I’m elated is an understatement. This internship has been a blessing and an amazing learning experience. I’m so grateful for these opportunities that will help me in pursuing Biological Anthropology as a career. 


Child, Stephanie L., and Libby W. Cowgill. 2017. “Femoral neck-shaft angle and climate-induced body proportions.” American Journal of Physical Anthropology 2017:1-16. 

Di Vincenzo, Fabio, Laura Rodriguez, José Miguel Carretero, Carmine Collina, Denis Geraads, Marcello Piperno, and Giorgio Manzi. 2015. “The massive fossil humerus from the Oldowan horizon of Gombore I, Melka Kunture (Ethiopia, >1.39 Ma).” Quaternary Science Reviews. 122:207-221. 

Fellmann, Connie D. 2006. “Estimation of Femoral Length and Stature in Homo Erectus from Fragmentary Remains.”Collected works for “The 40th Anniversary of Yuanmou Man Discovery and the International Conference on Paleoanthropological Studies”. 

Grine, Frederick E., William L. Jungers, Phillip Tobias, and Osbjorn M. Pearson. 1995. “Fossil Homo femur from Berg Aukas, northern Namibia.” American Journal of Physical Anthropology 26:67-78. 

Harmon, Elizabeth Hunt. “A Comparative Analysis of Femoral Morphology in Australopithecus afarensis: Implications for the Evolution of Bipedal Locomotion.” PhD dissertation, Arizona State University, August 2005. 

McHenry, Henry M. 1992. “Body Size and Proportions in Early Hominids.” American Journal of Physical Anthropology 87:407-431.

Ruff, Christopher B., and Ryan Higgins. 2013. “Femoral Neck Structure and Function in Early Hominins.” American Journal of Physical Anthropology 150:512-525.

Ruff, Christopher B., William W. Scott, and Allie Y.-C. Liu. 1991. “Articular and Diaphyseal Remodeling of the Proximal Femur with Changes in Body Mass in Adults.” American Journal of Physical Anthropology 86:397-413. 

White, Suzanna. 2015. “Virtual Archaeology – The NextEngine Desktop Laser Scanner.” Archaeology International18:41-44. doi: