Sexual dimorphism in the bony labyrinth of geographically diverse samples

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Sexual dimorphism in the bony labyrinth of geographically diverse samples Alexandra Uhl1, Katerina Harva'1

1 Paleoanthropology, Senckenberg Center for Human Evolu'on and Paleoenvironment, Eberhard Karls Universität Tübingen, Rümelinstrasse 23, 72070 Tübingen, Germany

Table 1. T-­‐Test between males and females Variabl p-­‐ Popula'o Popula'on Variable p-­‐value e value n GERMAN ASCh/w 0,92

Figure 1. Anatomical loca<on of the bony labyrinth. Right side, lateral view.

Introduc<on

Previous research on the bony labyrinth focused primarily on its morphology, phylogeny, and role in locomo'on (e.g. Spoor & Zonneveld 1998; Spoor et al. 2003; Gunz et al. 2012). The bony labyrinth was recently also shown to be sexually dimorphic in a Greek popula'on (Osipov et al. 2013). The present research aims to assess whether their results are applicable across samples of diverse geography.

ZULU

ASCh/w 0,34

PSCh/w 0,55

PSCh/w 0,39

LSCh/w 0,62

LSCh/w 0,47

SLI 0,049* SLI ASC-­‐R 0,33 ASC-­‐R PSC-­‐R 0,11 PSC-­‐R LSC-­‐R 0,45 LSC-­‐R ASC%R 0,46 ASC%R PSC%R 0,21 PSC%R LSC%R 0,69 LSC%R * p-­‐value is significant

0,09 0,006* 0,026* 0,05 0,31 0,33 0,33

Figure 3. PCA showing sex and popula<on differences. Wireframe morph shapes of extremes on axis ends. Mean male vs. female and zulu vs. German surface warps pictured below.

Figure 2.

Skeletoniza<on of the bony labyrinth and corresponding landmark placement.

Materials & Methods

Acknowledgements: We thank K. Carlson and T. Jashashvili for their work scanning the Zulu sample and B. Billings for access to the Dart collec'on. We also thank M.Francken, W. Binczik, C. Bauer, and L. Kellner for their help with the German sample. Alexandra Uhl is supported by a research grant from the L.S.B. Leakey Founda'on. This research was made possible through a DFG major instrumenta'on grant (DFG INST 37/706-­‐1 FUGG).

References: Gunz, P., Ramsier, M., Khurig, M., Hublin, J-­‐J., Spoor, F. 2012. The mammalian bony labyrinth reconsidered, introducing a comprehensive geometric morphometric approach. J Anat. 220, 529-­‐543. Osipov, B., Harva', K., Nathena, D., Spanakis, K., Karantanas, A., Kranio', E.F. 2013. Sexual Dimorphism of the Bony Labyrinth: A New Age Independent Method. Am. J. Phys. Anthropol. 151(2), 290-­‐301. Spoor, F. & Zonneveld, F. 1995. Morphometry of the primate bony labyrinth: a new method based on high resolu'on computed tomography. J Anat. 186, 271-­‐286. Spoor, F. & Zonneveld, F. 1998. Compara've review of the human bony labyrinth. Yearb of Phys Anthropol. 41, 211-­‐251. Spoor, F., Hublin, J-­‐J., Braun, M., Zonneveld, F. 2003. The bony labyrinth of Neandertals. J Hum Evol. 44, 141-­‐165.

Table 2. Discriminant Func<ons per sample. To classify individuals of unknown sex Popula'on

Zulu and Germans

Zulu

Germans

ASCh/w

-­‐0,021258

0,10083

-­‐0,1641

PSCh/w

0,062774

0,069266

0,056787

LSCh/w

-­‐0,036957

-­‐0,074329

0,077286

SLI

0,24048

0,26555

0,32744

ASC-­‐R

1,3484

1,509

0,96822

PSC-­‐R

1,3013

1,3812

1,0052

LSC-­‐R

0,96316

1,0019

0,74107

ASC%R

0,19111

0,38703

-­‐0,17833

PSC%R

0,20227

-­‐0,042368

0,3814

LSC%R

-­‐0,20098

-­‐0,042368

-­‐0,20927

Offset Constant

32,3235

46,4217

24,1316

% Classifica'on Accuracy

76,47

73,68

73,33

Figure 4. Discriminant Analysis by popula<on at 100% accuracy. Zulu in green, Germans in red.

9 8 7 Frequency

Popula'on samples studied include 38 adult Zulu from the Dart collec'on at the University of the Witwatersrand, Johannesburg, South Africa; as well as 30 adults from Baden-­‐WuerVemberg, Germany, housed in the collec'ons of the Eberhard Karls Universität Tübingen. All individuals were of known sex. CT-­‐scans of crania were obtained on site. Both the leh and right bony labyrinths were segmented using Avizo sohware (FEI Company, Hillsboro, OR, USA). The segmented volume was thinned to a skeleton (a centerline of connected voxels), which was placed through the virtual endocast with the Auto Skeleton module, following methods similar to those established by Gunz et al. (2012). 20 landmarks per side (40 total) were placed along the three semi-­‐circular canals, as well as on the cochlea. This method was used because the error tests proved it to be more accurate (less than 3% error for all measurements) than previous measurements. Using the pythagorean theorem, the distances between certain landmarks allowed us to calculate the height and width of each canal and the cochlea according to the dimensions used in Osipov et al. (2013) and based on Spoor & Zonneveld (1995). Indices from these publica'ons for the radius of curvature (ASC-­‐R, PSC-­‐R, LSC-­‐R) and rela've radii (ASC%R, PSC%R, LSC%R) were also calculated. A students t-­‐test between the sexes of each sample and a PCA on all variables was performed. In order to evaluate the rela'onship between males and females based on the variables measured, a discriminant analysis was used. From the discriminant analysis, discriminant func'ons were created which can be used to classify individuals of unknown sex (see Table 2).

6 5 4 3 2 1 0 -50 -40 -30 -20 -10 0 10 20 30 40 Population

Results & Discussion

T-­‐tests reveal that for the Zulu, ASC-­‐R (anterior semicircular canal radius of curvature and PSC-­‐R (posterior semicircular canal radius of curvature) were significantly different between sexes. For the German sample, SLI (a ra'o indica've of the posi'on of the lateral canal rela've to the posterior canal), was significant, see Table 1. These results are similar to those found by Osipov et al. (2013 with PSC-­‐R as the single best variable for sex es'ma'on with 76 % accuracy. Two mul'variate func'ons increased this accuracy to 84 %. Applying the Osipov et al. (2013) discriminant func'ons resulted in 76 % accuracy in the German sample and only 52 % classifica'on accuracy in the Zulu sample. Therefore, we created new discriminant func'ons (see Table 2) which can be used to es'mate the sex of an unknown individual. The discriminant analysis result for the Zulu was correct classifica<on by sex at 82 %. For the German sample, discrimina<on accuracy for sex was slightly lower at 77 %. When all individuals were analyzed together (n = 68), the discriminant classifica<on accuracy was 77 %. The PCA results show that within each popula'on, males and females are seperated along PC 2 with more males in the posi've and females in the nega've range. Popula'ons are clearly seperated by PC 1 (see Figure 3). This result is mirrored in a second discriminant analysis for popula'on -­‐ popula'ons can be successfully discriminanted to 100 % accuracy (see Figure 4).


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