FALLAS EN PAVIMENTOS FLEXIBLES

Due to its importance in evolutionary research and its ability to withstand fragmentation and diagenesis, the skull is one of the best studied skeletal elements (8,11). Additionally, recent studies show that the skull is the most frequently recovered skeletal element in South African forensic contexts. This section reviews the advantages and disadvantages of commonly used sex estimation methods, with reference to cranial research.

2.3.1 Morphological/ Quantitative Methods

In modern forensic anthropology, morphological examinations involve the visual assessment of cranial landmarks that are not pathological, generally not visible on the body surface and are difficult to assess metrically (6,18,40). Some commonly employed morphological sex-specific features of male crania include greater overall robusticity, larger mastoids and external occipital protuberances, more protrusive glabellae, squared orbits, taller and narrower nasal apertures, broad “U”-shaped palates, and more protrusive mental eminences (6,40–43). Morphological methods are simple to use, time efficient, cost effective, and can be applied to fragmentary specimens. However, they are highly subjective, cannot readily be subjected to rigorous multivariate statistical testing, can be difficult to reproduce due to subjectivity and often ill-defined methodology, and require a highly skilled observer (6,40–43).

The problem of subjectivity in morphological assessments has been reduced by using ordinal scoring systems (18,42,44). These are used for classifying discrete bony features (e.g. yes/no or absent/present) and for continuums of expressions (e.g.

progressive closure of the cranial sutures, scored on a scale of one to five) (18,44).

Walker’s (42) morphological system is commonly employed in forensic investigations as it is quick and easy to apply. Based on characteristics first detailed by Buikstra and Ubelaker (45), Walker employed linear discriminant analyses and an ordinal scoring system and was able to correctly assign sex in 90% of specimens. His methodology was tested in a South African context by Krüger and colleagues (46) on a sample of 245 black and white South Africans. The authors demonstrated similar accuracies to those found by Walker for white males (94.0%-97.0%), but very low accuracies in their female counterparts (31.0%-62.0%). This result highlighted the need for

population-13 specific standards for this unique population. After developing those, the female accuracies rose to 83.0%-94.0%. In a separate study, L’Abbé and associates (47) assessed a different set of morphological features in black, white and coloured South Africans. In this investigation, also implementing ordinal scoring, they demonstrated that only inter-orbital breadth was significantly influenced by sex alone, whilst nasal bone contour, nasal breadth, and interorbital breadth were influence by the interaction of sex and ancestry.

2.3.2 Metric/ Quantitative Analyses

Metric analyses involve taking measurements between various anatomical landmarks (6). Most metric studies employ linear discriminant analyses to create discriminant functions that use predetermined measurements to estimate sex (48,49).

Logistic regression, an alternative to discriminant analyses, has been gaining favour of late because it is less constrained by assumptions such as normality (50). This subject will be discussed in greater detail in Chapter Five.

A number of studies have analysed metric variation between the sexes in a South African context (1,4,20,51,52). Using basic univariate statistics, de Villiers (19) investigated SxD in black South African crania and found that the glabellar prominence, superior orbital margin, inferior margin of the nasal aperture, supramastoid crest and the mastoid process were particularly dimorphic. Loth and Henneberg (53) found the morphology of the mandibular ramus flexure in South Africans to be extremely dimorphic. Their study achieved sexing accuracies of between 91% and 99%, depending on the dental state of the mandible investigated. Such levels are as accurate as using the pelvis. In one of the few analyses conducted on white South Africans, İşcan and Steyn (1) measured 12 cranial and 5 mandibular dimensions and achieved sexing accuracies of between 80% (bizygomatic breadth alone) and 86%

(all cranial dimensions). More recently, Dayal et al. (54) were able to achieve accuracies ranging between 80% and 85% using 14 cranial and 6 mandibular measurements of black South Africans. The effects of applying FORDISC 3.0 to metric dimensions collected from South African crania were investigated by L’Abbé et al. (52).

They found sex classification errors were more common than ancestry errors, highlighting that unique sex characteristics are present in this population. Their conclusions provide further substantiation of the need for more detailed analyses of SxD in white South Africans.

14 Advantages of metric analyses are that they are less subjective than morphological assessments, can be readily tested using multivariate statistics, and are easily reproducible, given that landmarks and procedures are well-defined and can be implemented by less experienced observers (6). The disadvantages are that they are more time consuming to perform than morphological assessments, require specialised equipment that can be expensive, and can be difficult to apply if observed regional differences cannot be quantified through measurement (6,42).

2.3.3 Geometric Morphometrics

Geometric morphometrics (GMM) is a relatively new technique for analysing morphological characteristics by metric means and thereby eliminating some of the problems associated with traditional techniques mentioned above (6,55,56). Rohlf and Marcus (57) coined the term Geometric Morphometrics and believed that the method would revolutionise morphometrics. Indeed, GMM has gained considerable favour in recent years due to the fact that it retains all the geometric information throughout data collection, whereas traditional metric analyses tends to collapse structures into a number of landmarks, measurements and angles (55,58). The technique involves the analysis of two-dimensional (2-D) or three-dimensional (3-D) Cartesian coordinates of homologous landmarks captured across all specimens of interest. After the coordinates are digitised they are superimposed using either generalised or partial Procrustes superimposition (56,58,59). In the first step in the process, known as translation, all configurations are moved to the origin of the coordinate system.

Following translation, size is mitigated such that shape can be assessed independent of the bias introduced by overt size differences. During this “scaling” step a scaling factor, known as centroid size, is retained such that size can be evaluated or even reintroduced at a later stage, should it be of interest. The scaling step can also be skipped in a process called Procrustes size preservation, which is particularly useful in forensic investigations as 3-D landmarks can be analysed using traditional morphometric techniques (60). Finally, the configurations are rotated using a least squares procedures to minimise the sum of squared distances between corresponding landmarks (61).

Recently, GMM has gained considerable interest amongst anthropologists, and has been applied to numerous skeletal elements including the skull (62–65), mandible (58,65,66), pelvis (67) and scapula (55,68). Of these, the cranium has garnered the

15 most attention due to the high accuracies reported for both sex and ancestry estimation.

Several examples of GMM applications to forensic anthropological sex estimation provide evidence of the success of the methodology. Franklin et al. (3) studied SxD in Black South Africans by collecting 96 landmarks from 332 skulls and utilising the generalised Procrustes superimposition technique. Using principal components analysis, they found that lateral projection of the zygomatic bones, forehead contour, frontal profile, face shape, length of the midbasal region, and curve of the supramastoid crest were the most dimorphic features. Pretorius et al. (69) conducted a study on SxD in the same population using thin plate splines, canonical variants analyses, and relative warp plots. They focused specifically on the shape of the greater sciatic notch, flexure of the mandibular ramus, and the shape of the orbits.

The shape of the greater sciatic notch was the most dimorphic feature (93.1% accuracy in black males) and the orbits provided a better estimate of sex than did mandibular ramus flexure (73.3% versus 69.6% in black males, respectively) They also demonstrated that canonical variants analyses provided clearer results than thin plate splines for the population in question.

Similarly impressive results have been obtained for populations from other world regions. Bigoni and colleagues (63) studied a central European population from Bohemia in a similar fashion as the above mentioned studies, but they also included 39 semilandmarks along the midsagittal curve. They noted that there were no significant differences in this population in the cranium as a whole or in the basicranium, but they achieved outstanding accuracies of 100% using the shape of the nasal aperture, orbits and palate, and 99% using the midsagittal curve. Green and Curnoe (64) used GMM to demonstrate differences between the sexes in a Southeast Asian population. They found that facial breadth, particularly across the zygomatic and postorbital regions, and cranial vault breadth are especially dimorphic, and also that significant size differences are present. Using this knowledge they conducted discriminant analyses and were able to achieve 86.8% accurate sex estimation. These findings are very important, as previous studies have demonstrated size but not shape differences in this population. Ji et al. (62) focused on the orbits of a Chinese population. They identified significant sex differences in all orbital parameters except orbital height, and also found the orbits to be symmetrical. They did not determine sexing accuracies, however.

16 2.3.3.1 Semilandmark methods in geometric morphometrics

Geometric morphometrics (GMM) is based on capturing shape differences from the coordinates of homologous landmarks. It therefore faces the same limitations as traditional morphometrics when landmarks are damaged or missing, or too few are available to adequately capture shape via curves or outlines (58). To solve this, Bookstein (70) suggested the use of semilandmarks that are slid a certain distance along a curve until they attain positions that are similar to the reference structure (58,59). In this way, homologous points on curves can be compared (59). When semilandmarks slide, they do so to remove tangential variation. This can be done in two ways, either by minimising bending energy when semilandmarks are slid (in a parallel direction relative to the curve) allowing the landmark to align to the reference form, or by using the minimum Procrustes distance method that estimates the direction tangential to the curve and removes the component of the difference along the tangent whereby removing the difference in semilandmark position between the reference form and target specimen. Perez et al. (59) investigated the effectiveness of these two techniques by analysing the shape of the orbits, nasal aperture, maxilla, zygomatics and frontal bone. They concluded that the minimum Procrustes distance method was more accurate because the bending energy method resulted in larger intra- and interpopulation differences. This was believed to be due to differences in the placing of semilandmarks along the curves. Another interesting observation made in this study was that the difference between the two methods became more noticeable if an increased number of semilandmarks were used, suggesting that the number of semilandmarks should be limited as much as possible.

One of the most important advantages of GMM is that it overcomes observer subjectivity as shape is analysed statistically (63). Furthermore, GMM allows shape to be analysed independent of size. Morphological variation, as expressed through GMM, can be graphically depicted in intuitive images, and GMM can detect subtle variations that traditional metric and morphological methods cannot (3,58,63,69,71).

Disadvantages of GMM are that technical equipment and an in-depth understanding of the statistical nuances of the technique are required. Data collection can also be time consuming (3,58,69).