Abstract Modern human populations differ in developmental processes and in several phenotypic traits. However, the link between ontogenetic variation and human diversification has not been frequently addressed. Here, we analysed craniofacial ontogenies by means of geometric-morphometrics of Europeans and Southern Africans, according to dental and chronological ages. Results suggest that different adult cranial morphologies between Southern Africans and Europeans arise by a combination of processes that involve traits modified during the prenatal life and others that diverge during early postnatal ontogeny. Main craniofacial changes indicate that Europeans differ from Southern Africans by increasing facial developmental rates and extending the attainment of adult size and shape. Since other studies have suggested that native subsaharan populations attain adulthood earlier than Europeans, it is probable that facial ontogeny is linked with other developmental mechanisms that control the timing of maturation in other variables. Southern Africans appear as retaining young features in adulthood. Facial ontogeny in Europeans produces taller and narrower noses, which seems as an adaptation to colder environments. The lack of these morphological traits in Neanderthals, who lived in cold environments, seems a paradox, but it is probably the consequence of a warm-adapted faces together with precocious maturation. When modern Homo sapiens migrated into Asia and Europe, colder environments might establish pressures that constrained facial growth and development in order to depart from the warm-adapted morphology. Our results provide some answers about how cranial growth and development occur in two human populations and when developmental shifts take place providing a better adaptation to environmental constraints.

Citation: Sardi ML, Ramírez Rozzi FV (2012) Different Cranial Ontogeny in Europeans and Southern Africans. PLoS ONE 7(4): e35917. https://doi.org/10.1371/journal.pone.0035917 Editor: Carles Lalueza-Fox, Institut de Biologia Evolutiva - Universitat Pompeu Fabra, Spain Received: December 2, 2011; Accepted: March 28, 2012; Published: April 27, 2012 Copyright: © 2012 Sardi, Ramírez Rozzi. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Financial support was provided by: PICT 1822 Agencia Nacional de Promoción Científica y Técnica, Argentina [http://www.agencia.gov.ar/] and PI N531 Universidad Nacional de La Plata, Argentina [www.unlp.edu.ar]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

Introduction The variation of growth and development among modern humans has been studied since decades. Frequently these studies focused on nutritional and epidemiological aspects that influence life-history variables, such as the age of attainment of adult size, the age at menarche, age at first reproduction, etc., whereas some other studies suggest that differences in growth and development would be genetically programmed [1]. Populations of Sub-Saharan African ancestry, for instance, differ in body size and shape with respect to populations of European ancestry at similar ages and similar socioeconomic levels [1]. The former develop ossification centres and present skeletal maturation and sexual maturation at more advanced ages than the latter; however, these results have been contested [2]. Dental studies also suggest that Southern African populations are characterised by a more advanced development when they are compared with populations of European ancestry [3]–[5]. Comparing adult individuals, craniometric differences were observed in the jaw, midface and cranial base. On average, the upper nasal region is relatively more projected in Europeans, together with more retracted jaws; Southern Africans, in contrast, present low noses in low faces, some degree of prognatism, narrower midfaces and cranial bases and frontal flatness [6]–[9]. Similarities in phenotypes among individuals are produced by regularities in developmental systems but it remains unknown which developmental mechanisms does differ in order to produce variation of specific cranial structures between populations. The study of Strand Vidarsdottir et al. [10] carried on with ontogenetic series dealing with between-populations variation suggests that part of facial shape differentiation is already present in early stages of postnatal ontogeny and that postnatal development contribute to adult differentiation. Even if this study [10] included 10 human groups, some of them were represented by small sample sizes and most of the study focused on the relationship of shape versus size. All changes produced by growth and development constitute an ontogenetic trajectory. Growth results by changes in size while development by changes in shape [11]–[13] according with biological and/or chronological ages. The parameters that determine an ontogenetic trajectory are: the onset (α) and the offset (β) of growth and development, the rate of change (k) and the initial value of the trait (y 0 ), which resulted from growth and development previous to the observation [12]. The link between developmental changes and diversification among species or populations is the heterochronic approach. Heterochrony refers to evolutionary changes in rates and timing of developmental events, which modify ontogenetic trajectories of morphological units. Heterochrony has been described by formalisms of Gould [11] and Alberch et al. [12]. Any modification in α, k and β of a given trait, traditionally measured by a single variable, from one species to other [11]–[13] or from one population to other [14] indicates a heterochronic change. This concept as well as analytical approaches involved underwent several reformulations [13], leading to some confusions. In the last decades, most of the studies of biological form are based on landmark configuration and shape is quantified by Principal Component Analysis (PCA) after a Procrustes superimposition. Some scholars have suggested that in multivariate comparisons Alberch's et al. terminology [12] cannot be used and some controversy has arisen because there is no consensus about how to interpret ontogenetic trajectories and the dissociation between size, shape and time from multivariate data. On the one hand, Mitteroecker et al. [17], [18] evaluate ontogenetic changes in a shape space between species. These authors state that a change can only be interpreted as heterochrony when their trajectories are identical in the shape space, but differ just in the extension, which indicates that the offset of the development occurs at different time or size. One requisite is that the shape space encompasses all PCs since, according with Mitteroecker et al. [17], [18], individual PCs are statistical constructions and they cannot be directly interpreted. On the other hand, Lieberman et al. [19] consider that an individual PC derived from geometric-morphometric data is an adequate measure of shape because each PC is statistically independent, being useful to derive testable hypotheses about developmental covariation among characters [19]. Lieberman et al. [19] interpret heterochronies from the analysis of single PCs following the method proposed by Alberch's et al. [12] and reinterpreted by Alba [20]. Lieberman et al. [19] state that the requisite for indentifying heterochronies proposed by Mitteroecker et al. [17], [18] is too stringent since the multivariate analysis will almost always result in divergence of one or more PCs, even in two closely related species. Furthermore, the approach of Mitteroecker et al. [17], [18] does not include any measure of ontogenetic time (biological or chronological age), rendering difficult the assessment of heterochronies. Indeed, allometries (size-related shape changes) are sometimes taken as a surrogate of time, but this not always produces similar results because changes in the association between size and shape may be independent of that between shape and age [13], [19]. When age is not available, it has been usual to compare ontogenetic series to explain morphologic divergence, avoiding inferences about heterochronies [21]–[23]. Different approaches can lead to very contradictory interpretations, as occurred in the evaluation of heterochronies between bonobos and chimpanzees. Whereas Mitteroecker et al. [17], [18] explained variation between both species as result of non heterochronic transformations, Lieberman et al. [19], who used biological age as reference for size and shape modifications, suggested that bonobo is paedomorphic relative to chimpanzee due to initial shape underdevelopment. In this work, we assess craniofacial changes throughout ontogeny in two human populations -Western Europeans and Southern Africans- by means of geometric-morphometric methods. Since we agree with Lieberman's et al. [19], we follow their approach in order to examine main patterns of variation in ontogenetic data. Two null hypotheses are stated: a) Southern Africans and Europeans present similar rates of cranial growth and development, and b) they undergo the offset of growth and development at similar age.

Methods Two cranial ontogenetic series derived from individuals whose age at death is between 0–39 years old were studied (Table 5). The West European sample encompasses, for the main part, Portuguese cemetery-derived individuals, which are housed at the Museo Antropologico, of the University of Coimbra (Portugal). A smaller proportion of this sample is composed of cadaver-derived skulls from French individuals, which are housed at Musée de L'Homme (France). Sex and age at death is known through cemeteries archives and direct observation of cadavers in the case of sex. PPT PowerPoint slide

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larger image TIFF original image Download: Table 5. Sample distribution according with chronological ages. https://doi.org/10.1371/journal.pone.0035917.t005 The second sample encompasses South African individuals of Bantu origins. The cranial material belongs to the Dart collection housed at the University of Witwatersrand (Johannesburg, South Africa). This collection comprises skulls of cadaver-derived origins. Sex was assessed by direct observation, whereas age at death was estimated by unknown methods [43]. Since chronological age may be biased in the Dart collection, dental maturation was recorded according with a ranking (Table 6) in both collections, which is a good proxy of biological development. Each dental class was established when some teeth are fully emerged. Thus, morphometric analyses were carried out considering as reference both chronological and biological (dental) ages. PPT PowerPoint slide

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larger image TIFF original image Download: Table 6. Ranking of dental maturation and sample distribution. https://doi.org/10.1371/journal.pone.0035917.t006 Thirty three-dimensional (3D) landmarks, located in the vault, basicranium, and face (Table 7) were registered with Microscribe on the left side of the skull by one of the authors (M.L.S.). Wire-frames were built with landmarks located either on the face or neurocranium (Table 7). PPT PowerPoint slide

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larger image TIFF original image Download: Table 7. Landmarks registered with Microscribe on the left side of the skull. https://doi.org/10.1371/journal.pone.0035917.t007 All 3D coordinates of landmarks were analysed by geometric-morphometric methods. Geometric-morphometrics suit well with the analysis and representation of the relationships among size and shape because it enables the evaluation of heterochronies since the Procrustes superimposition provides measures of shape once all information due to scale, location and rotation was removed; and it provides a measure of size –the centroid size- that is uncorrelated with shape. Cuadratic distances between homologous landmarks were minimised by means of Generalised Procrustes Analysis (GPA) with Morphologika. After Procrustes transformation, landmark configurations were analysed by means of a Principal Component Analysis (PCA). GPA and PCA enabled to obtain scores of shape variation and the centroid size (CS). Transformation grids were built to visualize morphologic changes. Neurocranium and face were analysed separately because both morphological units present different embryological origins and they present different developmental rates [44], [45]. The neurocranium encompasses two main skeletal structures –the vault and the basicranium- of different embryological origins, however growth rates are similar and associated to brain growth. From a phylogenetic perspective, some developmental shifts in both the neurocranium and the face can explain morphologic diversity among mammals [46] and, more specifically, among primates [19], [47]. Individuals were plotted according with size (CS) and shape (PCs) variables against chronological and dental ages. In order to visualize trajectories according with chronological age, the smoothing spline was adjusted with Jump 5 (SAS Institute Inc.). This method requires the definition of the smoothing parameter λ, which establishes the trade-off between the bias and the variance along a trajectory. Some λ were explored but 10 were chosen by visual inspection. Greater detail is provided in those PCs that account for greatest percentage of variance. Statistical analyses were done with an alpha level of 0.05 using with Systat 10.2 (Systat Software Inc.) and Statistica (Statsoft Inc.) softwares. Differences among adults were tested with ANOVA. In order to test for change of size against age, shape against age and shape against size, within-populations regression lines were adjusted after the transformation of chronological age and centroid size into natural logarithms to get linear distributions. Equality in trajectories was evaluated by means of ANCOVA. Firstly, ANCOVA for testing the homogeneity of slopes was performed introducing the interaction term between the covariate and the grouping variable. Population was the grouping variable, log-chronological age and log-centroid size were covariates and shape variables (PCs) were the dependent variables; log-centroid size was also a dependent variable using log-chronological age as a covariate. A non significant interaction between the grouping variable and the covariate indicates that the relation between the covariate and the response variable Y does not differ between groups. When slopes did not differ, a second ANCOVA pooling the regression slopes (removing the interaction term) was performed. This enabled to test for differences in y-adjusted values for any x-value, which is also a test or equality of populations intercepts [48]. When slopes and intercepts do not differ, trajectories are identical and potential adult variation may result from the extension or truncation of trajectories; but if intercepts differ, it is probably due to differentiation generated during prenatal life. A significant interaction, in contrast, indicates that slopes differ. When slopes differ significantly, certain values of X (i.e. age) were chosen and both ANCOVA methods were repeated with and without the interaction term in order to determine the regions of significance [48]. Significant slopes can be associated with non-significant intercepts, which may indicate that both groups are not different during first stages of postnatal ontogeny and they diverge later. If the intercept also differs, no assumption about ontogeny can be done because the differentiation between intercepts is not maintained for other values of X [48]. In order to evaluate the offset of growth and development, individuals of different chronological ages in each population were compared with ANOVA and Dunnett's test (one tail). The Dunnett's t test is a method for comparing several group means to a control mean, which is useful to look for significant differences of those individuals that are older than 12 years old with respect to the adult reference. Adults encompass individuals aged between 25 and 39. Those individuals aged from 13 to 24 were grouped into 13–14, 15–16, 17–18, 19–20, 21–22, 23–24 classes in order to get greater sample sizes. When dental age was used, adults are those individuals belonging to dental class 8. These ones were compared only with those of dental class 7 which approximately corresponds to post-pubertal stage, given that M2 is fully emerged around 12.5–13.5 years [49]. Differences between means were compared with ANOVA.

Acknowledgments We are indebted to P. Mennecier, M.E. Cunha, S. Wasterlain, N. Pather, P. Mamiane who provided access to collections and to anonymous reviewers who made corrections and suggestions that improved significantly this paper. Much of this work was improved by comments and help from Marisol Anzelmo, Amandine Blin, Pablo Sardi, Jimena Barbeito-Andrés, Fernando Ventrice, Yves Le Bouc and Evelia Oyhenart.

Author Contributions Conceived and designed the experiments: MLS FVRR. Performed the experiments: MLS. Analyzed the data: MLS. Wrote the paper: MLS FVRR.