Evolutionary Relationships Among Robust and Gracile Australopiths: An “Evo-devo” Perspective

Gunz, Philipp

doi:10.1007/s11692-012-9185-4

Cited by 16 publications

(12 citation statements)

References 103 publications

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“…Landmarks or semilandmarks missing on only one side of the frontal bone were estimated by mirror‐imaging, based on the available paired landmarks and the symmetry axis defined by the midsagittal curve. Landmarks and semilandmarks missing on both sides or along the midsagittal, were estimated based on the thin‐plate spline algorithm during the semilandmark sliding process (Gunz et al,2009,2012; Grine et al,2010; Neubauer et al,2012b; Weber et al,2012): missing landmarks or semilandmarks were allowed to move so as to minimize the bending energy between each incomplete specimen and the sample Procrustes average shape. As many fossils were reconstructed by mirror‐imaging one side, we subsequently symmetrized (Supporting Information Fig.…”

Section: Methodsmentioning

confidence: 99%

“…Subsequently, we used developmental simulations (McNulty et al,2006; Singleton et al,2010; Neubauer et al,2010; Gunz et al,2010,2012; Gunz,2012) to predict adult shapes for Teshik‐Tash. Such developmental simulations can be computed based on size (Gunz,2012), dental stage via shape differences between group means (Neubauer et al,2010; Gunz et al,2012), or dental stage via regression (McNulty et al,2006). Here we used the dental stage via regression approach (see Discussion below).…”

Section: Methodsmentioning

confidence: 99%

“…The frontal bone encompasses two functionally different regions of the skull, the neurocranium and the upper face, which grow at different rates and different times. In modern humans, more than 90% of the adult neurocranial size is achieved by the M1 occlusion; facial growth and maturation, however, continue beyond this age 1 (Humphrey,1998; Viđarsdóttir et al,2002; Ackermann and Krovitz,2002; Cobb and O'Higgins,2004; Coqueugniot et al,2004; Guihard‐Costa and Ramírez Rozzi,2004; Mitteroecker et al,2004a,b; Viđarsdóttir and Cobb,2004; Bulygina et al,2006; Hublin and Coqueugniot,2006; Cobb and O'Higgins,2007; Coqueugniot and Hublin,2007; DeSilva and Lesnik,2008; Mitteroecker and Bookstein,2009; Neubauer et al,2009,2010; Harvati et al,2010; Gunz et al,2010,2011,2012; Coqueugniot and Hublin,2012; Leigh,2012; Neubauer and Hublin,2012; Neubauer et al,2012a). Developmental trajectories of the frontal bone are therefore the result of a combination of two developmental processes (Mitteroecker et al,2005; Mitteroecker and Bookstein,2007,2008), where size increase predates shape maturation.…”

Section: Aims Of This Studymentioning

confidence: 99%

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The Mousterian child from Teshik‐Tash is a Neanderthal: A geometric morphometric study of the frontal bone

Gunz¹,

Булыгина²

2012

American J Phys Anthropol

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In the 1930s subadult hominin remains and Mousterian artifacts were discovered in the Teshik-Tash cave in South Uzbekistan. Since then, the majority of the scientific community has interpreted Teshik-Tash as a Neanderthal. However, some have considered aspects of the morphology of the Teshik-Tash skull to be more similar to fossil modern humans such as those represented at Skhūl and Qafzeh, or to subadult Upper Paleolithic modern humans. Here we present a 3D geometric morphometric analysis of the Teshik-Tash frontal bone in the context of developmental shape changes in recent modern humans, Neanderthals, and early modern humans. We assess the phenetic affinities of Teshik-Tash to other subadult fossils, and use developmental simulations to predict possible adult shapes. We find that the morphology of the frontal bone places the Teshik-Tash child close to other Neanderthal children and that the simulated adult shapes are closest to Neanderthal adults. Taken together with genetic data showing that Teshik-Tash carried mtDNA of the Neanderthal type, as well as its occipital bun, and its shovel-shaped upper incisors, these independent lines of evidence firmly place Teshik-Tash among Neanderthals.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Aims Of This Studymentioning

confidence: 99%

See 1 more Smart Citation

The Mousterian child from Teshik‐Tash is a Neanderthal: A geometric morphometric study of the frontal bone

Gunz¹,

Булыгина²

2012

American J Phys Anthropol

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“…Allometry is the degree of covariation between size and shape (Gould 1966;Mosimann 1970), and thus describes the consequences of size changes on patterns of shape variation (Mitteroecker et al 2013;Voje et al 2014). Comparisons of allometric trajectories among species are frequently used to identify evolutionary changes in the size-shape relationship across taxa (e.g., Bookstein et al 2003;Mitteroecker et al 2004;Adams and Nistri 2010;Piras et al 2010;Gunz 2012). Additionally, evolutionary allometry may be inferred by characterizing the relationship between size and shape among species in a phylogenetic context (e.g., Monteiro and Nogueira 2011;Cardini and Polly 2013;Klingenberg and Marugán-Lobón 2013;Outomuro et al 2013b).…”

Section: A Biological Examplementioning

confidence: 99%

A Method for Assessing Phylogenetic Least Squares Models for Shape and Other High-Dimensional Multivariate Data

2014

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Studies of evolutionary correlations commonly use phylogenetic regression (i.e., independent contrasts and phylogenetic generalized least squares) to assess trait covariation in a phylogenetic context. However, while this approach is appropriate for evaluating trends in one or a few traits, it is incapable of assessing patterns in highly multivariate data, as the large number of variables relative to sample size prohibits parametric test statistics from being computed. This poses serious limitations for comparative biologists, who must either simplify how they quantify phenotypic traits, or alter the biological hypotheses they wish to examine.In this article, I propose a new statistical procedure for performing ANOVA and regression models in a phylogenetic context that can accommodate high-dimensional datasets. The approach is derived from the statistical equivalency between parametric methods using covariance matrices and methods based on distance matrices. Using simulations under Brownian motion, I show that the method displays appropriate Type I error rates and statistical power, whereas standard parametric procedures have decreasing power as data dimensionality increases. As such, the new procedure provides a useful means of assessing trait covariation across a set of taxa related by a phylogeny, enabling macroevolutionary biologists to test hypotheses of adaptation, and phenotypic change in high-dimensional datasets. K E Y W O R D S :Geometric morphometrics, macroevolution, morphological evolution, phylogenetic comparative method.In comparative biology it is generally accepted that the evaluation of evolutionary correlations among traits requires a phylogenetic perspective. Because of shared evolutionary history, species in a phylogeny are not independent (Felsenstein 1985;Harvey and Pagel 1991; Felsenstein 2004;Revell et al. 2008;Pennell and Harmon 2013). This leads to phenotypic similarities among taxa, whose expected covariance may be described in proportion to their shared ancestry under a specified model of trait evolution (Felsenstein 1985;Grafen 1989;Martins and Hansen 1997;Rohlf 2001). As a consequence, statistical procedures that assess patterns of covariation among traits from cross-species data must take the evolutionary relationships among taxa into consideration during the analysis, so that the lack of independence among species may be properly accounted for (Revell 2010). In these circumstances, when evolutionary correlations among traits are identified via phylogenetic comparative methods, such correlations provide important evidence of adaptation and inform on the evolutionary causes of phenotypic change (Garland et al. 1992;Rüber and Adams 2001;Pennell and Harmon 2013), as the potential effect of shared evolutionary history may be ruled out.Over the past several decades, numerous analytical approaches have been developed to account for phylogenetic nonindependence while assessing patterns of trait covariation (Cheverud et al. 1985;Felsenstein 1985;Grafen 1989;Martins and Hansen 1997;Diniz-F...

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“…2) recorded on the crania of 260 primate specimens (112 recent Homo sapiens, 67 Pan troglodytes, 36 Pan paniscus, 45 Gorilla gorilla) ( Table 3). The data represent a subset of the dataset used in Mitteroecker et al (2004) and Gunz (2012) and comprise only adult individuals of both sexes [details about the sample and preprocessing can be found in Gunz (2012)]. The original specimens are housed in the following institutions: the Natural History Museum in Vienna, Austria; the Institute of Anthropology, University of Zürich-Irchel, Switzerland; the Royal Museum for Central Africa in Tervuren, Belgium; and the Senckenberg Museum in Frankfurtam-Main, Germany.…”

Section: Example Datasetmentioning

confidence: 99%

Using geometric morphometric visualizations of directional selection gradients to investigate morphological differentiation

Weaver

Gunz

2018

Evolution

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Researchers studying extant and extinct taxa are often interested in identifying the evolutionary processes that have lead to the morphological differences among the taxa. Ideally, one could distinguish the influences of neutral evolutionary processes (genetic drift, mutation) from natural selection, and in situations for which selection is implicated, identify the targets of selection. The directional selection gradient is an effective tool for investigating evolutionary process, because it can relate form (size and shape) differences between taxa to the variation and covariation found within taxa. However, although most modern morphometric analyses use the tools of geometric morphometrics (GM) to analyze landmark data, to date, selection gradients have mainly been calculated from linear measurements. To address this methodological gap, here we present a GM approach for visualizing and comparing between-taxon selection gradients with each other, associated difference vectors, and "selection" gradients from neutral simulations. To exemplify our approach, we use a dataset of 347 three-dimensional landmarks and semilandmarks recorded on the crania of 260 primate specimens (112 humans, 67 common chimpanzees, 36 bonobos, 45 gorillas). Results on this example dataset show how incorporating geometric information can provide important insights into the evolution of the human braincase, and serve to demonstrate the utility of our approach for understanding morphological evolution.

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Evolutionary Relationships Among Robust and Gracile Australopiths: An “Evo-devo” Perspective

Cited by 16 publications

References 103 publications

The Mousterian child from Teshik‐Tash is a Neanderthal: A geometric morphometric study of the frontal bone

The Mousterian child from Teshik‐Tash is a Neanderthal: A geometric morphometric study of the frontal bone

A Method for Assessing Phylogenetic Least Squares Models for Shape and Other High-Dimensional Multivariate Data

Using geometric morphometric visualizations of directional selection gradients to investigate morphological differentiation

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