A multivariate ecogeographic analysis of macaque craniodental variation

Grunstra, Nicole D S; Mitterœcker, Philipp; Foley, Robert

doi:10.1002/ajpa.23439

Cited by 12 publications

(23 citation statements)

References 63 publications

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“…The landmark configurations were registered by Procrustes superimposition 82 and symmetrised by averaging original and reflected sets of landmarks for each individual. Because of the unbalanced sex composition of the groups, we corrected for sexual dimorphism by subtracting from each individual the sex-specific mean shape and than adding the overall mean 83 . The same treatment was applied to correct for sexual dimorphism in centroid size values.…”

Section: Methodsmentioning

confidence: 99%

Respiratory adaptation to climate in modern humans and Upper Palaeolithic individuals from Sungir and Mladeč

Stansfield

Mitterœcker

Vasilyev

et al. 2021

Sci Rep

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As our human ancestors migrated into Eurasia, they faced a considerably harsher climate, but the extent to which human cranial morphology has adapted to this climate is still debated. In particular, it remains unclear when such facial adaptations arose in human populations. Here, we explore climate-associated features of face shape in a worldwide modern human sample using 3D geometric morphometrics and a novel application of reduced rank regression. Based on these data, we assess climate adaptations in two crucial Upper Palaeolithic human fossils, Sungir and Mladeč, associated with a boreal-to-temperate climate. We found several aspects of facial shape, especially the relative dimensions of the external nose, internal nose and maxillary sinuses, that are strongly associated with temperature and humidity, even after accounting for autocorrelation due to geographical proximity of populations. For these features, both fossils revealed adaptations to a dry environment, with Sungir being strongly associated with cold temperatures and Mladeč with warm-to-hot temperatures. These results suggest relatively quick adaptative rates of facial morphology in Upper Palaeolithic Europe.

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Section: Methodsmentioning

confidence: 99%

Respiratory adaptation to climate in modern humans and Upper Palaeolithic individuals from Sungir and Mladeč

Stansfield

Mitterœcker

Vasilyev

et al. 2021

Sci Rep

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“…Theorists have recently endeavored to develop phylogenetic comparative methods capable of evaluating phylogenetic patterns in multivariate datasets (e.g., Adams 2014b, Adams 2014c, Adams and Collyer 2015, Bartoszek, et al 2012, Goolsby 2015, Klingenberg and Marugán-Lobón 2013, Revell and Harmon 2008. These methods are gaining prominence in the field, and are increasingly used to address evolutionary hypotheses in multivariate phenotypic datasets in a manner analogous to what has long been possible for univariate traits (e.g., Chira, et al 2018, Felice and Goswami 2017, Grunstra, et al 2018, Martinez, et al 2018, Zelditch, et al 2015. In this review, we survey the recent advances for evaluating evolutionary trends in multivariate phenotypes, highlight some biological insights discovered through use of multivariate phylogenetic comparative approaches, and identify several areas for future analytical development.…”

Section: Introductionmentioning

confidence: 99%

Phylogenetic Comparative Methods and the Evolution of Multivariate Phenotypes

Adams

Collyer

2019

Annu. Rev. Ecol. Evol. Syst.

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Evolutionary biology is multivariate, and advances in phylogenetic comparative methods for multivariate phenotypes have surged to accommodate this fact. Evolutionary trends in multivariate phenotypes are derived from distances and directions between species in a multivariate phenotype space. For these patterns to be interpretable, phenotypes should be characterized by traits in commensurate units and scale. Visualizing such trends, as is achieved with phylomorphospaces, should continue to play a prominent role in macroevolutionary analyses. Evaluating phylogenetic generalized least squares (PGLS) models (e.g., phylogenetic analysis of variance and regression) is valuable, but using parametric procedures is limited to only a few phenotypic variables. In contrast, nonparametric, permutation-based PGLS methods provide a flexible alternative and are thus preferred for high-dimensional multivariate phenotypes. Permutation-based methods for evaluating covariation within multivariate phenotypes are also well established and can test evolutionary trends in phenotypic integration. However, comparing evolutionary rates and modes in multivariate phenotypes remains an important area of future development.

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“…S6 available on Dryad). As a typical allometric pattern in primates and other placentals, muzzle length is correlated with body size and is of functional relevance (e.g., Singleton 2002 ; Frost et al 2003 ; Mitteroecker et al 2004 ; Cardini and Polly 2013 ; Grunstra et al 2018 ; van der Geer et al 2018 ). Regressing out cranial size (centroid size) from the small-scale shape data thus partially increased the consistency of the recovered phylogenetic tree with the molecular data ( Supplementary Fig.…”

Section: Discussionmentioning

confidence: 99%

Detecting Phylogenetic Signal and Adaptation in Papionin Cranial Shape by Decomposing Variation at Different Spatial Scales

et al. 2020

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This document corresponds to the worked example of the paper Detecting phylogenetic signal and adaptation in papionin cranial shape by decomposing variation at different spatial scales (Grunstra et al.). The dataset is a set of 70 2D landmarks on the midsagittal plane of the skull in 67 primates from 18 species (16 papionin taxa, 2 outgroups). The example below describes how to decompose shape variation into total, outline, and residual shape (approach 1) or into large-scale and small-scale shape (approach 2). For further details, please read the associated paper. Data preparation Install and load packages in R. library("prWarp") library("geomorph") Load the dataset papionin. This dataset comprises the coordinates of 70 two-dimensional landmarks for the 67 specimens as a 3D array. data("papionin") # load dataset species <-papionin$species # species papionin_ar <-papionin$coords # landmark coordinates k <-dim(papionin_ar)[1] # number of landmarks n_spec <-dim(papionin_ar)[3] # number of specimens n_species <-length(levels(species)) # number of species Approach 1: Total, outline, and residual shape variation In this approach the total shape variation is decomposed into the variation of outline shape and residual shape. The outline shape corresponds to a subset of the full landmark set, in which all landmarks that demarcate the boarders between bones (i.e., landmarks on sutures and synchondroses) are free to slide. The residual shape corresponds to the slid landmark coordinates of the full dataset after warping them to the mean outline shape using TPS interpolation.

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A multivariate ecogeographic analysis of macaque craniodental variation

Cited by 12 publications

References 63 publications

Respiratory adaptation to climate in modern humans and Upper Palaeolithic individuals from Sungir and Mladeč

Respiratory adaptation to climate in modern humans and Upper Palaeolithic individuals from Sungir and Mladeč

Phylogenetic Comparative Methods and the Evolution of Multivariate Phenotypes

Detecting Phylogenetic Signal and Adaptation in Papionin Cranial Shape by Decomposing Variation at Different Spatial Scales

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