Biogeographic Analysis Using Geometric Morphometrics: Clines in Skull Size and Shape in a Widespread African Arboreal Monkey

Abstract

Despite the "renaissance" of biogeography in the last two decades with its central role in the study of biodiversity and evolution, and the "revolution" in morphometrics brought about by methods based on the analysis of Cartesian coordinates of anatomical landmarks, the use of geometric morphometrics in biogeographic studies has been rather limited. With this analysis we aim to provide an example of how geometric morphometrics can fruitfully be applied to the study of clinal variation in a widespread African monkey group by a simple extension of methods widely employed by macroecologists and biogeographers to multivariate shape data. Throughout the paper we aim to explain these techniques so that those who are new to them can use and adapt them for their own needs, in some cases providing specific instructions on how to perform certain operations in standard morphometrics and statistical software. Our hope is that this may stimulate morphometricians and scientists from other disciplines to explore geographic variation in size and shape using up-to-date geometric morphometric methods. The application of geometric morphometrics to ecological, biogeographic and phylogeographic studies has enormous potential for a thorough understanding of how form changes in space and time during evolution and in relation to genetic and environmental factors.

Larger mammals have longer faces because of size-related constraints on skull form

“…Asymmetry, if present is unlikely to account for more than a tiny fraction of the total variance, as suggested by a visual inspection of specimens and the absence in the literature of any reference to an evident asymmetry in the study groups. To improve the effectiveness of the visualization and the accuracy of the superimposition, however, symmetric landmarks were mirror reflected and the tiny asymmetric component of landmarks on the midplane was removed 30 . The mirror reflected landmark configuration is shown in Fig.…”

Ulnar articular surface 3-D landmarks and ecomorphology of small mammals: a case study of two early Miocene typotheres (Notoungulata) from Patagonia

“…Following Cardini et al (2010) and Abba et al (2015), the correlation between two distance matrices, euclidean distances (PCs) and procrustes distances in the full shape space, was calculated and used to determine the number of principal components to explore. The correlation coefficients were plotted onto the number of PCs, and the PC at the ''elbow'' in the plot was taken as the highest PC to retain (Cardini et al 2010). Visualisation and graphics were made using the Morpho R package 2.3.1.1 (Schlager 2013), which allowed the colour pattern to be associated with the shape changes.…”

Craniofacial evolution in polynesia: A geometric morphometric study of population diversity

“…Clinal variation was quantified by regressing size and shape variables onto latitude and longitude and environmental variables. Trend surface analysis was performed to assess for any nonlinearities (Cardini et al, 2007(Cardini et al, , 2010Legendre, 1998;Ruggiero and Kitzberger, 2004). Size and shape were regressed onto a second and third-order polynomial of latitude and longitude, removing any non-significant terms until all terms of the multi- ple regression were significant, where applicable.…”

“…The relative importance of geographic and climatic variables was quantified by partial linear regression to estimate the amount of variation of cranial size or shape that could be attributed to one set of factors (environment) once the effects of the other (geography) had been taken into account (Cardini et al, 2007;Legendre, 1998). Following the study by Cardini et al (2007Cardini et al ( , 2010, the terms of the best-fit trend surface (spatial component) and environmental variables were combined and morphological variation was partitioned into four components: (1) Nonenvironmental spatial (proportion of variance exclusively explained by geography); (2) Spatially structured environmental (proportion of variance explained by both geography and environment); (3) Non-spatial environmental (proportion of variance explained exclusively by environment); (4) Unexplained variation (proportion of variance explained by the effect of other factors).…”

“…Geography and environment are also recognized as important influences on phenotypic diversity (Cardini et al, 2007(Cardini et al, , 2010Lomolino et al, 2006). Global craniometric diversity in humans has been suggested to be largely the result of neutral evolutionary processes, with natural selection being an influence in certain extreme climatic situations (Harvati and Weaver, 2006;Relethford, 2010).…”