Morphometric Variation at Different Spatial Scales: Coordination and Compensation in the Emergence of Organismal Form

Exploring Phylogenetic Signal in Multivariate Phenotypes by Maximizing Blomberg's K

Due to the hierarchical structure of the tree of life, closely related species often resemble each other more than distantly related species; a pattern termed phylogenetic signal. Numerous univariate statistics have been proposed as measures of phylogenetic signal for single phenotypic traits, but the study of phylogenetic signal for multivariate data, as is common in modern biology, remains challenging. Here, we introduce a new method to explore phylogenetic signal in multivariate phenotypes. Our approach decomposes the data into linear combinations with maximal (or minimal) phylogenetic signal, as measured by Blomberg's K. The loading vectors of these phylogenetic components or K-components can be biologically interpreted, and scatterplots of the scores can be used as a low-dimensional ordination of the data that maximally (or minimally) preserves phylogenetic signal. We present algebraic and statistical properties, along with 2 new summary statistics, KA and KG, of phylogenetic signal in multivariate data. Simulation studies showed that KA and KG have higher statistical power than the previously suggested statistic Km⁢u⁢l⁢t, especially if phylogenetic signal is low or concentrated in a few trait dimensions. In 2 empirical applications to vertebrate cranial shape (crocodyliforms and papionins), we found statistically significant phylogenetic signal concentrated in a few trait dimensions. The finding that phylogenetic signal can be highly variable across the dimensions of multivariate phenotypes has important implications for current maximum likelihood approaches to phylogenetic signal in multivariate data.

Cortical areas associated to higher cognition drove primate brain evolution

Although intense research effort is seeking to address which brain areas fire and connect to each other to produce complex behaviors in a few living primates, little is known about their evolution, and which brain areas or facets of cognition were favored by natural selection. By developing statistical tools to study the evolution of the brain cortex at the fine scale, we found that rapid cortical expansion in the prefrontal region took place early on during the evolution of primates. In anthropoids, fast-expanding cortical areas extended to the posterior parietal cortex. In Homo, further expansion affected the medial temporal lobe and the posteroinferior region of the parietal lobe. Collectively, the fast-expanding cortical areas in anthropoids are known to form a brain network producing mind reading abilities and other higher-order cognitive functions. These results indicate that pursuing complex cognition drove the evolution of Primate brains.

On the importance of scale in evolutionary quantitative genetics

The informed use of scales and units in evolutionary quantitative genetics is often neglected, and naïve standardizations can cause misinterpretations of empirical results. A potentially influential example of such neglect can be found in the recent book by Arnold (2023. Evolutionary quantitative genetics. Oxford University Press). There, Arnold championed the use of heritability over mean-scaled genetic variance as a measure of evolutionary potential arguing that mean-scaled genetic variances are correlated with trait means while heritabilities are not. Here, we show that Arnold's empirical result is an artifact of ignoring the units in which traits are measured. More importantly, Arnold's argument mistakenly assumes that the goal of mean scaling is to remove the relationship between mean and variance. In our view, the purpose of mean scaling is to put traits with different units on a common scale that makes evolutionary changes, or their potential, readily interpretable and comparable in terms of proportions of the mean.

Trapped in the morphospace: The relationship between morphological integration and functional performance

The evolution of complex morphological structures can be characterized by the interplay between different anatomical regions evolving under functional integration in response to shared selective pressures. Using the highly derived humeral morphology of talpid moles as a model, here we test whether functional performance is linked to increased levels of evolutionary integration between humerus subunits and, if so, what the strength is of the relationship. Combining two-dimensional geometric morphometrics, phylogenetic comparative methods, and functional landscape modeling, we demonstrate that the high biomechanical performance of subterranean moles' humeri is coupled with elevated levels of integration, whereas taxa with low-performance values show intermediate or low integration. Theoretical morphs occurring in high-performance areas of the functional landscape are not occupied by any species, and show a marked drop in covariation levels, suggesting the existence of a strong relationship between integration and performance in the evolution of talpid moles' humeri. We argue that the relative temporal invariance of the subterranean environment may have contributed to stabilize humeral morphology, trapping subterranean moles in a narrow region of the landscape and impeding any attempt to reposition on a new ascending slope.

Thirty years of geometric morphometrics: Achievements, challenges, and the ongoing quest for biological meaningfulness

The foundations of geometric morphometrics were worked out about 30 years ago and have continually been refined and extended. What has remained as a central thrust and source of debate in the morphometrics community is the shared goal of meaningful biological inference through a tight connection between biological theory, measurement, multivariate biostatistics, and geometry. Here we review the building blocks of modern geometric morphometrics: the representation of organismal geometry by landmarks and semilandmarks, the computation of shape or form variables via superimposition, the visualization of statistical results as actual shapes or forms, the decomposition of shape variation into symmetric and asymmetric components and into different spatial scales, the interpretation of various geometries in shape or form space, and models of the association between shape or form and other variables, such as environmental, genetic, or behavioral data. We focus on recent developments and current methodological challenges, especially those arising from the increasing number of landmarks and semilandmarks, and emphasize the importance of thorough exploratory multivariate analyses rather than single scalar summary statistics. We outline promising directions for further research and for the evaluation of new developments, such as "landmark-free" approaches. To illustrate these methods, we analyze three-dimensional human face shape based on data from the Avon Longitudinal Study of Parents and Children (ALSPAC).

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase ( www.facebase.org , https://doi.org/10.25550/3-HXMC ) and GitHub ( https://github.com/jaydevine/MusMorph ).

A model of developmental canalization, applied to human cranial form

Developmental mechanisms that canalize or compensate perturbations of organismal development (targeted or compensatory growth) are widely considered a prerequisite of individual health and the evolution of complex life, but little is known about the nature of these mechanisms. It is even unclear if and how a “target trajectory” of individual development is encoded in the organism’s genetic-developmental system or, instead, emerges as an epiphenomenon. Here we develop a statistical model of developmental canalization based on an extended autoregressive model. We show that under certain assumptions the strength of canalization and the amount of canalized variance in a population can be estimated, or at least approximated, from longitudinal phenotypic measurements, even if the target trajectories are unobserved. We extend this model to multivariate measures and discuss reifications of the ensuing parameter matrix. We apply these approaches to longitudinal geometric morphometric data on human postnatal craniofacial size and shape as well as to the size of the frontal sinuses. Craniofacial size showed strong developmental canalization during the first 5 years of life, leading to a 50% reduction of cross-sectional size variance, followed by a continual increase in variance during puberty. Frontal sinus size, by contrast, did not show any signs of canalization. Total variance of craniofacial shape decreased slightly until about 5 years of age and increased thereafter. However, different features of craniofacial shape showed very different developmental dynamics. Whereas the relative dimensions of the nasopharynx showed strong canalization and a reduction of variance throughout postnatal development, facial orientation continually increased in variance. Some of the signals of canalization may owe to independent variation in developmental timing of cranial components, but our results indicate evolved, partly mechanically induced mechanisms of canalization that ensure properly sized upper airways and facial dimensions.

Developmental mechanisms that canalize or compensate perturbations of organismal development are a prerequisite of individual health and the evolution of complex life. However, surprisingly little is known about these mechanisms, partly because the “target trajectories” of individual development cannot be directly observed. Here we develop a statistical model of developmental canalization that allows one to estimate the strength of canalization and the amount of canalized variance in a population even if the target trajectories are unobserved. We applied these approaches to data on human postnatal craniofacial growth. Whereas overall craniofacial size was strongly canalized during the first 5 years of age, frontal sinus size did not show any signs of canalization. The relative dimensions of the nasopharynx showed strong canalization and a reduction of variance throughout postnatal development, whereas other shape features, such as facial orientation, continually increased in variance. Our results indicate evolved, partly mechanically induced mechanisms of canalization that ensure properly sized upper airways and facial dimensions.

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

Phylogenetic reconstruction based on morphometric data is hampered by homoplasies. For example, many similarities in cranial form between primate taxa more strongly reflect ecological similarities rather than phylogenetic relatedness. However, the way in which the different cranial bones constitute cranial form is, if at all, of less functional relevance and thus largely hidden from selection. We propose that these “constructional details” are better indicators of phylogenetic history than any large-scale shape feature or raw form variable. Within a geometric morphometric context, we show how to analyze the relative extent of bones independently of differences in overall shape. We also show how to decompose total shape variation into small-scale and large-scale shape variation. We apply both methods to the midsagittal cranial morphology of papionin monkeys, which are well known for the discrepancy between morphological similarities and phylogenetic relationships. We study phylogenetic signal and functional adaptation using a molecular phylogeny and contextual data on feeding ecology and locomotor behavior. As expected, total cranial shape, bone outline shape, and large-scale shape features were only weakly associated with phylogenetic distance. But the relative bone contributions and small-scale shape features were both highly correlated with phylogenetic distances. By contrast, the association with ecological and behavioral variables was strongest for the outline shape and large-scale shape features. Studies of morphological adaptation and phylogenetic history thus profit from a decomposition of shape variation into different spatial scales. [Adaptation; canalization; cranial shape; geometric morphometrics; papionini; partial warps; phylogeny.]

Ontogenetic and static allometry in the skull and cranial units of nine-banded armadillos (Cingulata: Dasypodidae: Dasypus novemcinctus)

A large part of extant and past mammalian morphological diversity is related to variation in size through allometric effects. Previous studies suggested that craniofacial allometry is the dominant pattern underlying mammalian skull shape variation, but cranial allometries were rarely characterized within cranial units such as individual bones. Here, we used 3D geometric morphometric methods to study allometric patterns of the whole skull (global) and of cranial units (local) in a postnatal developmental series of nine-banded armadillos (Dasypus novemcinctus ssp.). Analyses were conducted at the ontogenetic and static levels, and for successive developmental stages. Our results support craniofacial allometry as the global pattern along with more local allometric trends, such as the relative posterior elongation of the infraorbital canal, the tooth row reduction on the maxillary, and the marked development of nuchal crests on the supraoccipital with increasing skull size. Our study also reports allometric proportions of shape variation varying substantially among cranial units and across ontogenetic stages. The multi-scale approach advocated here allowed unveiling previously unnoticed allometric variations, indicating an untapped complexity of cranial allometric patterns to further explain mammalian morphological evolution.

Intraspecific variability in human maxillary bone modeling patterns during ontogeny

OBJECTIVES

This study compares the ontogenetic bone modeling patterns of the maxilla to the related morphological changes in three human populations to better understand how morphological variability within a species is established during ontogeny at both micro- and macroscopic levels.

MATERIALS AND METHODS

The maxillary bones of an ontogenetic sample of 145 subadult and adult individuals from Greenland (Inuit), Western Europe (France, Germany, and Portugal), and South Africa (Khoekhoe and San) were analyzed. Bone formation and resorption were quantified using histological methods to visualize the bone modeling patterns. In parallel, semilandmark geometric morphometric techniques were used on 3D models of the same individuals to capture the morphological changes. Multivariate statistics were applied and shape differences between age groups were visualized through heat maps.

RESULTS

The three populations show differences in the degree of shape change acquired during ontogeny, leading to divergences in the developmental trajectories. Only subtle population differences in the bone modeling patterns were found, which were maintained throughout ontogeny. Bone resorption in adults mirrors the pattern found in subadults, but is expressed at lower intensities.

DISCUSSION

Our data demonstrate that maxillary morphological differences observed in three geographically distinct human populations are also reflected at the microscopic scale. However, we suggest that these differences are mostly driven by changes in rates and timings of the cellular activities, as only slight discrepancies in the location of bone resorption could be observed. The shared general bone modeling pattern is likely characteristic of all Homo sapiens, and can be observed throughout ontogeny.

Evolution of the Mammalian Ear: An Evolvability Hypothesis

Encapsulated within the temporal bone and comprising the smallest elements of the vertebrate skeleton, the ear is key to multiple senses: balance, posture control, gaze stabilization, and hearing. The transformation of the primary jaw joint into the mammalian ear ossicles is one of the most iconic transitions in vertebrate evolution, but the drivers of this complex evolutionary trajectory are not fully understood. We propose a novel hypothesis: The incorporation of the bones of the primary jaw joint into the middle ear has considerably increased the genetic, regulatory, and developmental complexity of the mammalian ear. This increase in the number of genetic and developmental factors may, in turn, have increased the evolutionary degrees of freedom for independent adaptations of the different functional ear units. The simpler ear anatomy in birds and reptiles may be less susceptible to developmental instabilities and disorders than in mammals but also more constrained in its evolution. Despite the tight spatial entanglement of functional ear components, the increased "evolvability" of the mammalian ear may have contributed to the evolutionary success and adaptive diversification of mammals in the vast diversity of ecological and behavioral niches observable today. A brief literature review revealed supporting evidence for this hypothesis.

On the use of the coefficient of variation to quantify and compare trait variation

Meaningful comparison of variation in quantitative trait requires controlling for both the dimension of the varying entity and the dimension of the factor generating variation. Although the coefficient of variation (CV; standard deviation divided by the mean) is often used to measure and compare variation of quantitative traits, it only accounts for the dimension of the former, and its use for comparing variation may sometimes be inappropriate. Here, we discuss the use of the CV to compare measures of evolvability and phenotypic plasticity, two variational properties of quantitative traits. Using a dimensional analysis, we show that contrary to evolvability, phenotypic plasticity cannot be meaningfully compared across traits and environments by mean‐scaling trait variation. We further emphasize the need of remaining cognizant of the dimensions of the traits and the relationship between mean and standard deviation when comparing CVs, even when the scales on which traits are expressed allow meaningful calculation of the CV.