The evolution of quantitative sensitivity

The ability to represent approximate quantities appears to be phylogenetically widespread, but the selective pressures and proximate mechanisms favouring this ability remain unknown. We analysed quantity discrimination data from 672 subjects across 33 bird and mammal species, using a novel Bayesian model that combined phylogenetic regression with a model of number psychophysics and random effect components. This allowed us to combine data from 49 studies and calculate the Weber fraction (a measure of quantity representation precision) for each species. We then examined which cognitive, socioecological and biological factors were related to variance in Weber fraction. We found contributions of phylogeny to quantity discrimination performance across taxa. Of the neural, socioecological and general cognitive factors we tested, cortical neuron density and domain-general cognition were the strongest predictors of Weber fraction, controlling for phylogeny. Our study is a new demonstration of evolutionary constraints on cognition, as well as of a relation between species-specific neuron density and a particular cognitive ability. This article is part of the theme issue ‘Systems neuroscience through the lens of evolutionary theory’.

Statistical bias control in typology

In this paper, we propose two new statistical controls for genealogical and areal bias in typological samples. Our test case being the effect of VO-order effect on affix position (prefixation vs. suffixation), we show how statistical modeling including a phylogenetic regression term (phylogenetic control) and a two-dimensional Gaussian Process (areal control) can be used to capture genealogical and areal effects in a large but unbalanced sample. We find that, once these biases are controlled for, VO-order has no effect on affix position. Another important finding, which is in line with previous studies, is that areal effects are as important as genealogical effects, emphasizing the importance of areal or contact control in typological studies built on language samples. On the other hand, we also show that strict probability sampling is not required with the statistical controls that we propose, as long as the sample is a variety sample large enough to cover different areas and families. This has the crucial practical consequence that it allows us to include as much of the available information as possible, without the need to artificially restrict the sample and potentially lose otherwise available information.

Long-term evolution of quantitative traits in the Drosophila melanogaster species subgroup

Quantitative genetics aims at untangling the genetic and environmental effects on phenotypic variation. Trait heritability, which summarizes the relative importance of genetic effects, is estimated at the intraspecific level, but theory predicts that heritability could influence long-term evolution of quantitative traits. The phylogenetic signal concept bears resemblance to heritability and it has often been called species-level heritability. Under certain conditions, such as trait neutrality or contribution to phylogenesis, within-species heritability and between-species phylogenetic signal should be correlated. Here, we investigate the potential relationship between these two concepts by examining the evolution of multiple morphological traits for which heritability has been estimated in Drosophila melanogaster. Specifically, we analysed 42 morphological traits in both sexes on a phylogeny inferred from 22 nuclear genes for nine species of the melanogaster subgroup. We used Pagel's λ as a measurement of phylogenetic signal because it is the least influenced by the number of analysed taxa. Pigmentation traits showed the strongest concordance with the phylogeny, but no correlation was found between phylogenetic signal and heritability estimates mined from the literature. We obtained data for multiple climatic variables inferred from the geographical distribution of each species. Phylogenetic regression of quantitative traits on climatic variables showed a significantly positive correlation with heritability. Convergent selection, the response to which depends on the trait heritability, may have led to the null association between phylogenetic signal and heritability for morphological traits in Drosophila. We discuss the possible causes of discrepancy between both statistics and caution against their confusion in evolutionary biology.

Scaling between stomatal size and density in forest plants

The size and density of stomatal pores limit the maximum rate of leaf carbon gain and water loss (gmax) in land plants. Stomatal size and density are negatively correlated at broad phylogenetic scales, such that species with small stomata tend to have greater stomatal density, but the consequences of this relationship for leaf function have been controversial. The prevailing hypothesis posits that the negative scaling of size and density arises because species that evolved higher gmax also achieved reduced allocation of epidermal area to stomata (stomatal-area minimization). Alternatively, the negative scaling of size and density might reflect the maintenance of a stable mean and variance in gmax despite variation in stomatal size and density, which would result in a higher allocation of epidermal area to achieve high gmax (stomatal-area increase). Here, we tested these hypotheses by comparing their predictions for the structure of the covariance of stomatal size and density across species, applying macroevolutionary models and phylogenetic regression to data for 2408 species of angiosperms, gymnosperms, and ferns from forests worldwide. The observed stomatal size-density scaling and covariance supported the stomatal-area increase hypothesis for high gmax. Thus, contrary to the prevailing view, higher gmax is not achieved while minimizing stomatal area allocation but requires increasing epidermal area allocated to stomata. Understanding of optimal stomatal conductance, photosynthesis, and plant water-use efficiency used in Earth System and crop productivity models will thus be improved by including the cost of higher gmax both in construction cost of stomata and opportunity cost in epidermal space.

Assessing bite force estimates in extinct mammals and archosaurs using phylogenetic predictions

ABSTRACTBite force is an ecologically important biomechanical performance measure is informative in inferring the ecology of extinct taxa. However, biomechanical modelling to estimate bite force is associated with some level of uncertainty. Here, I assess the accuracy of bite force estimates in extinct taxa using a Bayesian phylogenetic prediction model. I first fitted a phylogenetic regression model on a training set comprising extant data. The model predicts bite force from body mass and skull width while accounting for differences owning to biting position. The posterior predictive model has a 93% prediction accuracy as evaluated through leave-one-out cross-validation. I then predicted bite force in 37 species of extinct mammals and archosaurs from the posterior distribution of predictive models.Biomechanically estimated bite forces fall within the posterior predictive distributions for all except four species of extinct taxa, and are thus as accurate as that predicted from body size and skull width, given the variation inherent in extant taxa and the amount of time available for variance to accrue. Biomechanical modelling remains a valuable means to estimate bite force in extinct taxa and should be reliably informative of functional performances and serve to provide insights into past ecologies.

A test of the lateral semicircular canal correlation to head posture, diet and other biological traits in “ungulate” mammals

For over a century, researchers have assumed that the plane of the lateral semicircular canal of the inner ear lies parallel to the horizon when the head is at rest, and used this assumption to reconstruct head posture in extinct species. Although this hypothesis has been repeatedly questioned, it has never been tested on a large sample size and at a broad taxonomic scale in mammals. This study presents a comprehensive test of this hypothesis in over one hundred “ungulate” species. Using CT scanning and manual segmentation, the orientation of the skull was reconstructed as if the lateral semicircular canal of the bony labyrinth was aligned horizontally. This reconstructed cranial orientation was statistically compared to the actual head posture of the corresponding species using a dataset of 10,000 photographs and phylogenetic regression analysis. A statistically significant correlation between the reconstructed cranial orientation and head posture is found, although the plane of the lateral semicircular canal departs significantly from horizontal. We thus caution against the use of the lateral semicircular canal as a proxy to infer precisely the horizontal plane on dry skulls and in extinct species. Diet (browsing or grazing) and head-butting behaviour are significantly correlated to the orientation of the lateral semicircular canal, but not to the actual head posture. Head posture and the orientation of the lateral semicircular canal are both strongly correlated with phylogenetic history.

Reliable Phylogenetic Regressions for Multivariate Comparative Data: Illustration with the MANOVA and Application to the Effect of Diet on Mandible Morphology in Phyllostomid Bats

Understanding what shapes species phenotypes over macroevolutionary timescales from comparative data often requires studying the relationship between phenotypes and putative explanatory factors or testing for differences in phenotypes across species groups. In phyllostomid bats for example, is mandible morphology associated to diet preferences? Performing such analyses depends upon reliable phylogenetic regression techniques and associated tests (e.g., phylogenetic Generalized Least Squares, pGLS, and phylogenetic analyses of variance and covariance, pANOVA, pANCOVA). While these tools are well established for univariate data, their multivariate counterparts are lagging behind. This is particularly true for high-dimensional phenotypic data, such as morphometric data. Here, we implement much-needed likelihood-based multivariate pGLS, pMANOVA, and pMANCOVA, and use a recently developed penalized-likelihood framework to extend their application to the difficult case when the number of traits $p$ approaches or exceeds the number of species $n$. We then focus on the pMANOVA and use intensive simulations to assess the performance of the approach as $p$ increases, under various levels of phylogenetic signal and correlations between the traits, phylogenetic structure in the predictors, and under various types of phenotypic differences across species groups. We show that our approach outperforms available alternatives under all circumstances, with greater power to detect phenotypic differences across species group when they exist, and a lower risk of improperly detecting nonexistent differences. Finally, we provide an empirical illustration of our pMANOVA on a geometric-morphometric data set describing mandible morphology in phyllostomid bats along with data on their diet preferences. Overall our results show significant differences between ecological groups. Our approach, implemented in the R package mvMORPH and illustrated in a tutorial for end-users, provides efficient multivariate phylogenetic regression tools for understanding what shapes phenotypic differences across species. [Generalized least squares; high-dimensional data sets; multivariate phylogenetic comparative methods; penalized likelihood; phenomics; phyllostomid bats; phylogenetic MANOVA; phylogenetic regression.]

Pre- and post-copulatory traits working in concert: sexual dichromatism in passerines is associated with sperm morphology

Passerine birds produce costly traits under intense sexual selection, including elaborate sexually dichromatic plumage and sperm morphologies, to compete for fertilizations. Plumage and sperm traits vary markedly among species, but it is unknown if this reflects a trade-off between pre- and post-copulatory investment under strong sexual selection producing negative trait covariance, or variation in the strength of sexual selection among species producing positive covariance. Using phylogenetic regression, we analysed datasets describing plumage and sperm morphological traits for 278 passerine species. We found a significant positive relationship between sperm midpiece length and male plumage elaboration and sexual dichromatism. We did not find a relationship between plumage elaboration and testes mass. Our results do not support a trade-off between plumage and sperm traits, but may be indicative of variance among species in the strength of sexual selection to produce both brightly coloured plumage and costly sperm traits.

phylogenize: correcting for phylogeny reveals genes associated with microbial distributions

Summary Phylogenetic comparative methods are powerful but presently under-utilized ways to identify microbial genes underlying differences in community composition. These methods help to identify functionally important genes because they test for associations beyond those expected when related microbes occupy similar environments. We present phylogenize, a pipeline with web, QIIME 2 and R interfaces that allows researchers to perform phylogenetic regression on 16S amplicon and shotgun sequencing data and to visualize results. phylogenize applies broadly to both host-associated and environmental microbiomes. Using Human Microbiome Project and Earth Microbiome Project data, we show that phylogenize draws similar conclusions from 16S versus shotgun sequencing and reveals both known and candidate pathways associated with host colonization. Availability and implementation phylogenize is available at https://phylogenize.org and https://bitbucket.org/pbradz/phylogenize. Supplementary information Supplementary data are available at Bioinformatics online.

Reliable Phylogenetic Regressions for Multivariate Comparative Data: Illustration with the MANOVA and Application to the Effect of Diet on Mandible Morphology in Phyllostomid Bats

ABSTRACTUnderstanding what shapes species phenotypes over macroevolutionary time scales from comparative data requires the use of reliable phylogenetic regression techniques and associated tests (e.g. phylogenetic Generalized Least Squares, pGLS and phylogenetic analyses of variance and covariance, pANOVA, pANCOVA). While these tools are well established for univariate data, their multivariate counterparts are lagging behind. This is particularly true for high dimensional phenotypic data, such as morphometric data. Here we implement well-needed likelihood-based multivariate pGLS, pMANOVA and pMANCOVA, and use a recently-developed penalized likelihood framework to extend their application to the difficult case when the number of traits p approaches or exceeds the number of species n. We then focus on the pMANOVA and use intensive simulations to assess the performance of the approach as p increases, under various levels of phylogenetic signal and correlations between the traits, phylogenetic structure in the predictors, and under various types of phenotypic differences across species groups. We show that our approach outperforms available alternatives under all circumstances, with a greater power to detect phenotypic differences across species group when they exist, and a low risk to improperly detect inexistent differences. Finally, we provide an empirical illustration of our pMANOVA on a geometric-morphometric dataset describing mandible morphology in phyllostomid bats along with data on their diet preferences. Our approach, implemented in the R package mvMORPH, provides efficient multivariate phylogenetic regression tools for understanding what shapes phenotypic differences across species.