Fast Bayesian Inference of Phylogenies from Multiple Continuous Characters

Time-scaled phylogenetic trees are an ultimate goal of evolutionary biology and a necessary ingredient in comparative studies. The accumulation of genomic data has resolved the tree of life to a great extent, yet timing evolutionary events remain challenging if not impossible without external information such as fossil ages and morphological characters. Methods for incorporating morphology in tree estimation have lagged behind their molecular counterparts, especially in the case of continuous characters. Despite recent advances, such tools are still direly needed as we approach the limits of what molecules can teach us. Here, we implement a suite of state-of-the-art methods for leveraging continuous morphology in phylogenetics, and by conducting extensive simulation studies we thoroughly validate and explore our methods' properties. While retaining model generality and scalability, we make it possible to estimate absolute and relative divergence times from multiple continuous characters while accounting for uncertainty. We compile and analyze one of the most data-type diverse data sets to date, comprised of contemporaneous and ancient molecular sequences, and discrete and continuous morphological characters from living and extinct Carnivora taxa. We conclude by synthesizing lessons about our method's behavior, and suggest future research venues.

Surfperches versus Damselfishes: Trophic Evolution in Closely Related Pharyngognath Fishes with Highly Divergent Reproductive Strategies

Surfperches and damselfishes are very closely related ovalentarians with large reproductive differences. Damselfishes are typical of most Ovalentaria in that they lay demersal eggs that hatch into small, free-feeding larvae. Surfperches are unusual among ovalentarians and most acanthomorphs in having prolonged internal development. They are born at an advanced stage, some as adults, and bypass the need to actively feed throughout an extended period of ontogeny. Damselfishes and surfperches possess the same modifications of the fifth branchial arch that allow them to perform advanced food processing within the pharynx. This condition (pharyngognathy) has large effects on the evolution of feeding mechanics and trophic ecology. Although the evolution of pharyngognaths has received considerable attention, the effects of different reproductive strategies on their diversification have not been examined. We compared head shape evolution in surfperches and damselfishes using geometric morphometrics, principal component analyses, and multiple phylogenetic-comparative techniques. We found that they have similar mean head shapes, that their primary axes of shape variation are comparable and distinguish benthic-feeding and pelagic-feeding forms in each case, and that, despite large differences in crown divergence times, their head shape disparities are not significantly different. Several lines of evidence suggest that evolution has been more constrained in damselfishes: Head shape is evolving faster in surfperches, more anatomical traits have undergone correlated evolution in damselfishes, there is significant phylogenetic signal in damselfish evolution (but not surfperches), and damselfishes exhibit significant allometry in head shape that is not present in surfperches.

A new approach to exploratory data analysis in hominin phylogenetic reconstruction

The phylogenetic relationships between fossil hominin taxa have been a contentious topic for decades. Recent discoveries of new taxa, rather than resolving the issue, have only further confused it. Compounding this problem are the limitations of some of the tools frequently used by paleoanthropologists to analyze these relationships. Most commonly, phylogenetic questions are investigated using analytical methods such as maximum parsimony and Bayesian analysis. While these are useful analytical tools, these tree-building methods can have limitations when investigating taxa that may have complex evolutionary histories. Exploratory data analysis can provide information about patterns in a dataset that are obscured by tree-based methods. These patterns include phylogenetic signal conflict, which is not depicted in tree-based methods. Signal conflict can have a number of sources, including methodological issues with character choice, taxonomic issues, homoplasy, and gene flow between taxa. In this study, an exploratory data analysis of fossil hominin morphological data is conducted using the tree-based analytical method neighbor-joining and the network-based analytical method neighbor-net with the goal of visualizing phylogenetic signal conflict within a hominin morphological data set. The data set is divided into cranial regions, and each cranial region is analyzed individually to investigate which regions of the skull contain the highest levels of signal conflict. Results of this analysis show that conflicting phylogenetic signals are present in the hominin fossil record during the relatively speciose period between 3 and 1 Ma, and they also indicate that levels of signal conflict vary by cranial region. Possible sources of these conflicting signals are then explored. Exploratory data analyses such as this can be a useful tool in generating phylogenetic hypotheses and in refining character choice. This study also highlights the value network-based approaches can bring to the hominin phylogenetic analysis toolkit.

The relationship between sternum variation and mode of locomotion in birds

BACKGROUND

The origin of powered avian flight was a locomotor innovation that expanded the ecological potential of maniraptoran dinosaurs, leading to remarkable variation in modern birds (Neornithes). The avian sternum is the anchor for the major flight muscles and, despite varying widely in morphology, has not been extensively studied from evolutionary or functional perspectives. We quantify sternal variation across a broad phylogenetic scope of birds using 3D geometric morphometrics methods. Using this comprehensive dataset, we apply phylogenetically informed regression approaches to test hypotheses of sternum size allometry and the correlation of sternal shape with both size and locomotory capabilities, including flightlessness and the highly varying flight and swimming styles of Neornithes.

RESULTS

We find evidence for isometry of sternal size relative to body mass and document significant allometry of sternal shape alongside important correlations with locomotory capability, reflecting the effects of both body shape and musculoskeletal variation. Among these, we show that a large sternum with a deep or cranially projected sternal keel is necessary for powered flight in modern birds, that deeper sternal keels are correlated with slower but stronger flight, robust caudal sternal borders are associated with faster flapping styles, and that narrower sterna are associated with running abilities. Correlations between shape and locomotion are significant but show weak explanatory power, indicating that although sternal shape is broadly associated with locomotory ecology, other unexplored factors are also important.

CONCLUSIONS

These results display the ecological importance of the avian sternum for flight and locomotion by providing a novel understanding of sternum form and function in Neornithes. Our study lays the groundwork for estimating the locomotory abilities of paravian dinosaurs, the ancestors to Neornithes, by highlighting the importance of this critical element for avian flight, and will be useful for future work on the origin of flight along the dinosaur-bird lineage.

Novel neuroanatomical integration and scaling define avian brain shape evolution and development

How do large and unique brains evolve? Historically, comparative neuroanatomical studies have attributed the evolutionary genesis of highly encephalized brains to deviations along, as well as from, conserved scaling relationships among brain regions. However, the relative contributions of these concerted (integrated) and mosaic (modular) processes as drivers of brain evolution remain unclear, especially in non-mammalian groups. While proportional brain sizes have been the predominant metric used to characterize brain morphology to date, we perform a high-density geometric morphometric analysis on the encephalized brains of crown birds (Neornithes or Aves) compared to their stem taxa—the non-avialan coelurosaurian dinosaurs and Archaeopteryx. When analyzed together with developmental neuroanatomical data of model archosaurs (Gallus, Alligator), crown birds exhibit a distinct allometric relationship that dictates their brain evolution and development. Furthermore, analyses by neuroanatomical regions reveal that the acquisition of this derived shape-to-size scaling relationship occurred in a mosaic pattern, where the avian-grade optic lobe and cerebellum evolved first among non-avialan dinosaurs, followed by major changes to the evolutionary and developmental dynamics of cerebrum shape after the origin of Avialae. Notably, the brain of crown birds is a more integrated structure than non-avialan archosaurs, implying that diversification of brain morphologies within Neornithes proceeded in a more coordinated manner, perhaps due to spatial constraints and abbreviated growth period. Collectively, these patterns demonstrate a plurality in evolutionary processes that generate encephalized brains in archosaurs and across vertebrates.

Sensory adaptations reshaped intrinsic factors underlying morphological diversification in bats

Background

Morphological evolution may be impacted by both intrinsic (developmental, constructional, physiological) and extrinsic (ecological opportunity and release) factors, but can intrinsic factors be altered by adaptive evolution and, if so, do they constrain or facilitate the subsequent diversification of biological form? Bats underwent deep adaptive divergences in skull shape as they evolved different sensory modes; here we investigate the potential impact of this process on two intrinsic factors that underlie morphological variation across organisms, allometry, and modularity.

Results

We use comparative phylogenetic and morphometric approaches to examine patterns of evolutionary allometry and modularity across a 3D geometric morphometric dataset spanning all major bat clades. We show that allometric relationships diverge between echolocators and visually oriented non-echolocators and that the evolution of nasal echolocation reshaped the modularity of the bat cranium.

Conclusions

Shifts in allometry and modularity may have significant consequences on the diversification of anatomical structures, as observed in the bat skull.

BEExact: a Metataxonomic Database Tool for High-Resolution Inference of Bee-Associated Microbial Communities

High-throughput 16S rRNA gene sequencing technologies have robust potential to improve our understanding of bee (Hymenoptera: Apoidea)-associated microbial communities and their impact on hive health and disease. Despite recent computation algorithms now permitting exact inferencing of high-resolution exact amplicon sequence variants (ASVs), the taxonomic classification of these ASVs remains a challenge due to inadequate reference databases. To address this, we assemble a comprehensive data set of all publicly available bee-associated 16S rRNA gene sequences, systematically annotate poorly resolved identities via inclusion of 618 placeholder labels for uncultivated microbial dark matter, and correct for phylogenetic inconsistencies using a complementary set of distance-based and maximum likelihood correction strategies. To benchmark the resultant database (BEExact), we compare performance against all existing reference databases in silico using a variety of classifier algorithms to produce probabilistic confidence scores. We also validate realistic classification rates on an independent set of ∼234 million short-read sequences derived from 32 studies encompassing 50 different bee types (36 eusocial and 14 solitary). Species-level classification rates on short-read ASVs range from 80 to 90% using BEExact (with ∼20% due to "bxid" placeholder names), whereas only ∼30% at best can be resolved with current universal databases. A series of data-driven recommendations are developed for future studies. We conclude that BEExact (https://github.com/bdaisley/BEExact) enables accurate and standardized microbiota profiling across a broad range of bee species-two factors of key importance to reproducibility and meaningful knowledge exchange within the scientific community that together, can enhance the overall utility and ecological relevance of routine 16S rRNA gene-based sequencing endeavors.IMPORTANCE The failure of current universal taxonomic databases to support the rapidly expanding field of bee microbiota research has led to many investigators relying on "in-house" reference sets or manual classification of sequence reads (usually based on BLAST searches), often with vague identity thresholds and subjective taxonomy choices. This time-consuming, error- and bias-prone process lacks standardization, cripples the potential for comparative cross-study analysis, and in many cases is likely to incorrectly sway study conclusions. BEExact is structured on and leverages several complementary bioinformatic techniques to enable refined inference of bee host-associated microbial communities without any other methodological modifications necessary. It also bridges the gap between current practical outcomes (i.e., phylotype-to-genus level constraints with 97% operational taxonomic units [OTUs]) and the theoretical resolution (i.e., species-to-strain level classification with 100% ASVs) attainable in future microbiota investigations. Other niche habitats could also likely benefit from customized database curation via implementation of the novel approaches introduced in this study.

ESTIMATION OF CELL LINEAGE TREES BY MAXIMUM-LIKELIHOOD PHYLOGENETICS

CRISPR technology has enabled cell lineage tracing for complex multicellular organisms through insertion-deletion mutations of synthetic genomic barcodes during organismal development. To reconstruct the cell lineage tree from the mutated barcodes, current approaches apply general-purpose computational tools that are agnostic to the mutation process and are unable to take full advantage of the data's structure. We propose a statistical model for the CRISPR mutation process and develop a procedure to estimate the resulting tree topology, branch lengths, and mutation parameters by iteratively applying penalized maximum likelihood estimation. By assuming the barcode evolves according to a molecular clock, our method infers relative ordering across parallel lineages, whereas existing techniques only infer ordering for nodes along the same lineage. When analyzing transgenic zebrafish data from McKenna, Findlay and Gagnon et al. (2016), we find that our method recapitulates known aspects of zebrafish development and the results are consistent across samples.

Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

BACKGROUND

Bird plumage exhibits a diversity of colors that serve functional roles ranging from signaling to camouflage and thermoregulation. However, birds must maintain a balance between evolving colorful signals to attract mates, minimizing conspicuousness to predators, and optimizing adaptation to climate conditions. Examining plumage color macroevolution provides a framework for understanding this dynamic interplay over phylogenetic scales. Plumage evolution due to a single overarching process, such as selection, may generate the same macroevolutionary pattern of color variation across all body regions. In contrast, independent processes may partition plumage and produce region-specific patterns. To test these alternative scenarios, we collected color data from museum specimens of an ornate clade of birds, the Australasian lorikeets, using visible-light and UV-light photography, and comparative methods. We predicted that the diversification of homologous feather regions, i.e., patches, known to be involved in sexual signaling (e.g., face) would be less constrained than patches on the back and wings, where new color states may come at the cost of crypsis. Because environmental adaptation may drive evolution towards or away from color states, we tested whether climate more strongly covaried with plumage regions under greater or weaker macroevolutionary constraint.

RESULTS

We found that alternative macroevolutionary models and varying rates best describe color evolution, a pattern consistent with our prediction that different plumage regions evolved in response to independent processes. Modeling plumage regions independently, in functional groups, and all together showed that patches with similar macroevolutionary models clustered together into distinct regions (e.g., head, wing, belly), which suggests that plumage does not evolve as a single trait in this group. Wing patches, which were conserved on a macroevolutionary scale, covaried with climate more strongly than plumage regions (e.g., head), which diversified in a burst.

CONCLUSIONS

Overall, our results support the hypothesis that the extraordinary color diversity in the lorikeets was generated by a mosaic of evolutionary processes acting on plumage region subsets. Partitioning of plumage regions in different parts of the body provides a mechanism that allows birds to evolve bright colors for signaling and remain hidden from predators or adapt to local climatic conditions.

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.]

Integration of skeletal traits in some passerines: impact (or the lack thereof) of body mass, phylogeny, diet and habitat

Morphological integration of the bird skeleton is of great interest because it relates to issues of specialization, plasticity, and rate of evolutionary transformations of a skeleton as a whole and its anatomical regions. Despite growing interest, the integration and modularity of the skeleton of birds, in general, remain little studied. We evaluated the change of relative sizes and integration of shapes of skull, sternum and pelvis, and factors that influence the covariation of these regions among passerines. Results of both standard and phylogenetic reduced major axis showed that the relative lengths of the most studied skeletal traits were largely determined by body mass. The length of the skull scaled isometrically on body mass, and the lengths of both synsacrum and ilium showed positive allometry. Within the skull, beak length was positively allometric, whereas cranium length was negatively allometric with body mass. We found the presence of covariation between shapes of skull, sternum and pelvis using standard partial least squares (PLS) analysis and absence of covariation between most of these blocks using evolutionary PLS analysis on phylogenetic independent contrasts. Evolutionary integration is confirmed only for shapes of skull and pelvis (dorsal view).

Convergent Evolution of Claw Shape in a Transcontinental Lizard Radiation

Species occupying similar selective environments often share similar phenotypes as the result of natural selection. Recent discoveries, however, have led to the understanding that phenotypes may also converge for other reasons than recurring selection. We argue that the vertebrate claw system constitutes a promising but understudied model system for testing the adaptive nature of phenotypic, functional, and genetic convergence. In this study, we combine basic morphometrics and advanced techniques in form analysis to examine claw shape divergence in a transcontinental lizard radiation (Lacertidae). We find substantial interspecific variation in claw morphology and phylogenetic comparative statistics reveal a strong correlation with structural habitat use: ground-dwelling species living in open areas are equipped with long, thick, weakly curved, slender-bodied claws, whereas climbing species carry high, short, strongly curved, full-bodied claws. Species occupying densely vegetated habitats tend to carry intermediately shaped claws. Evolutionary models suggest that claw shape evolves toward multiple adaptive peaks, with structural habitat use pulling species toward a specific selective optimum. Contrary to findings in several other vertebrate taxa, our analyses indicate that environmental pressures, not phylogenetic relatedness, drive convergent evolution of similarly shaped claws in lacertids. Overall, our study suggests that lacertids independently evolved similarly shaped claws as an adaptation to similar structural environments in order to cope with the specific locomotory challenges posed by the habitat. Future biomechanical studies that link form and function in combination with genomic and development research will prove valuable in better understanding the adaptive significance of claw shape divergence.

Phylogenetic Comparative Methods and the Evolution of Multivariate Phenotypes

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.

Deciphering African late middle Pleistocene hominin diversity and the origin of our species

The origin of Homo sapiens remains a matter of debate. The extent and geographic patterning of morphological diversity among Late Middle Pleistocene (LMP) African hominins is largely unknown, thus precluding the definition of boundaries of variability in early H. sapiens and the interpretation of individual fossils. Here we use a phylogenetic modelling method to predict possible morphologies of a last common ancestor of all modern humans, which we compare to LMP African fossils (KNM-ES 11693, Florisbad, Irhoud 1, Omo II, and LH18). Our results support a complex process for the evolution of H. sapiens, with the recognition of different, geographically localised, populations and lineages in Africa - not all of which contributed to our species' origin. Based on the available fossils, H. sapiens appears to have originated from the coalescence of South and, possibly, East-African source populations, while North-African fossils may represent a population which introgressed into Neandertals during the LMP.

Ecomorphological diversification in squamates from conserved pattern of cranial integration

Factors intrinsic and extrinsic to organisms dictate the course of morphological evolution but are seldom considered together in comparative analyses. Among vertebrates, squamates (lizards and snakes) exhibit remarkable morphological and developmental variations that parallel their incredible ecological spectrum. However, this exceptional diversity also makes systematic quantification and analysis of their morphological evolution challenging. We present a squamate-wide, high-density morphometric analysis of the skull across 181 modern and extinct species to identify the primary drivers of their cranial evolution within a unified, quantitative framework. Diet and habitat preferences, but not reproductive mode, are major influences on skull-shape evolution across squamates, with fossorial and aquatic taxa exhibiting convergent and rapid changes in skull shape. In lizards, diet is associated with the shape of the rostrum, reflecting its use in grasping prey, whereas snakes show a correlation between diet and the shape of posterior skull bones important for gape widening. Similarly, we observe the highest rates of evolution and greatest disparity in regions associated with jaw musculature in lizards, whereas those forming the jaw articulation evolve faster in snakes. In addition, high-resolution ancestral cranial reconstructions from these data support a terrestrial, nonfossorial origin for snakes. Despite their disparate evolutionary trends, lizards and snakes unexpectedly share a common pattern of trait integration, with the highest correlations in the occiput, jaw articulation, and palate. We thus demonstrate that highly diverse phenotypes, exemplified by lizards and snakes, can and do arise from differential selection acting on conserved patterns of phenotypic integration.

Estimating Correlated Rates of Trait Evolution with Uncertainty

Correlated evolution among traits, which can happen due to genetic constraints, ontogeny, and selection, can have an important impact on the trajectory of phenotypic evolution. For example, shifts in the pattern of evolutionary integration may allow the exploration of novel regions of the morphospace by lineages. Here, we use phylogenetic trees to study the pace of evolution of several traits and their pattern of evolutionary correlation across clades and over time. We use regimes mapped to the branches of the phylogeny to test for shifts in evolutionary integration while incorporating the uncertainty related to trait evolution and ancestral regimes with joint estimation of all parameters of the model using Bayesian Markov chain Monte Carlo. We implemented the use of summary statistics to test for regime shifts based on a series of attributes of the model that can be directly relevant to biological hypotheses. In addition, we extend Felsenstein's pruning algorithm to the case of multivariate Brownian motion models with multiple rate regimes. We performed extensive simulations to explore the performance of the method under a series of scenarios. Finally, we provide two test cases; the evolution of a novel buccal morphology in fishes of the family Centrarchidae and a shift in the trajectory of evolution of traits during the radiation of anole lizards to and from the Caribbean islands. [Anolis; Centrarchidae; comparative methods; evolutionary integration; evolutionary rates; modularity; pruning algorithm.].

Bayesian Estimation of Species Divergence Times Using Correlated Quantitative Characters

Discrete morphological data have been widely used to study species evolution, but the use of quantitative (or continuous) morphological characters is less common. Here, we implement a Bayesian method to estimate species divergence times using quantitative characters. Quantitative character evolution is modeled using Brownian diffusion with character correlation and character variation within populations. Through simulations, we demonstrate that ignoring the population variation (or population “noise”) and the correlation among characters leads to biased estimates of divergence times and rate, especially if the correlation and population noise are high. We apply our new method to the analysis of quantitative characters (cranium landmarks) and molecular data from carnivoran mammals. Our results show that time estimates are affected by whether the correlations and population noise are accounted for or ignored in the analysis. The estimates are also affected by the type of data analyzed, with analyses of morphological characters only, molecular data only, or a combination of both; showing noticeable differences among the time estimates. Rate variation of morphological characters among the carnivoran species appears to be very high, with Bayesian model selection indicating that the independent-rates model fits the morphological data better than the autocorrelated-rates model. We suggest that using morphological continuous characters, together with molecular data, can bring a new perspective to the study of species evolution. Our new model is implemented in the MCMCtree computer program for Bayesian inference of divergence times.

Speciation Rate Is Independent of the Rate of Evolution of Morphological Size, Shape, and Absolute Morphological Specialization in a Large Clade of Birds

Whether ecological differences between species evolve in parallel with lineage diversification is a fundamental issue in evolutionary biology. These processes might be connected if conditions that favor the proliferation of species, such as release from competitors, facilitate the evolution of novel ecological relationships. Despite this, phylogenetic studies do not consistently identify such a connection. Conversely, if higher diversity caused species to become increasingly specialized ecologically, then lineage diversification might become dissociated from ecological diversification. In this analysis, we ask whether the rate of lineage diversification in a large clade of birds is correlated with morphological specialization and with rates of morphological evolution. We find that morphological variation is related to species richness within clades but that rates of morphological evolution are decoupled from the rate of lineage diversification. Additionally, morphological specialization within lineages is independent of the rate at which lineages diversify, with the results apparently robust against false negative inference. This dissociation is likely a consequence of the major ecomorphological differences between avian clades arising early in their evolutionary history, with comparatively little variation added subsequently, while avian diversification has been driven predominantly by geographic isolation and sexual selection. Accordingly, biodiversity appears to be limited by the extent to which taxa can subdivide exploited regions of ecological space and not just overall ecological opportunity.

Scent matters: differential contribution of scent to insect response in flowers with insect vs. wind pollination traits

BACKGROUND AND AIMS

Growing experimental evidence that floral scent is a key contributor to pollinator attraction supports its investigation as a component of the suite of floral traits that result from pollinator-mediated selection. Yet, the fate of floral scent during the transition out of biotic into abiotic pollination has rarely been tested. In the case of wind pollination, this is due not only to its rarer incidence among flowering plants compared with insect pollination, but also to the scarcity of systems amenable to genus-level comparisons. Thalictrum (Ranunculaceae), with its multiple transitions from insect to wind pollination, offers a unique opportunity to test interspecific changes in floral fragrance and their potential impact on pollinator attraction.

METHODS

First, the Thalictrum phylogeny was revised and the ancestral character state of pollination mode was reconstructed. Then, volatile organic compounds (VOCs) that comprise the scent bouquets of flowers from 11 phylogenetically representative wind- and insect-pollinated species were characterized and compared. Finally, to test the hypothesis that scent from insect-pollinated flowers elicits a significantly greater response from potential pollinators than that from wind-pollinated flowers, electroantennograms (EAGs) were performed on Bombus impatiens using whole flower extracts.

KEY RESULTS

Phylogenetic reconstruction of the pollination mode recovered 8-10 transitions to wind pollination from an ancestral insect pollination state and two reversals to insect pollination. Biochemical and multivariate analysis showed that compounds are distinct by species and only partially segregate with pollination mode, with no significant phylogenetic signal on scent composition. Floral VOCs from insect-pollinated Thalictrum elicited a larger antennal response from potential insect pollinators than those from wind-pollinated congeners.

CONCLUSIONS

An evolutionary scenario is proposed where an ancestral ability of floral fragrance to elicit an insect response through the presence of specific compounds was independently lost during the multiple evolutionary transitions to wind pollination in Thalictrum.

A Penalized Likelihood Framework for High-Dimensional Phylogenetic Comparative Methods and an Application to New-World Monkeys Brain Evolution

Working with high-dimensional phylogenetic comparative data sets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits $p $ approaches the number of species $n $ and because some computational complications occur when $p $ exceeds $n$. Alternative phylogenetic comparative methods have recently been proposed to deal with the large $p $ small $n $ scenario but their use and performances are limited. Herein, we develop a penalized likelihood (PL) framework to deal with high-dimensional comparative data sets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian motion (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU), and Pagel's lambda models. We show using simulations that our PL approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when $p$ approaches $n$, and allows for their accurate estimation when $p$ equals or exceeds $n$. In addition, we show that PL models can be efficiently compared using generalized information criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic principal component analysis in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3D data set of brain shape in the New World monkeys. We find a clear support for an EB model suggesting an early diversification of brain morphology during the ecological radiation of the clade. PL offers an efficient way to deal with high-dimensional multivariate comparative data.

Inference of Adaptive Shifts for Multivariate Correlated Traits

To study the evolution of several quantitative traits, the classical phylogenetic comparative framework consists of a multivariate random process running along the branches of a phylogenetic tree. The Ornstein-Uhlenbeck (OU) process is sometimes preferred to the simple Brownian motion (BM) as it models stabilizing selection toward an optimum. The optimum for each trait is likely to be changing over the long periods of time spanned by large modern phylogenies. Our goal is to automatically detect the position of these shifts on a phylogenetic tree, while accounting for correlations between traits, which might exist because of structural or evolutionary constraints. We show that, in the presence of shifts, phylogenetic Principal Component Analysis fails to decorrelate traits efficiently, so that any method aiming at finding shifts needs to deal with correlation simultaneously. We introduce here a simplification of the full multivariate OU model, named scalar OU, which allows for noncausal correlations and is still computationally tractable. We extend the equivalence between the OU and a BM on a rescaled tree to our multivariate framework. We describe an Expectation-Maximization (EM) algorithm that allows for a maximum likelihood estimation of the shift positions, associated with a new model selection criterion, accounting for the identifiability issues for the shift localization on the tree. The method, freely available as an R-package (PhylogeneticEM) is fast, and can deal with missing values. We demonstrate its efficiency and accuracy compared to another state-of-the-art method ($\ell$1ou) on a wide range of simulated scenarios and use this new framework to reanalyze recently gathered data sets on New World Monkeys and Anolis lizards.

Multivariate Phylogenetic Comparative Methods: Evaluations, Comparisons, and Recommendations

Recent years have seen increased interest in phylogenetic comparative analyses of multivariate data sets, but to date the varied proposed approaches have not been extensively examined. Here we review the mathematical properties required of any multivariate method, and specifically evaluate existing multivariate phylogenetic comparative methods in this context. Phylogenetic comparative methods based on the full multivariate likelihood are robust to levels of covariation among trait dimensions and are insensitive to the orientation of the data set, but display increasing model misspecification as the number of trait dimensions increases. This is because the expected evolutionary covariance matrix (V) used in the likelihood calculations becomes more ill-conditioned as trait dimensionality increases, and as evolutionary models become more complex. Thus, these approaches are only appropriate for data sets with few traits and many species. Methods that summarize patterns across trait dimensions treated separately (e.g., SURFACE) incorrectly assume independence among trait dimensions, resulting in nearly a 100% model misspecification rate. Methods using pairwise composite likelihood are highly sensitive to levels of trait covariation, the orientation of the data set, and the number of trait dimensions. The consequences of these debilitating deficiencies are that a user can arrive at differing statistical conclusions, and therefore biological inferences, simply from a dataspace rotation, like principal component analysis. By contrast, algebraic generalizations of the standard phylogenetic comparative toolkit that use the trace of covariance matrices are insensitive to levels of trait covariation, the number of trait dimensions, and the orientation of the data set. Further, when appropriate permutation tests are used, these approaches display acceptable Type I error and statistical power. We conclude that methods summarizing information across trait dimensions, as well as pairwise composite likelihood methods should be avoided, whereas algebraic generalizations of the phylogenetic comparative toolkit provide a useful means of assessing macroevolutionary patterns in multivariate data. Finally, we discuss areas in which multivariate phylogenetic comparative methods are still in need of future development; namely highly multivariate Ornstein-Uhlenbeck models and approaches for multivariate evolutionary model comparisons.

Assessment of 226Ra, 238U, 232Th, 137Cs and 40K activities from the northern coastline of Oman Sea (water and sediments)

Water and sediment samples were collected from northern coast of Oman Sea covering from Goatr to Hormoz canyon seaport. Water and sediment quality assessment for naturally or anthropogenic radionuclides at Oman Sea as a main strategic golf for trade and transit, is an important issue. Correspondence analysis (CA) by R-mode analysis represents that sigma(T)-temperature-conductivity-O₂ parameters are well-correlated with ²²⁶Ra, ²³²Th and ⁴⁰K. Accordingly Q-mode analysis revealed an indicator samples of ST13W for different radionuclides, ST03W for O₂, and simultaneously ST34W-ST21W-ST08W-ST04W for sigma(T) parameters. The CA results overlapped with factor and cluster analysis results that explained 85.8% of total variance of water samples. Descriptive analysis of sediments indicates more significant variation than water samples. The ²³²Th and ²²⁶Ra generally showing that ST13D to ST25D sediments that restricted to Pi Bashk coastline are concentrated from ¹³⁷Cs and ⁴⁰K. By comparison with reference-values from Iran and other parts of the world, they are acceptable with respect to environmental and radioisotope hazards.

Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting-free algorithm

Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non-Brownian models, missing data, and within-species variation. Furthermore, even for simple univariate Brownian motion models, most phylogenetic comparative R packages compute ancestral states via inefficient tree rerooting and full tree traversals at each tree node, making ancestral state reconstruction extremely time-consuming for large phylogenies. Here, a computationally efficient method for fast maximum likelihood ancestral state reconstruction of continuous characters is described. The algorithm has linear complexity relative to the number of species and outperforms the fastest existing R implementations by several orders of magnitude. The described algorithm is capable of performing ancestral state reconstruction on a 1,000,000-species phylogeny in fewer than 2 s using a standard laptop, whereas the next fastest R implementation would take several days to complete. The method is generalizable to more complex evolutionary models, such as phylogenetic regression, within-species variation, non-Brownian evolutionary models, and multivariate trait evolution. Because this method enables fast repeated computations on phylogenies of virtually any size, implementation of the described algorithm can drastically alleviate the computational burden of many otherwise prohibitively time-consuming tasks requiring reconstruction of ancestral states, such as phylogenetic imputation of missing data, bootstrapping procedures, Expectation-Maximization algorithms, and Bayesian estimation. The described ancestral state reconstruction algorithm is implemented in the Rphylopars functions anc.recon and phylopars.

The evolution of jaw protrusion mechanics is tightly coupled to bentho-pelagic divergence in damselfishes (Pomacentridae)

Most species-rich lineages of aquatic organisms have undergone divergence between forms that feed from the substrate (benthic feeding) and forms that feed from the water column (pelagic feeding). Changes in trophic niche are frequently accompanied by changes in skull mechanics, and multiple fish lineages have evolved highly specialized biomechanical configurations that allow them to protrude their upper jaws toward the prey during feeding. Damselfishes (family Pomacentridae) are an example of a species-rich lineage with multiple trophic morphologies and feeding ecologies. We sought to determine whether bentho-pelagic divergence in the damselfishes is tightly coupled to changes in jaw protrusion ability. Using high-speed video recordings and kinematic analysis, we examined feeding performance in 10 species that include three examples of convergence on herbivory, three examples of convergence on omnivory and two examples of convergence on planktivory. We also utilized morphometrics to characterize the feeding morphology of an additional 40 species that represent all 29 damselfish genera. Comparative phylogenetic analyses were then used to examine the evolution of trophic morphology and biomechanical performance. We find that pelagic-feeding damselfishes (planktivores) are strongly differentiated from extensively benthic-feeding species (omnivores and herbivores) by their jaw protrusion ability, upper jaw morphology and the functional integration of upper jaw protrusion with lower jaw abduction. Most aspects of cranial form and function that separate these two ecological groups have evolved in correlation with each other and the evolution of the functional morphology of feeding in damselfishes has involved repeated convergence in form, function and ecology.