How many species are there on Earth and to what groups do these species belong? These fundamental questions span systematics, ecology, and evolutionary biology. Yet, recent estimates of overall global biodiversity have ranged wildly, from the low millions to the trillions. Insects are a pivotal group for these estimates. Insects make up roughly half of currently described extant species (across all groups), with ~1 million described species. Insect diversity is also crucial because many other taxa have species that may be unique to each insect host species, including bacteria, apicomplexan protists, microsporidian fungi, nematodes, and mites. Several projections of total insect diversity (described and undescribed) have converged on ~6 million species. However, these projections have not incorporated the morphologically cryptic species revealed by molecular data. Here, we estimate the extent of cryptic insect diversity. We perform a systematic review of studies that used explicit species-delimitation methods with multi-locus data. We estimate that each morphology-based insect species contains (on average) 3.1 cryptic species. We then use these estimates to project the overall number of species on Earth and their distribution among major groups. Our estimates suggest that overall global biodiversity may range from 563 million to 2.2 billion species. [Biodiversity; cryptic species; insects; species delimitation; species richness].

Gastropods have survived several mass extinctions during their evolutionary history resulting in extraordinary diversity in morphology, ecology, and developmental modes, which complicate the reconstruction of a robust phylogeny. Currently, gastropods are divided into six subclasses: Caenogastropoda, Heterobranchia, Neomphaliones, Neritimorpha, Patellogastropoda, and Vetigastropoda. Phylogenetic relationships among these taxa historically lack consensus, despite numerous efforts using morphological and molecular information. We generated sequence data for transcriptomes derived from 12 taxa belonging to clades with little or no prior representation in previous studies in order to infer the deeper cladogenetic events within Gastropoda and, for the first time, infer the position of the deep-sea Neomphaliones using a phylogenomic approach. We explored the impact of missing data, homoplasy, and compositional heterogeneity on the inferred phylogenetic hypotheses. We recovered a highly supported backbone for gastropod relationships that is congruent with morphological and mitogenomic evidence, in which Patellogastropoda, true limpets, are the sister lineage to all other gastropods (Orthogastropoda) which are divided into two main clades 1) Vetigastropoda $s.l.$ (including Pleurotomariida $+$ Neomphaliones) and 2) Neritimorpha $+$ (Caenogastropoda $+$ Heterobranchia). As such, our results support the recognition of five subclasses (or infraclasses) in Gastropoda: Patellogastropoda, Vetigastropoda, Neritimorpha, Caenogastropoda, and Heterobranchia. [Compositional heterogeneity; fast-evolving; long-branch attraction; missing data; Mollusca; phylogenetics; systematic error.].

To examine phylogenetic heterogeneity in turtle evolution, we collected thousands of high-confidence single-copy orthologs from 19 genome assemblies representative of extant turtle diversity and estimated a phylogeny with multispecies coalescent and concatenated partitioned methods. We also collected next-generation sequences from 26 turtle species and assembled millions of biallelic markers to reconstruct phylogenies based on annotated regions from the western painted turtle (Chrysemys picta bellii) genome (coding regions, introns, untranslated regions, intergenic, and others). We then measured gene tree-species tree discordance, as well as gene and site heterogeneity at each node in the inferred trees, and tested for temporal patterns in phylogenomic conflict across turtle evolution. We found strong and consistent support for all bifurcations in the inferred turtle species phylogenies. However, a number of genes, sites, and genomic features supported alternate relationships between turtle taxa. Our results suggest that gene tree-species tree discordance in these data sets is likely driven by population-level processes such as incomplete lineage sorting. We found very little effect of substitutional saturation on species tree topologies, and no clear phylogenetic patterns in codon usage bias and compositional heterogeneity. There was no correlation between gene and site concordance, node age, and DNA substitution rate across most annotated genomic regions. Our study demonstrates that heterogeneity is to be expected even in well-resolved clades such as turtles, and that future phylogenomic studies should aim to sample as much of the genome as possible in order to obtain accurate phylogenies for assessing conservation priorities in turtles. [Discordance; genomes; phylogeny; turtles.].

We present a two-headed approach called Bayesian Integrated Coalescent Epoch PlotS (BICEPS) for efficient inference of coalescent epoch models. Firstly, we integrate out population size parameters, and secondly, we introduce a set of more powerful Markov chain Monte Carlo (MCMC) proposals for flexing and stretching trees. Even though population sizes are integrated out and not explicitly sampled through MCMC, we are still able to generate samples from the population size posteriors. This allows demographic reconstruction through time and estimating the timing and magnitude of population bottlenecks and full population histories. Altogether, BICEPS can be considered a more muscular version of the popular Bayesian skyline model. We demonstrate its power and correctness by a well-calibrated simulation study. Furthermore, we demonstrate with an application to SARS-CoV-2 genomic data that some analyses that have trouble converging with the traditional Bayesian skyline prior and standard MCMC proposals can do well with the BICEPS approach. BICEPS is available as open-source package for BEAST 2 under GPL license and has a user-friendly graphical user interface.[Bayesian phylogenetics; BEAST 2; BICEPS; coalescent model.].

The use of information criteria to distinguish between phylogenetic models has become ubiquitous within the field. However, the variety and complexity of available models are much greater now than when these practices were established. The literature shows an increasing trajectory of healthy skepticism with regard to the use of information theory-based model selection within phylogenetics. We add to this by analyzing the specific case of comparison between partition and mixture models. We argue from a theoretical basis that information criteria are inherently more likely to favor partition models over mixture models, and we then demonstrate this through simulation. Based on our findings, we suggest that partition and mixture models are not suitable for information-theory based model comparison. [AIC, BIC; information criteria; maximum likelihood; mixture models; partitioned model; phylogenetics.].

How long does speciation take? The answer to this important question in evolutionary biology lies in the genetic difference not only among species, but also among lineages within each species. With the advance of genome sequencing in non-model organisms and the statistical tools to improve accuracy in inferring evolutionary histories among recently diverged lineages, we now have the lineage-level trees to answer these questions. However, we do not yet have an analytical tool for inferring speciation processes from these trees. What is needed is a model of speciation processes that generates both the trees and species identities of extant lineages. The model should allow calculation of the probability that certain lineages belong to certain species and have an evolutionary history consistent with the tree. Here, we propose such a model and test the model performance on both simulated data and real data. We show that maximum-likelihood estimates of the model are highly accurate and give estimates from real data that generate patterns consistent with observations. We discuss how to extend the model to account for different rates and types of speciation processes across lineages in a species group. By linking evolutionary processes on lineage level to species level, the model provides a new phylogenetic approach to study not just when speciation happened, but how speciation happened. [Micro-macro evolution; Protracted birth-death process; speciation completion rate; SSE approach.].

Evolutionary comparisons between major environmental divides, such as between marine and freshwater systems, can reveal the fundamental processes governing diversification dynamics. Although processes may differ due to the different scales of their biogeographic barriers, freshwater and marine environments nevertheless offer similar opportunities for diversification in benthic, demersal, and pelagic habitats. Here, we compare the evolutionary patterns and processes shaping teleost diversity in each of these three habitats and between marine and freshwater systems. Using specimens from the National Museum of Natural History, we developed a data set of linear measurements capturing body shape in 2266 freshwater and 3344 marine teleost species. With a novel comparative approach, we contrast the primary axis of morphological diversification in each habitat with the major axis defined by phylogenetic signal. By comparing angles between these axes, we find that fish in corresponding habitats have more similar primary axes of morphological diversity than would be expected by chance, but that different historical processes underlie these parallel patterns in freshwater and marine environments. Marine diversification is more strongly aligned with phylogenetic signal and shows a trend toward lineages occupying separate regions of morphospace. In contrast, ecological signal appears to be a strong driver of diversification in freshwater lineages through repeated morphological evolution in densely packed regions of morphospace. In spite of these divergent histories, our findings reveal that habitat has driven convergent patterns of evolutionary diversification on a global scale. [Benthic-pelagic axis; body shape; convergent evolution; morphological diversification; phylogenetic signal.].

A large variety of pairwise measures of similarity or dissimilarity have been developed for comparing phylogenetic trees, for example, species trees or gene trees. Due to its intuitive definition in terms of tree clades and bipartitions and its computational efficiency, the Robinson-Foulds (RF) distance is the most widely used for trees with unweighted edges and labels restricted to leaves (representing the genetic elements being compared). However, in the case of gene trees, an important information revealing the nature of the homologous relation between gene pairs (orthologs, paralogs, and xenologs) is the type of event associated to each internal node of the tree, typically speciations or duplications, but other types of events may also be considered, such as horizontal gene transfers. This labeling of internal nodes is usually inferred from a gene tree/species tree reconciliation method. Here, we address the problem of comparing such event-labeled trees. The problem differs from the classical problem of comparing uniformly labeled trees (all labels belonging to the same alphabet) that may be done using the Tree Edit Distance (TED) mainly due to the fact that, in our case, two different alphabets are considered for the leaves and internal nodes of the tree, and leaves are not affected by edit operations. We propose an extension of the RF distance to event-labeled trees, based on edit operations comparable to those considered for TED: node insertion, node deletion, and label substitution. We show that this new Labeled Robinson-Foulds (LRF) distance can be computed in linear time, in addition of maintaining other desirable properties: being a metric, reducing to RF for trees with no labels on internal nodes and maintaining an intuitive interpretation. The algorithm for computing the LRF distance enables novel analyses on event-label trees such as reconciled gene trees. Here, we use it to study the impact of taxon sampling on labeled gene tree inference and conclude that denser taxon sampling yields trees with better topology but worse labeling. [Algorithms; combinatorics; gene trees; phylogenetics; Robinson-Foulds; tree distance.].

Phylogenetic trees are a central tool in many areas of life science and medicine. They demonstrate evolutionary patterns among species, genes, and patterns of ancestry among sets of individuals. The tree shapes and branch lengths of phylogenetic trees encode evolutionary and epidemiological information. To extract information from tree shapes and branch lengths, representation and comparison methods for phylogenetic trees are needed. Representing and comparing tree shapes and branch lengths of phylogenetic trees are challenging, for a tree shape is unlabeled and can be displayed in numerous different forms, and branch lengths of a tree shape are specific to edges whose positions vary with respect to the displayed forms of the tree shape. In this article, we introduce representation and comparison methods for rooted unlabeled phylogenetic trees based on a tree lattice that serves as a coordinate system for rooted binary trees with branch lengths and a graph polynomial that fully characterizes tree shapes. We show that the introduced tree representations and metrics provide distance-based likelihood-free methods for tree clustering, parameter estimation, and model selection and apply the methods to analyze phylogenies reconstructed from virus sequences. [Graph polynomial; likelihood-free inference; phylogenetics; tree lattice; tree metrics.].

The Ornstein-Uhlenbeck (OU) model is widely used in comparative phylogenetic analyses to study the evolution of quantitative traits. It has been applied to various purposes, including the estimation of the strength of selection or ancestral traits, inferring the existence of several selective regimes, or accounting for phylogenetic correlation in regression analyses. Most programs implementing statistical inference under the OU model have resorted to maximum-likelihood (ML) inference until the recent advent of Bayesian methods. A series of issues have been noted for ML inference using the OU model, including parameter nonidentifiability. How these problems translate to a Bayesian framework has not been studied much to date and is the focus of the present article. In particular, I aim to assess the impact of the choice of priors on parameter estimates. I show that complex interactions between parameters may cause the priors for virtually all parameters to impact inference in sometimes unexpected ways, whatever the purpose of inference. I specifically draw attention to the difficulty of setting the prior for the selection strength parameter, a task to be undertaken with much caution. I particularly address investigators who do not have precise prior information, by highlighting the fact that the effect of the prior for one parameter is often only visible through its impact on the estimate of another parameter. Finally, I propose a new parameterization of the OU model that can be helpful when prior information about the parameters is not available. [Bayesian inference; Brownian motion; Ornstein-Uhlenbeck model; phenotypic evolution; phylogenetic comparative methods; prior distribution; quantitative trait evolution.].

Phylodynamic models generally aim at jointly inferring phylogenetic relationships, model parameters, and more recently, the number of lineages through time, based on molecular sequence data. In the fields of epidemiology and macroevolution, these models can be used to estimate, respectively, the past number of infected individuals (prevalence) or the past number of species (paleodiversity) through time. Recent years have seen the development of "total-evidence" analyses, which combine molecular and morphological data from extant and past sampled individuals in a unified Bayesian inference framework. Even sampled individuals characterized only by their sampling time, that is, lacking morphological and molecular data, which we call occurrences, provide invaluable information to estimate the past number of lineages. Here, we present new methodological developments around the fossilized birth-death process enabling us to (i) incorporate occurrence data in the likelihood function; (ii) consider piecewise-constant birth, death, and sampling rates; and (iii) estimate the past number of lineages, with or without knowledge of the underlying tree. We implement our method in the RevBayes software environment, enabling its use along with a large set of models of molecular and morphological evolution, and validate the inference workflow using simulations under a wide range of conditions. We finally illustrate our new implementation using two empirical data sets stemming from the fields of epidemiology and macroevolution. In epidemiology, we infer the prevalence of the coronavirus disease 2019 outbreak on the Diamond Princess ship, by taking into account jointly the case count record (occurrences) along with viral sequences for a fraction of infected individuals. In macroevolution, we infer the diversity trajectory of cetaceans using molecular and morphological data from extant taxa, morphological data from fossils, as well as numerous fossil occurrences. The joint modeling of occurrences and trees holds the promise to further bridge the gap between traditional epidemiology and pathogen genomics, as well as paleontology and molecular phylogenetics. [Birth-death model; epidemiology; fossils; macroevolution; occurrences; phylogenetics; skyline.].

A prominent question in animal research is how the evolution of morphology and ecology interacts in the generation of phenotypic diversity. Spiders are some of the most abundant arthropod predators in terrestrial ecosystems and exhibit a diversity of foraging styles. It remains unclear how spider body size and proportions relate to foraging style, and if the use of webs as prey capture devices correlates with changes in body characteristics. Here, we present the most extensive data set to date of morphometric and ecological traits in spiders. We used this data set to estimate the change in spider body sizes and shapes over deep time and to test if and how spider phenotypes are correlated with their behavioral ecology. We found that phylogenetic variation of most traits best fitted an Ornstein-Uhlenbeck model, which is a model of stabilizing selection. A prominent exception was body length, whose evolutionary dynamics were best explained with a Brownian Motion (free trait diffusion) model. This was most expressed in the araneoid clade (ecribellate orb-weaving spiders and allies) that showed bimodal trends toward either miniaturization or gigantism. Only few traits differed significantly between ecological guilds, most prominently leg length and thickness, and although a multivariate framework found general differences in traits among ecological guilds, it was not possible to unequivocally associate a set of morphometric traits with the relative ecological mode. Long, thin legs have often evolved with aerial webs and a hanging (suspended) locomotion style, but this trend is not general. Eye size and fang length did not differ between ecological guilds, rejecting the hypothesis that webs reduce the need for visual cue recognition and prey immobilization. For the inference of the ecology of species with unknown behaviors, we propose not to use morphometric traits, but rather consult (micro-)morphological characters, such as the presence of certain podal structures. These results suggest that, in contrast to insects, the evolution of body proportions in spiders is unusually stabilized and ecological adaptations are dominantly realized by behavioral traits and extended phenotypes in this group of predators. This work demonstrates the power of combining recent advances in phylogenomics with trait-based approaches to better understand global functional diversity patterns through space and time. [Animal architecture; Arachnida; Araneae; extended phenotype; functional traits; macroevolution; stabilizing selection.].

Whole-genome duplication (WGD) occurs broadly and repeatedly across the history of eukaryotes and is recognized as a prominent evolutionary force, especially in plants. Immediately following WGD, most genes are present in two copies as paralogs. Due to this redundancy, one copy of a paralog pair commonly undergoes pseudogenization and is eventually lost. When speciation occurs shortly after WGD; however, differential loss of paralogs may lead to spurious phylogenetic inference resulting from the inclusion of pseudoorthologs-paralogous genes mistakenly identified as orthologs because they are present in single copies within each sampled species. The influence and impact of including pseudoorthologs versus true orthologs as a result of gene extinction (or incomplete laboratory sampling) are only recently gaining empirical attention in the phylogenomics community. Moreover, few studies have yet to investigate this phenomenon in an explicit coalescent framework. Here, using mathematical models, numerous simulated data sets, and two newly assembled empirical data sets, we assess the effect of pseudoorthologs on species tree estimation under varying degrees of incomplete lineage sorting (ILS) and differential gene loss scenarios following WGD. When gene loss occurs along the terminal branches of the species tree, alignment-based (BPP) and gene-tree-based (ASTRAL, MP-EST, and STAR) coalescent methods are adversely affected as the degree of ILS increases. This can be greatly improved by sampling a sufficiently large number of genes. Under the same circumstances, however, concatenation methods consistently estimate incorrect species trees as the number of genes increases. Additionally, pseudoorthologs can greatly mislead species tree inference when gene loss occurs along the internal branches of the species tree. Here, both coalescent and concatenation methods yield inconsistent results. These results underscore the importance of understanding the influence of pseudoorthologs in the phylogenomics era. [Coalescent method; concatenation method; incomplete lineage sorting; pseudoorthologs; single-copy gene; whole-genome duplication.].

The concept that complex ancestral traits can never be recovered after their loss is still widely accepted, despite phylogenetic and molecular approaches suggest instances where phenotypes may have been lost throughout the evolutionary history of a clade and subsequently reverted back in derived lineages. One of the first and most notable examples of such a process is wing evolution in phasmids; this polyneopteran order of insects, which comprises stick and leaf insects, has played a central role in initiating a long-standing debate on the topic. In this study, a novel and comprehensive time tree including over 300 Phasmatodea species is used as a framework for investigating wing evolutionary patterns in the clade. Despite accounting for several possible biases and sources of uncertainty, macroevolutionary analyses consistently revealed multiple reversals to winged states taking place after their loss, and reversibility is coupled with higher species diversification rates. Our findings support a loss of or reduction in wings that occurred in the lineage leading to the extant phasmid most recent common ancestor, and brachyptery is inferred to be an unstable state unless co-opted for nonaerodynamic adaptations. We also explored how different assumptions of wing reversals probability could impact their inference: we found that until reversals are assumed to be over 30 times more unlikely than losses, they are consistently inferred despite uncertainty in tree and model parameters. Our findings demonstrate that wing evolution is a reversible and dynamic process in phasmids and contribute to our understanding of complex trait evolution. [Dollo's law; Phasmatodea; phylogenetic comparative methods; polyneoptera; reversals; wing.].

Morphology remains a primary source of phylogenetic information for many groups of organisms, and the only one for most fossil taxa. Organismal anatomy is not a collection of randomly assembled and independent "parts", but instead a set of dependent and hierarchically nested entities resulting from ontogeny and phylogeny. How do we make sense of these dependent and at times redundant characters? One promising approach is using ontologies-structured controlled vocabularies that summarize knowledge about different properties of anatomical entities, including developmental and structural dependencies. Here, we assess whether evolutionary patterns can explain the proximity of ontology-annotated characters within an ontology. To do so, we measure phylogenetic information across characters and evaluate if it matches the hierarchical structure given by ontological knowledge-in much the same way as across-species diversity structure is given by phylogeny. We implement an approach to evaluate the Bayesian phylogenetic information (BPI) content and phylogenetic dissonance among ontology-annotated anatomical data subsets. We applied this to data sets representing two disparate animal groups: bees (Hexapoda: Hymenoptera: Apoidea, 209 chars) and characiform fishes (Actinopterygii: Ostariophysi: Characiformes, 463 chars). For bees, we find that BPI is not substantially explained by anatomy since dissonance is often high among morphologically related anatomical entities. For fishes, we find substantial information for two clusters of anatomical entities instantiating concepts from the jaws and branchial arch bones, but among-subset information decreases and dissonance increases substantially moving to higher-level subsets in the ontology. We further applied our approach to address particular evolutionary hypotheses with an example of morphological evolution in miniature fishes. While we show that phylogenetic information does match ontology structure for some anatomical entities, additional relationships and processes, such as convergence, likely play a substantial role in explaining BPI and dissonance, and merit future investigation. Our work demonstrates how complex morphological data sets can be interrogated with ontologies by allowing one to access how information is spread hierarchically across anatomical concepts, how congruent this information is, and what sorts of processes may play a role in explaining it: phylogeny, development, or convergence. [Apidae; Bayesian phylogenetic information; Ostariophysi; Phenoscape; phylogenetic dissonance; semantic similarity.].

New, rapid, accurate, scalable, and cost-effective species discovery and delimitation methods are needed for tackling "dark taxa," here defined as groups for which $<$10$\%$ of all species are described and the estimated diversity exceeds 1,000 species. Species delimitation for these taxa should be based on multiple data sources ("integrative taxonomy") but collecting multiple types of data risks impeding a discovery process that is already too slow. We here develop large-scale integrative taxonomy (LIT), an explicit method where preliminary species hypotheses are generated based on inexpensive data that can be obtained quickly and cost-effectively. These hypotheses are then evaluated based on a more expensive type of "validation data" that is only obtained for specimens selected based on objective criteria applied to the preliminary species hypotheses. We here use this approach to sort 18,000 scuttle flies (Diptera: Phoridae) into 315 preliminary species hypotheses based on next-generation sequencing barcode (313 bp) clusters (using objective clustering [OC] with a 3$\%$ threshold). These clusters are then evaluated with morphology as the validation data. We develop quantitative indicators for predicting which barcode clusters are likely to be incongruent with morphospecies by randomly selecting 100 clusters for in-depth validation with morphology. A linear model demonstrates that the best predictors for incongruence between barcode clusters and morphology are maximum p-distance within the cluster and a newly proposed index that measures cluster stability across different clustering thresholds. A test of these indicators using the 215 remaining clusters reveals that these predictors correctly identify all clusters that are incongruent with morphology. In our study, all morphospecies are true or disjoint subsets of the initial barcode clusters so that all incongruence can be eliminated by varying clustering thresholds. This leads to a discussion of when a third data source is needed to resolve incongruent grouping statements. The morphological validation step in our study involved 1,039 specimens (5.8$\%$ of the total). The formal LIT protocol we propose would only have required the study of 915 (5.1$\%$: 2.5 specimens per species), as we show that clusters without signatures of incongruence can be validated by only studying two specimens representing the most divergent haplotypes. To test the generality of our results across different barcode clustering techniques, we establish that the levels of incongruence are similar across OC, Automatic Barcode Gap Discovery (ABGD), Poisson Tree Processes (PTP), and Refined Single Linkage (RESL) (used by Barcode of Life Data System to assign Barcode Index Numbers [BINs]). OC and ABGD achieved a maximum congruence score with the morphology of 89$\%$ while PTP was slightly less effective (84$\%$). RESL could only be tested for a subset of the specimens because the algorithm is not public. BINs based on 277 of the original 1,714 haplotypes were 86$\%$ congruent with morphology while the values were 89$\%$ for OC, 74$\%$ for PTP, and 72$\%$ for ABGD. [Biodiversity discovery; dark taxa; DNA barcodes; integrative taxonomy.].

Understanding phenotypic disparity across the tree of life requires identifying where and when evolutionary rates change on phylogeny. A primary methodological challenge in macroevolution is therefore to develop methods for accurate inference of among-lineage variation in rates of phenotypic evolution. Here, we describe a method for inferring among-lineage evolutionary rate heterogeneity in both continuous and discrete traits. The method assumes that the present-day distribution of a trait is shaped by a variable-rate process arising from a mixture of constant-rate processes and uses a single-pass tree traversal algorithm to estimate branch-specific evolutionary rates. By employing dynamic programming optimization techniques and approximate maximum likelihood estimators where appropriate, our method permits rapid exploration of the tempo and mode of phenotypic evolution. Simulations indicate that the method reconstructs rates of trait evolution with high accuracy. Application of the method to data sets on squamate reptile reproduction and turtle body size recovers patterns of rate heterogeneity identified by previous studies but with computational costs reduced by many orders of magnitude. Our results expand the set of tools available for detecting macroevolutionary rate heterogeneity and point to the utility of fast, approximate methods for studying large-scale biodiversity dynamics. [Brownian motion; continuous characters; discrete characters; macroevolution; Markov process; rate heterogeneity.].

Scorpions constitute a charismatic lineage of arthropods and comprise more than 2500 described species. Found throughout various tropical and temperate habitats, these predatory arachnids have a long evolutionary history, with a fossil record that began in the Silurian. While all scorpions are venomous, the asymmetrically diverse family Buthidae harbors nearly half the diversity of extant scorpions, and all but one of the 58 species that are medically significant to humans. However, the lack of a densely sampled scorpion phylogeny has hindered broader inferences of the diversification dynamics of scorpion toxins. To redress this gap, we assembled a phylogenomic data set of 100 scorpion venom gland transcriptomes and genomes, emphasizing the sampling of highly toxic buthid genera. To infer divergence times of venom gene families, we applied a phylogenomic node dating approach for the species tree in tandem with phylostratigraphic bracketing to estimate the minimum ages of mammal-specific toxins. Our analyses establish a robustly supported phylogeny of scorpions, particularly with regard to relationships between medically significant taxa. Analysis of venom gene families shows that mammal-active sodium channel toxins (NaTx) have independently evolved in five lineages within Buthidae. Temporal windows of mammal-targeting toxin origins are correlated with the basal diversification of major scorpion mammal predators such as shrews, bats, and rodents. These results suggest an evolutionary model of relatively recent diversification of buthid NaTx homologs in response to the diversification of scorpion predators. [Adaptation; arachnids; phylogenomic dating; phylostratigraphy; venom.].

The complex island archipelagoes of Wallacea and Melanesia have provided empirical data behind integral theories in evolutionary biology, including allopatric speciation and island biogeography. Yet, questions regarding the relative impact of the layered biogeographic barriers, such as deep-water trenches and isolated island systems, on faunal diversification remain underexplored. One such barrier is Wallace's Line, a significant biogeographic boundary that largely separates Australian and Asian biodiversity. To assess the relative roles of biogeographic barriers-specifically isolated island systems and Wallace's Line-we investigated the tempo and mode of diversification in a diverse avian radiation, Corvides (Crows and Jays, Birds-of-paradise, Vangas, and allies). We combined a genus-level data set of thousands of ultraconserved elements (UCEs) and a species-level, 12-gene Sanger sequence matrix to produce a well-resolved supermatrix tree that we leveraged to explore the group's historical biogeography and the effects of the biogeographic barriers on their macroevolutionary dynamics. The tree is well resolved and differs substantially from what has been used extensively for past comparative analyses within this group. We confirmed that Corvides, and its major constituent clades, arose in Australia and that a burst of dispersals west across Wallace's Line occurred after the uplift of Wallacea during the mid-Miocene. We found that dispersal across this biogeographic barrier was generally rare, though westward dispersals were two times more frequent than eastward dispersals. Wallacea's central position between Sundaland and Sahul no doubt acted as a bridge for island-hopping dispersal out of Australia, across Wallace's Line, to colonize the rest of Earth. In addition, we found that the complex island archipelagoes east of Wallace's Line harbor the highest rates of net diversification and are a substantial source of colonists to continental systems on both sides of this biogeographic barrier. Our results support emerging evidence that island systems, particularly the geologically complex archipelagoes of the Indo-pacific, are drivers of species diversification. [Historical biogeography; island biogeography; Melanesia; molecular phylogenetics; state-dependent diversification and extinction.].

Complex speciation, involving rapid divergence and multiple bouts of post-divergence gene flow, can obfuscate phylogenetic relationships and species limits. In North America, cases of complex speciation are common, due at least in part to the cyclical Pleistocene glacial history of the continent. Scrub-Jays in the genus Aphelocoma provide a useful case study in complex speciation because their range throughout North America is structured by phylogeographic barriers with multiple cases of secondary contact between divergent lineages. Here, we show that a comprehensive approach to genomic reconstruction of evolutionary history, i.e., synthesizing results from species delimitation, species tree reconstruction, demographic model testing, and tests for gene flow, is capable of clarifying evolutionary history despite complex speciation. We find concordant evidence across all statistical approaches for the distinctiveness of an endemic southern Mexico lineage (A. w. sumichrasti), culminating in support for the species status of this lineage under any commonly applied species concept. We also find novel genomic evidence for the species status of a Texas endemic lineage A. w. texana, for which equivocal species delimitation results were clarified by demographic modeling and spatially explicit models of gene flow. Finally, we find that complex signatures of both ancient and modern gene flow between the non-sister California Scrub-Jay (Aphelocoma californica) and Woodhouse's Scrub-Jay (Aphelocoma woodhouseii) result in discordant gene trees throughout the species' genomes despite clear support for their overall isolation and species status. In sum, we find that a multi-faceted approach to genomic analysis can increase our understanding of complex speciation histories, even in well-studied groups. Given the emerging recognition that complex speciation is relatively commonplace, the comprehensive framework that we demonstrate for interrogation of species limits and evolutionary history using genomic data can provide a necessary roadmap for disentangling the impacts of gene flow and incomplete lineage sorting (ILS) to better understand the systematics of other groups with similarly complex evolutionary histories. [Gene flow; genomics; introgression; phylogenomics; population genetics; species delimitation; species trees; systematics.].

Contamination of a genetic sample with DNA from one or more nontarget species is a continuing concern of molecular phylogenetic studies, both Sanger sequencing studies and next-generation sequencing studies. We developed an automated pipeline for identifying and excluding likely cross-contaminated loci based on the detection of bimodal distributions of patristic distances across gene trees. When contamination occurs between samples within a data set, a comparison between a contaminated sample and its contaminant taxon will yield bimodal distributions with one peak close to zero patristic distance. This new method does not rely on a priori knowledge of taxon relatedness nor does it determine the causes(s) of the contamination. Exclusion of putatively contaminated loci from a data set generated for the insect family Cicadidae showed that these sequences were affecting some topological patterns and branch supports, although the effects were sometimes subtle, with some contamination-influenced relationships exhibiting strong bootstrap support. Long tip branches and outlier values for one anchored phylogenomic pipeline statistic (AvgNHomologs) were correlated with the presence of contamination. While the anchored hybrid enrichment markers used here, which target hemipteroid taxa, proved effective in resolving deep and shallow level Cicadidae relationships in aggregate, individual markers contained inadequate phylogenetic signal, in part probably due to short length. The cleaned data set, consisting of 429 loci, from 90 genera representing 44 of 56 current Cicadidae tribes, supported three of the four sampled Cicadidae subfamilies in concatenated-matrix maximum likelihood (ML) and multispecies coalescent-based species tree analyses, with the fourth subfamily weakly supported in the ML trees. No well-supported patterns from previous family-level Sanger sequencing studies of Cicadidae phylogeny were contradicted. One taxon (Aragualna plenalinea) did not fall with its current subfamily in the genetic tree, and this genus and its tribe Aragualnini is reclassified to Tibicininae following morphological re-examination. Only subtle differences were observed in trees after the removal of loci for which divergent base frequencies were detected. Greater success may be achieved by increased taxon sampling and developing a probe set targeting a more recent common ancestor and longer loci. Searches for contamination are an essential step in phylogenomic analyses of all kinds and our pipeline is an effective solution. [Auchenorrhyncha; base-composition bias; Cicadidae; Cicadoidea; Hemiptera; phylogenetic conflict.].