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The partitioning of global biodiversity into biogeographic regions is critical for understanding the impacts of global-scale ecological and evolutionary processes on species assemblages as well as prioritizing areas for conservation. However, the lack of globally comprehensive data on species distributions precludes fine-scale estimation of biogeographical regionalization for numerous taxa of ecological, economic and conservation interest. Using a recently published phylogeny and novel curated native range maps for over 10 000 species of butterflies around the world, we delineated biogeographic regions for the world’s butterflies using phylogenetic dissimilarity. We uncovered 19 distinct phylogenetically delimited regions (phyloregions) nested within 6 realms. Regional boundaries were predicted by spatial turnover in modern-day temperature and precipitation seasonality, but historical climate change also left a pronounced fingerprint on deeper- (realm-) level boundaries. We use a culturally and ecologically important group of insects to expand our understanding of how historical and contemporary factors drive the distribution of organismal lineages on the Earth. As insects and global biodiversity more generally face unprecedented challenges from anthropogenic factors, our research provides the groundwork for prioritizing regions and taxa for conservation, especially with the goal of preserving the legacies of our biosphere’s evolutionary history. This article is part of the discussion meeting issue ‘Bending the curve towards nature recovery: building on Georgina Mace's legacy for a biodiverse future’. 

Abstract Reconstructing the evolutionary history of different groups of organisms provides insight into how life originated and diversified on Earth. Phylogenetic trees are commonly used to estimate this evolutionary history. Within Bayesian phylogenetics a major step in estimating a tree is in choosing an appropriate model of character evolution. While the most common character data used is molecular sequence data, morphological data remains a vital source of information. The use of morphological characters allows for the incorporation fossil taxa, and despite advances in molecular sequencing, continues to play a significant role in neontology. Moreover, it is the main data source that allows us to unite extinct and extant taxa directly under the same generating process. We therefore require suitable models of morphological character evolution, the most common being the Mk Lewis model. While it is frequently used in both palaeobiology and neontology, it is not known whether the simple Mk substitution model, or any extensions to it, provide a sufficiently good description of the process of morphological evolution. In this study we investigate the impact of different morphological models on empirical tetrapod datasets. Specifically, we compare unpartitioned Mk models with those where characters are partitioned by the number of observed states, both with and without allowing for rate variation across sites and accounting for ascertainment bias. We show that the choice of substitution model has an impact on both topology and branch lengths, highlighting the importance of model choice. Through simulations, we validate the use of the model adequacy approach, posterior predictive simulations, for choosing an appropriate model. Additionally, we compare the performance of model adequacy with Bayesian model selection. We demonstrate how model selection approaches based on marginal likelihoods are not appropriate for choosing between models with partition schemes that vary in character state space (i.e., that vary in Q-matrix state size). Using posterior predictive simulations, we found that current variations of the Mk model are often performing adequately in capturing the evolutionary dynamics that generated our data. We do not find any preference for a particular model extension across multiple datasets, indicating that there is no “one size fits all” when it comes to morphological data and that careful consideration should be given to choosing models of discrete character evolution. By using suitable models of character evolution, we can increase our confidence in our phylogenetic estimates, which should in turn allow us to gain more accurate insights into the evolutionary history of both extinct and extant taxa. 

Abstract Phylogenetic trees establish a historical context for the study of organismal form and function. Most phylogenetic trees are estimated using a model of evolution. For molecular data, modeling evolution is often based on biochemical observations about changes between character states. For example, there are four nucleotides, and we can make assumptions about the probability of transitions between them. By contrast, for morphological characters, we may not know a priori how many characters states there are per character, as both extant sampling and the fossil record may be highly incomplete, which leads to an observer bias. For a given character, the state space may be larger than what has been observed in the sample of taxa collected by the researcher. In this case, how many evolutionary rates are needed to even describe transitions between morphological character states may not be clear, potentially leading to model misspecification. To explore the impact of this model misspecification, we simulated character data with varying numbers of character states per character. We then used the data to estimate phylogenetic trees using models of evolution with the correct number of character states and an incorrect number of character states. The results of this study indicate that this observer bias may lead to phylogenetic error, particularly in the branch lengths of trees. If the state space is wrongly assumed to be too large, then we underestimate the branch lengths, and the opposite occurs when the state space is wrongly assumed to be too small. 

Over the past decade, a new set of methods for estimating dated trees has emerged. Originally referred to as the fossilized birth–death (FBD) process, this single model has expanded to a family of models that allows researchers to coestimate evolutionary parameters (e.g., diversification, sampling) and patterns alongside divergence times for a variety of applications from paleobiology to real-time epidemiology. We provide an overview of this family of models. We explore the ways in which these models correspond to methods in quantitative paleobiology, as the FBD process provides a framework through which neontological and paleontological approaches to phylogenetics and macroevolution can be unified. We also provide an overview of challenges associated with applying FBD models, particularly with an eye toward the fossil record. We conclude this review by discussing several exciting avenues for the inclusion of fossil data in phylogenetic analyses. 

Poeciliopsis (Cyprinodontiformes: Poeciliidae) is a genus comprised of 25 species of freshwater fishes. Several well-known taxonomic uncertainties exist within the genus, especially in relation to the taxonomic status of Poeciliopsis pleurospilus and P . gracilis . However, to date, no studies have been conducted to specifically address the taxonomic status of these two species. The goal of this study was to examine the taxonomic validity of P . pleurospilus and P . gracilis using genomic data (ddRADseq) in phylogenetic, population genetic, and species delimitation frameworks. Multiple analyses support the recognition of both taxa as distinct species and also permits us to revise their respective distributions. A species delimitation analysis indicates that P . pleurospilus and P . gracilis are distinct species, each of which consists of two distinct lineages that are geographically structured. Phylogenetic and population genetic analyses provide clear evidence that individuals of P . gracilis are distributed north and west of the Isthmus of Tehuantepec in both Pacific and Atlantic river systems in Mexico, whereas individuals of P . pleurospilus are distributed in both Atlantic and Pacific river systems south and east of the Isthmus of Tehuantepec, from southern Mexico to Honduras. 

Abstract Simulations are playing an increasingly important role in paleobiology. When designing a simulation study, many decisions have to be made and common challenges will be encountered along the way. Here, we outline seven rules for executing a good simulation study. We cover topics including the choice of study question, the empirical data used as a basis for the study, statistical and methodological concerns, how to validate the study, and how to ensure it can be reproduced and extended by others. We hope that these rules and the accompanying examples will guide paleobiologists when using simulation tools to address fundamental questions about the evolution of life. 

No abstract available. 

Many biologists are interested in teaching computing skills or using computing in the classroom, despite not being formally trained in these skills themselves. Thus biologists may find themselves researching how to teach these skills, and therefore many individuals are individually attempting to discover resources and methods to do so. Recent years have seen an expansion of new technologies to assist in delivering course content interactively. Educational research provides insights into how learners absorb and process information during interactive learning. In this review, we discuss the value of teaching foundational computing skills to biologists, and strategies and tools to do so. Additionally, we review the literature on teaching practices to support the development of these skills. We pay special attention to meeting the needs of diverse learners, and consider how different ways of delivering course content can be leveraged to provide a more inclusive classroom experience. Our goal is to enable biologists to teach computational skills and use computing in the classroom successfully.