Gene flow among populations or species and incomplete lineage sorting (ILS) are two evolutionary processes responsible for generating gene tree discordance and therefore hindering species tree estimation. Numerous studies have evaluated the impacts of ILS on species tree inference, yet the ramifications of gene flow on species trees remain less studied. Here, we simulate and analyse multilocus sequence data generated with ILS and gene flow to quantify their impacts on species tree inference. We characterize species tree estimation errors under various models of gene flow, such as the isolation-migration model, the n-island model, and gene flow between non-sister species or involving ancestral species, and species boundaries crossed by a single gene copy (allelic introgression) or by a single migrant individual. These patterns of gene flow are explored on species trees of different sizes (4 vs. 10 species), at different time scales (shallow vs. deep), and with different migration rates. Species trees are estimated with the multispecies coalescent model using Bayesian methods (BEST and *BEAST) and with a summary statistic approach (MPEST) that facilitates phylogenomic-scale analysis. Even in cases where the topology of the species tree is estimated with high accuracy, we find that gene flow can result in overestimates of population sizes (species tree dilation) and underestimates of species divergence times (species tree compression). Signatures of migration events remain present in the distribution of coalescent times for gene trees, and with sufficient data it is possible to identify those loci that have crossed species boundaries. These results highlight the need for careful sampling design in phylogeographic and species delimitation studies as gene flow, introgression, or incorrect sample assignments can bias the estimation of the species tree topology and of parameter estimates such as population sizes and divergence times.

Students from underrepresented groups start college with the same level of interest in STEM majors as their peers, but leave STEM at higher rates. We tested the hypothesis that low grades in general chemistry contribute to this “weeding,” using records from 25,768 students. In the first course of a general chemistry series, grade gaps based on binary gender, race/ethnicity, socioeconomic status, and family education background ranged from 0.12 to 0.54 on a four-point scale. Gaps persisted when the analysis controlled for academic preparation, indicating that students from underrepresented groups underperformed relative to their capability. Underrepresented students were less likely than well-represented peers to persist in chemistry if they performed below a C−, but more likely to persist if they got a C or better. This “hyperpersistent zone” suggests that reducing achievement gaps could have a disproportionately large impact on efforts to achieve equity in STEM majors and professions.

Since the initial description of the genomic patterns expected under models of positive selection acting on standing genetic variation and on multiple beneficial mutations—so-called soft selective sweeps—researchers have sought to identify these patterns in natural population data. Indeed, over the past two years, large-scale data analyses have argued that soft sweeps are pervasive across organisms of very different effective population size and mutation rate—humans, Drosophila, and HIV. Yet, others have evaluated the relevance of these models to natural populations, as well as the identifiability of the models relative to other known population-level processes, arguing that soft sweeps are likely to be rare. Here, we look to reconcile these opposing results by carefully evaluating three recent studies and their underlying methodologies. Using population genetic theory, as well as extensive simulation, we find that all three examples are prone to extremely high false-positive rates, incorrectly identifying soft sweeps under both hard sweep and neutral models. Furthermore, we demonstrate that well-fit demographic histories combined with rare hard sweeps serve as the more parsimonious explanation. These findings represent a necessary response to the growing tendency of invoking parameter-heavy, assumption-laden models of pervasive positive selection, and neglecting best practices regarding the construction of proper demographic null models.

Aim Unique amongst birds, megapodes (family Megapodiidae) have exchanged the strategy of incubating eggs with the warmth of their bodies for incubation behaviours that rely entirely on environmental heat sources. Typically, mound‐builders capture heat released from the decomposition of organic materials, while burrow‐nesters lay their eggs in geothermal or solar‐heated soils. The evolutionary path towards novel incubation behaviours has led to ecological and physiological adaptations unique to megapodes. Here, we present a species tree for all extant megapodes that settles long‐standing debates about megapode evolution: namely, their biogeographical origins and ancestral nesting behaviour. Location Australasia. Methods A time‐calibrated multilocus species tree for all extant megapodes was constructed using *beast. We estimated and compared divergence dates for megapodes obtained from molecular rates, fossils, and a combination of fossils and rates. Using this tree, Bayesian estimation of ancestral nesting behaviour was conducted in BayesTraits and ancestral ranges were estimated in BioGeoBEARS. Results Recent dispersal has led to the recolonization of mainland Australia and New Guinea by Megapodius. Bayesian estimation of ancestral states indicates that mound building is the most probable ancestral nesting behaviour in megapodes (posterior probability = 0.75). Burrow nesting was acquired early in the diversification of the family (at least 14 Ma), followed by a single switch back to mound building. Main conclusions Divergence dates and biogeographical reconstructions strongly suggest that dispersal, and not vicariance, led to the isolation of megapodes in Australasia. We propose that flight‐mediated dispersal to environmentally variable islands is responsible for the behavioural lability in nesting behaviours observed in some Megapodius species today.

The recent increase in time-series population genomic data from experimental, natural, and ancient populations has been accompanied by a promising growth in methodologies for inferring demographic and selective parameters from such data. However, these methods have largely presumed that the populations of interest are well-described by the Kingman coalescent. In reality, many groups of organisms, including viruses, marine organisms, and some plants, protists, and fungi, typified by high variance in progeny number, may be best characterized by multiple-merger coalescent models. Estimation of population genetic parameters under Wright-Fisher assumptions for these organisms may thus be prone to serious mis-inference. We propose a novel method for the joint inference of demography and selection under the C-coalescent model, termed Multiple-Merger Coalescent Approximate Bayesian Computation, or MMC-ABC. We first demonstrate mis-inference under the Kingman, and then exhibit the superior performance of MMC-ABC under conditions of skewed offspring distributions. In order to highlight the utility of this approach, we reanalyzed previously published drug-selection lines of influenza A virus. We jointly inferred the extent of progeny-skew inherent to viral replication and identified putative drug-resistance mutations.

Generally, genotypes and phenotypes are expected to be spatially congruent; however, in widespread species complexes with few barriers to dispersal, multiple contact zones, and limited reproductive isolation, discordance between phenotypes and phylogeographic groups is more probable. Wagtails (Motacilla) are a genus of birds with striking plumage pattern variation across the Old World. Up to 13 subspecies are recognized within a single species, yet previous studies using mitochondrial DNA have supported polyphyletic phylogeographic groups that are inconsistent with subspecies plumage characteristics. In this study, we investigate the link between phenotypes and genotype by taking a phylogenetic approach. We use genome-wide SNPs, nuclear introns, and mitochondrial DNA to estimate population structure, isolation by distance, and species relationships. Together, our genetic sampling includes complete species-level sampling and comprehensive coverage of the three most phenotypically diverse Palearctic species. Our study provides strong evidence for species-level patterns of differentiation, however population-level differentiation is less pronounced. SNPs provide a robust estimate of species-level relationships, which are mostly corroborated by a combined analysis of mtDNA and nuclear introns (the first time-calibrated species tree for the genus). However, the mtDNA tree is strongly incongruent and is considered to misrepresent the species phylogeny. The extant wagtail lineages originated during the Pliocene and the Eurasian lineage underwent rapid diversification during the Pleistocene. Three of four widespread Eurasian species exhibit an east-west divide that contradicts both subspecies taxonomy and phenotypic variation. Indeed, SNPs fail to distinguish between phenotypically distinct subspecies within the M. alba and M. flava complexes, and instead support geographical regions, each of which is home to two or more different looking subspecies. This is a major step towards our understanding of wagtail phylogeny compared to previous analyses of fewer species and considerably less sequence data.

In this study, we explore the long-standing issue of how many loci are needed to infer accurate phylogenetic relationships, and whether loci with particular attributes (e.g., parsimony informativeness, variability, gene tree resolution) outperform others. To do so, we use an empirical data set consisting of the seven species of chickadees (Aves: Paridae), an analytically tractable, recently diverged group, and well-studied ecologically but lacking a nuclear phylogeny. We estimate relationships using 40 nuclear loci and mitochondrial DNA using four coalescent-based species tree inference methods (BEST, * BEAST, STEM, STELLS). Collectively, our analyses contrast with previous studies and support a sister relationship between the Black-capped and Carolina Chickadee, two superficially similar species that hybridize along a long zone of contact. Gene flow is a potential source of conflict between nuclear and mitochondrial gene trees, yet we find a significant, albeit low, signal of gene flow. Our results suggest that relatively few loci with high information content may be sufficient for estimating an accurate species tree, but that substantially more loci are necessary for accurate parameter estimation. We provide an empirical reference point for researchers designing sampling protocols with the purpose of inferring phylogenies and population parameters of closely related taxa.

Gender gaps in exam scores or final grades are common in introductory college science and engineering classrooms, with women underperforming relative to men with the same admission test scores or college grade point averages. After failing to close a historically documented gender gap in a large introductory biology course using interventions targeted at training a growth mindset, we implemented interventions designed to reduce student test anxiety. We combined evidence-based exercises based on expressive writing and on reappraising physiological arousal. We also used a valid measure to quantify test anxiety at the start and end of the course. This instrument measures an individual’s self-declared or perceived test anxiety—also called trait anxiety—but not the immediate or “state” anxiety experienced during an actual exam. Consistent with previous reports in the literature, we found that women in this population declared much higher test anxiety than men and that students who declared higher test anxiety had lower exam scores than students who declared lower test anxiety. Although the test anxiety interventions had no impact on the level of self-declared trait anxiety, they did significantly increase student exam performance. The treatment benefits occurred in both men and women. These data suggest that 1) a combination of interventions based on expressive writing and reappraising physiological arousal can be a relatively easy manner to boost exam performance in a large-enrollment science, technology, engineering, and mathematics (STEM) course and encourage emotion regulation; 2) women are more willing than men to declare that they are anxious about exams, but men and women may actually experience the same level of anxiety during the exam itself; and 3) women are underperforming in STEM courses for reasons other than gender-based differences in mindset or test anxiety.