New Approaches for Inferring Phylogenies in the Presence of Paralogs.

The availability of whole genome sequences was expected to supply essentially unlimited data for phylogenetics. However, strict reliance on single-copy genes for this purpose has drastically limited the amount of data that can be used. Here, we review several approaches for increasing the amount of data used for phylogenetic inference, focusing on methods that allow for the inclusion of duplicated genes (paralogs). Recently developed methods that are robust to high levels of incomplete lineage sorting also appear to be robust to the inclusion of paralogs, suggesting a promising way to take full advantage of genomic data. We discuss the pitfalls of these approaches, as well as further avenues for research.

Phylogenetic inference using generative adversarial networks.

MOTIVATION: The application of machine learning approaches in phylogenetics has been impeded by the vast model space associated with inference. Supervised machine learning approaches require data from across this space to train models. Because of this, previous approaches have typically been limited to inferring relationships among unrooted quartets of taxa, where there are only three possible topologies. Here, we explore the potential of generative adversarial networks (GANs) to address this limitation. GANs consist of a generator and a discriminator: at each step, the generator aims to create data that is similar to real data, while the discriminator attempts to distinguish generated and real data. By using an evolutionary model as the generator, we use GANs to make evolutionary inferences. Since a new model can be considered at each iteration, heuristic searches of complex model spaces are possible. Thus, GANs offer a potential solution to the challenges of applying machine learning in phylogenetics. RESULTS: We developed phyloGAN, a GAN that infers phylogenetic relationships among species. phyloGAN takes as input a concatenated alignment, or a set of gene alignments, and infers a phylogenetic tree either considering or ignoring gene tree heterogeneity. We explored the performance of phyloGAN for up to 15 taxa in the concatenation case and 6 taxa when considering gene tree heterogeneity. Error rates are relatively low in these simple cases. However, run times are slow and performance metrics suggest issues during training. Future work should explore novel architectures that may result in more stable and efficient GANs for phylogenetics. AVAILABILITY AND IMPLEMENTATION: phyloGAN is available on github: https://github.com/meganlsmith/phyloGAN/.

Applications of machine learning in phylogenetics.

Machine learning has increasingly been applied to a wide range of questions in phylogenetic inference. Supervised machine learning approaches that rely on simulated training data have been used to infer tree topologies and branch lengths, to select substitution models, and to perform downstream inferences of introgression and diversification. Here, we review how researchers have used several promising machine learning approaches to make phylogenetic inferences. Despite the promise of these methods, several barriers prevent supervised machine learning from reaching its full potential in phylogenetics. We discuss these barriers and potential paths forward. In the future, we expect that the application of careful network designs and data encodings will allow supervised machine learning to accommodate the complex processes that continue to confound traditional phylogenetic methods.

The use of Lentilactobacillus buchneri PJB1 and Lactiplantibacillus plantarum MTD1 on the ensiling of whole-plant corn silage, snaplage, and high-moisture corn.

Experiments were conducted over a 3-yr period to evaluate the effects of bacterial inoculants on the fermentation profile and aerobic stability of whole-plant corn silage (WPC), snaplage (SNA), and high-moisture corn (HMC). Whole-plant corn was inoculated with Lentilactobacillus buchneri PJB1 in combination with Lactiplantibacillus plantarum MTD1 or with Lpb. plantarum alone (experiments 1 and 2). Snaplage (experiment 3) and HMC (experiments 4 and 5) were inoculated with Len. buchneri in combination with Lpb. plantarum or with Len. buchneri alone. After inoculation, the feedstuffs were ensiled in 7.57-L silos and stored at 21 ± 2°C for 30 or 90 d. In experiment 5, silage was subjected to air stress for 2 h every 2 wk through 42 d and then for 2 h/wk until 90 d and had samples analyzed for their bacterial community composition by metagenomics. Overall, in all experiments, silages inoculated with Len. buchneri alone or in combination with Lpb. plantarum had more acetic acid and 1,2-propanediol and fewer yeasts than uninoculated silages. After 30 d of ensiling, inoculation with Len. buchneri alone or in combination with Lpb. plantarum did not affect the aerobic stability of SNA, but it slightly increased the stability of WPC and markedly improved the stability of HMC. After 90 d of ensiling, inoculation with Len. buchneri alone or in combination with Lpb. plantarum markedly improved the aerobic stability of WPC, SNA, and HMC. In experiment 5, inoculation increased the relative abundance (RA) of Lactobacillaceae and reduced the RA of Enterobacteriaceae and Leuconostocaceae in HMC at 30 and 90 d and the RA of Clostridiaceae in non-air-stressed HMC at 90 d. Air-stressed HMC inoculated with Len. buchneri had less lactic acid, more acetic acid and 1,2-propanediol, and markedly greater aerobic stability than uninoculated air-stressed HMC at 90 d. In conclusion, inoculation with Len. buchneri PJB1 alone or in combination with Lpb. plantarum MTD1 increased the production of acetic acid and 1,2-propanediol, inhibited yeasts development, and improved the aerobic stability of WPC, SNA, and HMC. In HMC, inoculation markedly improved aerobic stability as soon as after 30 d of ensiling, and after 90 d, inoculation improved stability even under air stress conditions.

Using all Gene Families Vastly Expands Data Available for Phylogenomic Inference.

Traditionally, single-copy orthologs have been the gold standard in phylogenomics. Most phylogenomic studies identify putative single-copy orthologs using clustering approaches and retain families with a single sequence per species. This limits the amount of data available by excluding larger families. Recent advances have suggested several ways to include data from larger families. For instance, tree-based decomposition methods facilitate the extraction of orthologs from large families. Additionally, several methods for species tree inference are robust to the inclusion of paralogs and could use all of the data from larger families. Here, we explore the effects of using all families for phylogenetic inference by examining relationships among 26 primate species in detail and by analyzing five additional data sets. We compare single-copy families, orthologs extracted using tree-based decomposition approaches, and all families with all data. We explore several species tree inference methods, finding that identical trees are returned across nearly all subsets of the data and methods for primates. The relationships among Platyrrhini remain contentious; however, the species tree inference method matters more than the subset of data used. Using data from larger gene families drastically increases the number of genes available and leads to consistent estimates of branch lengths, nodal certainty and concordance, and inferences of introgression in primates. For the other data sets, topological inferences are consistent whether single-copy families or orthologs extracted using decomposition approaches are analyzed. Using larger gene families is a promising approach to include more data in phylogenomics without sacrificing accuracy, at least when high-quality genomes are available.

Species limits and diversification of the Dendropsophus rubicundulus subgroup (Anura, Hylidae) in Neotropical savannas.

Understanding the processes that generate and maintain biodiversity at and below the species level is a central goal of evolutionary biology. Here we explore the spatial and temporal drivers of diversification of the treefrog subgroup Dendropsophus rubicundulus, a subgroup of the D. microcephalus species group, over periods of pronounced geological and climatic changes in the Neotropical savannas that they inhabit. This subgroup currently comprises 11 recognized species distributed across the Brazilian and Bolivian savannas, but the taxonomy has been in a state of flux, necessitating reexamination. Using newly generated single nucleotide polymorphism (SNP) data from restriction-site associated DNA sequencing (RADseq) and mitochondrial 16S sequence data for ∼150 specimens, we inferred phylogenetic relationships, tested species limits using a model-based approach, and estimated divergence times to gain insights into the geographic and climatic events that affected the diversification of this subgroup. Our results recognized at least nine species: D. anataliasiasi, D. araguaya, D. cerradensis, D. elianeae, D. jimi, D. rubicundulus, D. tritaeniatus, D. rozenmani, and D. sanborni. Although we did not collect SNP data for the latter two species, they are likely distinct based on mitochondrial data. In addition, we found genetic structure within the widespread species D. rubicundulus, which comprises three allopatric lineages connected by gene flow upon secondary contact. We also found evidence of population structure and perhaps undescribed diversity in D. elianeae, which warrants further study. The D. rubicundulus subgroup is estimated to have originated in the Late Miocene (∼5.45 million years ago), with diversification continuing through the Pliocene and Early Pleistocene, followed by the most recent divergence of D. rubicundulus lineages in the Middle Pleistocene. The epeirogenic uplift followed by erosion and denudation of the central Brazilian plateau throughout the Pliocene and Pleistocene, in combination with the increasing frequency and amplitude of climatic fluctuations during the Pleistocene, was important for generating and structuring diversity at or below the species level in the D. rubicundulus subgroup.

The Frequency and Topology of Pseudoorthologs.

Phylogenetics has long relied on the use of orthologs, or genes related through speciation events, to infer species relationships. However, identifying orthologs is difficult because gene duplication can obscure relationships among genes. Researchers have been particularly concerned with the insidious effects of pseudoorthologs-duplicated genes that are mistaken for orthologs because they are present in a single copy in each sampled species. Because gene tree topologies of pseudoorthologs may differ from the species tree topology, they have often been invoked as the cause of counterintuitive results in phylogenetics. Despite these perceived problems, no previous work has calculated the probabilities of pseudoortholog topologies or has been able to circumscribe the regions of parameter space in which pseudoorthologs are most likely to occur. Here, we introduce a model for calculating the probabilities and branch lengths of orthologs and pseudoorthologs, including concordant and discordant pseudoortholog topologies, on a rooted three-taxon species tree. We show that the probability of orthologs is high relative to the probability of pseudoorthologs across reasonable regions of parameter space. Furthermore, the probabilities of the two discordant topologies are equal and never exceed that of the concordant topology, generally being much lower. We describe the species tree topologies most prone to generating pseudoorthologs, finding that they are likely to present problems to phylogenetic inference irrespective of the presence of pseudoorthologs. Overall, our results suggest that pseudoorthologs are unlikely to mislead inferences of species relationships under the biological scenarios considered here.[Birth-death model; orthologs; paralogs; phylogenetics.].

Species Tree Inference Methods Intended to Deal with Incomplete Lineage Sorting Are Robust to the Presence of Paralogs.

Many recent phylogenetic methods have focused on accurately inferring species trees when there is gene tree discordance due to incomplete lineage sorting (ILS). For almost all of these methods, and for phylogenetic methods in general, the data for each locus are assumed to consist of orthologous, single-copy sequences. Loci that are present in more than a single copy in any of the studied genomes are excluded from the data. These steps greatly reduce the number of loci available for analysis. The question we seek to answer in this study is: what happens if one runs such species tree inference methods on data where paralogy is present, in addition to or without ILS being present? Through simulation studies and analyses of two large biological data sets, we show that running such methods on data with paralogs can still provide accurate results. We use multiple different methods, some of which are based directly on the multispecies coalescent model, and some of which have been proven to be statistically consistent under it. We also treat the paralogous loci in multiple ways: from explicitly denoting them as paralogs, to randomly selecting one copy per species. In all cases, the inferred species trees are as accurate as equivalent analyses using single-copy orthologs. Our results have significant implications for the use of ILS-aware phylogenomic analyses, demonstrating that they do not have to be restricted to single-copy loci. This will greatly increase the amount of data that can be used for phylogenetic inference.[Gene duplication and loss; incomplete lineage sorting; multispecies coalescent; orthology; paralogy.].

The role of multiple Pleistocene refugia in promoting diversification in the Pacific Northwest.

Pleistocene glacial cycles drastically changed the distributions of taxa endemic to temperate rainforests in the Pacific Northwest, with many experiencing reduced habitat suitability during glacial periods. In this study, we investigate whether glacial cycles promoted intraspecific divergence and whether subsequent range changes led to secondary contact and gene flow. For seven invertebrate species endemic to the PNW, we estimated species distribution models (SDMs) and projected them onto current and historical climate conditions to assess how habitat suitability changed during glacial cycles. Using single nucleotide polymorphism (SNP) data from these species, we assessed population genetic structure and used a machine-learning approach to compare models with and without gene flow between populations upon secondary contact after the last glacial maximum (LGM). Finally, we estimated divergence times and rates of gene flow between populations. SDMs suggest that there was less suitable habitat in the North Cascades and Northern Rocky Mountains during glacial compared to interglacial periods, resulting in reduced habitat suitability and increased habitat fragmentation during the LGM. Our genomic data identify population structure in all taxa, and support gene flow upon secondary contact in five of the seven taxa. Parameter estimates suggest that population divergences date to the later Pleistocene for most populations. Our results support a role of refugial dynamics in driving intraspecific divergence in the Cascades Range. In these invertebrates, population structure often does not correspond to current biogeographic or environmental barriers. Rather, population structure may reflect refugial lineages that have since expanded their ranges, often leading to secondary contact between once isolated lineages.

Genomic evidence of an ancient inland temperate rainforest in the Pacific Northwest of North America.

The disjunct temperate rainforests of the Pacific Northwest of North America (PNW) are characterized by late-successional dominant tree species Thuja plicata (western redcedar) and Tsuga heterophylla (western hemlock). The demographic histories of these species, along with the PNW rainforest ecosystem in its entirety, have been heavily impacted by geological and climatic changes the PNW has experienced over the last 5 million years, including mountain orogeny and repeated Pleistocene glaciations. These environmental events have ultimately shaped the history of these species, with inland populations potentially being extirpated during the Pleistocene glaciations. Here, we collect genomic data for both species across their ranges to test multiple demographic models, each reflecting a different phylogeographical hypothesis on how the ecosystem-dominating species may have responded to dramatic climatic change. Our results indicate that inland and coastal populations in both species diverged ~2.5 million years ago in the early Pleistocene and experienced decreases in population size during glacial cycles, with subsequent population expansion. Importantly, we found evidence for gene flow between coastal and inland populations during the mid-Holocene. It is likely that intermittent migration in these species during this time has prevented allopatric speciation via genetic drift alone. In conclusion, our results from combining genomic data and demographic inference procedures establish that populations of the ecosystem dominants Thuja plicata and Tsuga heterophylla persisted in refugia located in both the coastal and inland regions of the PNW throughout the Pleistocene, with populations expanding and contracting in response to glacial cycles with occasional gene flow.

Caffeine consumption and onset of alcohol use among early adolescents.

Preventing or delaying the onset of alcohol use among children and youth is an important public health goal. One possible factor in alcohol use onset among early adolescents is caffeine. The aim of this study was to assess the possible contribution of caffeine to the onset of alcohol use during early adolescence. We used data from the Young Mountaineer Health Study Cohort. Survey data were collected from 1349 (response rate: 80.7%) 6th grade students (mean age at baseline 11.5 years) in 20 middle schools in West Virginia during the fall of 2020, and again approximately 6 months later in spring of 2021. We limited our analyses to students reporting never having used any form of alcohol at baseline. Logistic regression was employed in multivariable analyses and both Odds Ratios and Relative Risks reported. At follow-up, almost 14% of participants reported having consumed alcohol at least once and 57% used caffeine of 100 mg + daily. In multivariable analyses we controlled for social and behavioral variables known to impact tobacco use. Caffeine use was operationalized as a three-level factor: no use, <100 mg per day, and 100 + mg per day, with the latter being the approximate equivalent of the minimum of a typical cup of coffee or can of energy drink. Caffeine use of 100 mg + per day was significantly related to alcohol use at 6-months follow-up (OR: 1.79, RR: 1.56, p = .037). We conclude that caffeine consumption among 11-12-year-old adolescents may be a factor in early onset of alcohol use.

Parental support and monitoring as associated with adolescent alcohol and tobacco use by gender and age.

BACKGROUND: Parental support (PS) and parental monitoring (PM) are known protective factors against adolescent substance use (SU). However, little is known about whether PS and PM may affect SU outcomes differently by gender and age. This study examined the relationship between PS and PM and adolescent SU, specifically alcohol and tobacco use, stratified by gender and age group. METHODS: Middle and high school students (n = 2351, 48.5% Female) completed surveys of self-reported SU, perceived PS and PM, and socioeconomic background. Age group was defined dichotomously as grade 7-8 Middle school and grade 9-10 High school students. PS and PM were each measured using previously validated tools. SU was measured by lifetime and past 30 days cigarette/alcohol use. One-way ANOVA and binary logistic regression models were completed. Odds ratios and means were reported. RESULTS: PS and PM were significantly and negatively related to all outcome variables regardless of gender and age group. Mean differences in PS and PM were insignificant between age groups. Between genders, PM scores were significantly higher for girls (14.05) compared to boys (13.48) (p < 0.01). Odds Ratios of all four SU types (for alcohol and tobacco use) increased with higher age group, with ORs ranging from 1.45-2.61 (p < .05). CONCLUSIONS: PS and PM were protective against SU for all participants, consistent with previous literature. Girls reported greater parental monitoring than boys, irrespective of age-group. While girls experienced higher levels of monitoring, they did not report lower SU than boys. This suggests that monitoring girls more closely than boys appears unnecessary in preventing adolescent SU. Finally, PS was a more significant factor in preventing SU for older adolescents (high school aged group) than for younger adolescents, irrespective of gender suggesting that PS may be more impactful and important as adolescents age. As children mature, particularly from middle school to high school, PS may play a larger role in preventing SU for older adolescents compared to younger ones.

Population genetic structure and demographic history of the lone star tick, Amblyomma americanum (Ixodida: Ixodidae): New evidence supporting old records.

Range expansions are a potential outcome of changes in habitat suitability, which commonly result as a consequence of climate change. Hypotheses on such changes in the geographic distribution of a certain species can be evaluated using population genetic structure and demography. In this study we explore the population genetic structure, genetic variability, demographic history of, and habitat suitability for Amblyomma americanum, a North American tick species that is a known vector of several pathogenic microorganisms. We used a double digestion restriction site-associated DNA sequencing technique (dd-RAD seq) and discovered 8,181 independent single nucleotide polymorphisms (SNPs) in 189 ticks from across the geographic range of the species. Genetic diversity was low, particularly when considering the broad geographic range of this species. The edge populations were less diverse than populations belonging to the historic range, possibly indicative of a range expansion, but this hypothesis was not statistically supported by a test based on genetic data. Nonetheless, moderate levels of population structure and substructure were detected between geographic regions. For New England, demographic and species distribution models support a scenario where A. americanum was present in more northern locations in the past, underwent a bottleneck, and subsequently recovered. These results are consistent with a hypothesis that this species is re-establishing in this area, rather than one focused on range expansion from the south. This hypothesis is consistent with old records describing the presence of A. americanum in the northeastern US in the early colonial period.

Integrating life history traits into predictive phylogeography.

Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine-learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive frameworks due to difficulties inherent to the scoring of trait data across a taxonomically broad set of taxa. We refine predictive frameworks from two North American systems, the inland temperate rainforests of the Pacific Northwest and the Southwestern Arid Lands (SWAL), by incorporating a number of organismal trait variables. Our results indicate that incorporating life history traits as predictor variables improves the performance of the supervised machine-learning approach to predictive phylogeography, especially for the SWAL system, in which predictions made from only taxonomic and climate variables meets only moderate success. In particular, traits related to reproduction (e.g., reproductive mode; clutch size) and trophic level appear to be particularly informative to the predictive framework. Predictive frameworks offer an important mechanism for integration of organismal trait, environmental data, and genetic data in phylogeographic studies.

Combining allele frequency and tree-based approaches improves phylogeographic inference from natural history collections.

Model selection approaches in phylogeography have allowed researchers to evaluate the support for competing demographic histories, which provides a mode of inference and a measure of uncertainty in understanding climatic and spatial influences on intraspecific diversity. Here, to rank all models in the comparison set and determine what proportion of the total support the top-ranked model garners, we conduct model selection using two analytical approaches-allele frequency-based, implemented in fastsimcoal2, and gene tree-based, implemented in phrapl. We then expand this model selection framework by including an assessment of absolute fit of the models to the data. For this, we utilize DNA isolated from existing natural history collections that span the distribution of red alder (Alnus rubra) in the Pacific Northwest of North America to generate genomic data for the evaluation of 13 demographic scenarios. The quality of DNA recovered from herbarium specimen leaf tissue was assessed for its utility and effectiveness in demographic model selection, specifically in the two approaches mentioned. We present strong support for the use of herbarium tissue in the generation of genomic DNA, albeit with the inclusion of additional quality control checks prior to library preparation and analyses with multiple approaches that incorporate various data. Analyses with allele frequency spectra and gene trees predominantly support A. rubra having experienced an ancient vicariance event with intermittent and frequent gene flow between the disjunct populations. Additionally, the data consistently fit the most frequently selected model, corroborating the model selection techniques. Finally, these results suggest that the A. rubra disjunct populations do not represent separate species.

An evaluation of the effectiveness of a chemical additive based on sodium benzoate, potassium sorbate, and sodium nitrite on the fermentation and aerobic stability of corn silage.

We evaluated the effectiveness of an additive comprising sodium benzoate, potassium sorbate, and sodium nitrite (SSL) as active ingredients for its ability to improve the aerobic stability of corn silages made in North America. In experiment 1, treatment with SSL (1.5 and 2.0 L/t) on whole-plant corn (WPC) was compared with treatment with an additive containing buffered propionic acid and citric acid (BPA; 2 L/t) on corn harvested at 32 and 38% dry matter and ensiled for 120 d. Silage treated with BPA was higher in ammonia-N and propionic acid relative to other treatments. Treatments with all of the additives had numerically, but not statistically, fewer yeasts compared with untreated silage. Both application rates of SSL resulted in lower concentrations of ethanol compared with untreated and BPA silages. Treatment with BPA improved the aerobic stability of silages compared with untreated silage, but the effect from SSL was markedly greater. In experiment 2, WPC was untreated or treated with 2 or 3 L of SSL/t or a microbial inoculant containing Enterococcus faecium M74, Lactobacillus plantarum CH6072, and Lactobacillus buchneri LN1819 (final total lactic acid bacteria application rate of 150,000 cfu/g of fresh forage). Silages were air stressed for 24 h at 28 and 42 d of storage and ensiled for 49 d before opening. Inoculation had no effect on acid end products, ethanol, number of yeasts, or aerobic stability compared with other treatments. Treatment with SSL decreased the amount of ethanol, had no effect on number of yeasts, and improved aerobic stability in a dose-dependent manner compared with other treatments. In experiment 3, WPC was untreated or treated with 2 L of SSL/t and ensiled for 5, 15, and 30 d. Treatment with SSL resulted in silage with fewer yeasts and lower concentrations of ethanol after all times of ensiling compared with untreated silage. In addition, SSL improved aerobic stability after each period of ensiling, but the effect was more at 15 and 30 d compared with 5 d of storage. Treating WPC with SSL can improve the aerobic stability of corn silage made in North America, and the effect can be observed as soon as 5 d after ensiling.

Social Profile of Middle School-Aged Adolescents Who Use Electronic Cigarettes: Implications for Primary Prevention.

Electronic cigarette (EC) use continues to increase among adolescents. From a primary prevention point of view, an important gap in our knowledge includes determining whether young smokers that use EC maintain a distinct social profile from kids who use combustible cigarettes (CC). Survey data from middle school students in West Virginia, USA were collected between September and November of 2015 (N = 6547, response rate 84.7%) as part of a state wide school-based mental health intervention program. Data was analyzed using multinomial logistic regression for categorical data. The results show that compared to never smokers, EC-only users possessed a weaker social support and parental monitoring profile and performed worse in school. Additionally, EC-only users were more likely to feel alienated from school, to associate with delinquent peers, to spend time outside late at night, and to engage in unsupervised gatherings with their friends. In 11 of 13 statistical models no difference was observed between EC-only users compared with CC-only users. However, dual users (that had used both EC and CC in their lifetime) demonstrated a significantly greater risk profile compared with EC-only users. We conclude that middle school-aged kids that use EC share a similar risk profile as kids of the same age that use CC. Similar to traditional cigarette smoking, EC use in young adolescents is likely to be a social marker of a pathway to further delinquency and should therefore be subject to primary prevention approaches.

Demographic model selection using random forests and the site frequency spectrum.

Phylogeographic data sets have grown from tens to thousands of loci in recent years, but extant statistical methods do not take full advantage of these large data sets. For example, approximate Bayesian computation (ABC) is a commonly used method for the explicit comparison of alternate demographic histories, but it is limited by the "curse of dimensionality" and issues related to the simulation and summarization of data when applied to next-generation sequencing (NGS) data sets. We implement here several improvements to overcome these difficulties. We use a Random Forest (RF) classifier for model selection to circumvent the curse of dimensionality and apply a binned representation of the multidimensional site frequency spectrum (mSFS) to address issues related to the simulation and summarization of large SNP data sets. We evaluate the performance of these improvements using simulation and find low overall error rates (~7%). We then apply the approach to data from Haplotrema vancouverense, a land snail endemic to the Pacific Northwest of North America. Fifteen demographic models were compared, and our results support a model of recent dispersal from coastal to inland rainforests. Our results demonstrate that binning is an effective strategy for the construction of a mSFS and imply that the statistical power of RF when applied to demographic model selection is at least comparable to traditional ABC algorithms. Importantly, by combining these strategies, large sets of models with differing numbers of populations can be evaluated.

Prevalence of substance use among middle school-aged e-cigarette users compared with cigarette smokers, nonusers, and dual users: Implications for primary prevention.

BACKGROUND: The objective of this study was to compare the prevalence of substance use in e-cigarette (EC)-only users with combustible cigarette (CC)-only users, dual users, and nonusers in a large sample of middle school-aged adolescents. METHODS: Population-based cross-sectional school survey conducted in 15 middle schools in 3 counties in West Virginia in the United States between October and December of 2015 (N = 6547, girls = 49.6%; response rate 84.7%). RESULTS: Approximately 4.3% of participants had used EC only, 4.5% had used CC only, and around 5.5% were dual users. Nonusers had the lowest prevalence of all 9 forms of substance use assessed in the study (i.e., chewing tobacco, any alcohol, drunkenness, marijuana, sniffing, prescription drugs, hallucinogens, synthetic marijuana, and bath salts), followed by EC and CC users. Dual users had the highest prevalence of 8 of 9 forms of substance use. Multinomial logistic regression models showed that EC-only users had significantly greater odds over nonusers of using 8 of 9 types of substances included in the study. Conversely, EC-only users had significantly lower odds of using 7 of 9 types of substances when compared with dual users. However, EC-only users did not differ from CC-only users in odds of use in any of the 9 substances included in this analysis. CONCLUSIONS: Among middle school-aged adolescents, EC-only users do not differ from CC-only users in odds for other forms of substance use. Primary prevention programs should consider EC use initiation as a pathway to greater risk of other licit and illicit substances among young adolescents.

Identifying cryptic diversity with predictive phylogeography.

Identifying units of biological diversity is a major goal of organismal biology. An increasing literature has focused on the importance of cryptic diversity, defined as the presence of deeply diverged lineages within a single species. While most discoveries of cryptic lineages proceed on a taxon-by-taxon basis, rapid assessments of biodiversity are needed to inform conservation policy and decision-making. Here, we introduce a predictive framework for phylogeography that allows rapidly identifying cryptic diversity. Our approach proceeds by collecting environmental, taxonomic and genetic data from codistributed taxa with known phylogeographic histories. We define these taxa as a reference set, and categorize them as either harbouring or lacking cryptic diversity. We then build a random forest classifier that allows us to predict which other taxa endemic to the same biome are likely to contain cryptic diversity. We apply this framework to data from two sets of disjunct ecosystems known to harbour taxa with cryptic diversity: the mesic temperate forests of the Pacific Northwest of North America and the arid lands of Southwestern North America. The predictive approach presented here is accurate, with prediction accuracies placed between 65% and 98.79% depending of the ecosystem. This seems to indicate that our method can be successfully used to address ecosystem-level questions about cryptic diversity. Further, our application for the prediction of the cryptic/non-cryptic nature of unknown species is easily applicable and provides results that agree with recent discoveries from those systems. Our results demonstrate that the transition of phylogeography from a descriptive to a predictive discipline is possible and effective.