Following the rivers: historical reconstruction of California voles Microtus californicus (Rodentia: Cricetidae) in the deserts of eastern California

The California vole, Microtus californicus, restricted to habitat patches where water is available nearly year-round, is a remnant of the mesic history of the southern Great Basin and Mojave deserts of eastern California. The history of voles in this region is a model for species-edge population dynamics through periods of climatic change. We sampled voles from the eastern deserts of California and examined variation in the mitochondrial cytb gene, three nuclear intron regions, and across 12 nuclear microsatellite markers. Samples are allocated to two mitochondrial clades: one associated with southern California and the other with central and northern California. The limited mtDNA structure largely recovers the geographical distribution, replicated by both nuclear introns and microsatellites. The most remote population, Microtus californicus scirpensis at Tecopa near Death Valley, was the most distinct. This population shares microsatellite alleles with both mtDNA clades, and both its northern clade nuclear introns and southern clade mtDNA sequences support a hybrid origin for this endangered population. The overall patterns support two major invasions into the desert through an ancient system of riparian corridors along streams and lake margins during the latter part of the Pleistocene followed by local in situ divergence subsequent to late Pleistocene and Holocene drying events. Changes in current water resource use could easily remove California voles from parts of the desert landscape

RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language.

Programs for Bayesian inference of phylogeny currently implement a unique and fixed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be specified interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-specification language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous flexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our field. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.]

Probabilistic Graphical Model Representation in Phylogenetics

Recent years have seen a rapid expansion of the model space explored in statistical phylogenetics, emphasizing the need for new approaches to statistical model representation and software development. Clear communication and representation of the chosen model is crucial for: (1) reproducibility of an analysis, (2) model development and (3) software design. Moreover, a unified, clear and understandable framework for model representation lowers the barrier for beginners and non-specialists to grasp complex phylogenetic models, including their assumptions and parameter/variable dependencies. Graphical modeling is a unifying framework that has gained in popularity in the statistical literature in recent years. The core idea is to break complex models into conditionally independent distributions. The strength lies in the comprehensibility, flexibility, and adaptability of this formalism, and the large body of computational work based on it. Graphical models are well-suited to teach statistical models, to facilitate communication among phylogeneticists and in the development of generic software for simulation and statistical inference. Here, we provide an introduction to graphical models for phylogeneticists and extend the standard graphical model representation to the realm of phylogenetics. We introduce a new graphical model component, tree plates, to capture the changing structure of the subgraph corresponding to a phylogenetic tree. We describe a range of phylogenetic models using the graphical model framework and introduce modules to simplify the representation of standard components in large and complex models. Phylogenetic model graphs can be readily used in simulation, maximum likelihood inference, and Bayesian inference using, for example, Metropolis-Hastings or Gibbs sampling of the posterior distribution

Inferring the demographic history of the North American firefly Photinus pyralis

The firefly Photinus pyralis inhabits a wide range of latitudinal and ecological niches, with populations living from temperate to tropical habitats. Despite its broad distribution, its demographic history is unknown. In this study, we modelled and inferred different demographic scenarios for North American populations of P. pyralis, which were collected from Texas to New Jersey. We used a combination of ABC techniques (for multi-population/colonization analyses) and likelihood inference (dadi, StairwayPlot2, PoMo) for single-population demographic inference, which proved useful with our RAD data. We uncovered that the most ancestral North American population lays in Texas, which further colonized the Central region of the US and more recently the North Eastern coast. Our study confidently rejects a demographic scenario where the North Eastern populations colonized more southern populations until reaching Texas. To estimate the age of divergence between of P. pyralis, which provides deeper insights into the history of the entire species, we assembled a multi-locus phylogenetic data covering the genus Photinus. We uncovered that the phylogenetic node leading to P. pyralis lies at the end of the Miocene. Importantly, modelling the demographic history of North American P. pyralis serves as a null model of nucleotide diversity patterns in a widespread native insect species, which will serve in future studies for the detection of adaptation events in this firefly species, as well as a comparison for future studies of other North American insect taxa

PM10- und PM2.5- Emissionspotentiale von Substraten der Tagebaue im Lausitzer Revier

Im Lausitzer Revier werden aktuell 4 Braukohlen-Tagebaue betrieben, die als Quellen für Feinstaub-Emissionen gelten und somit zur lokalen Luftbelastungen beitragen. Berechnungen von möglichen Zusatzbelastungen durch den Tagebaubetrieb ergaben jedoch große Differenzen zu Messungen der Behörden vor Ort. Die Ursachen hierfür liegen in der starren Handhabung von Emissionsfaktoren, die vor allem die durch Winderosion hervorgerufene flächenhafte Emission von PM10 und PM2.5 stark überschätzen. Die Substrate der Hauptarbeitsebenen aller Tagebaue wurden untersucht, um die Materialeigenschaften als auch die Oberflächeneigenschaften, die die Emissionen beeinflussen, zu charakterisieren. Im ersten Schritt wurde mittels Horizontal-Querstromsichtung das Emissionspotential aller Substrate im luftgetrockneten Zustand ermittelt. Hierbei wird bei einer Windgeschwindigkeit von 3 ms-1 das Probenmaterial am Anfang des Windkanals von oben zugeführt und durch die Schwerkraft und die horizontale Strömung nach Größe und aerodynamischen Eigenschaften über die 7 m lange Messstrecke sortiert. Am Ende des Windkanals erfolgte die Messung der Partikelgrößenverteilung der Staubfraktion. Einzelne Proben wurden behutsam rückbefeuchtet und ebenfalls auf diese Weise untersucht. Für Untersuchungen zum Einfluss der Winderosion auf die PM-Emissionen wurde die Messstrecke in voller Länge mit den Substraten befüllt und mit Windgeschwindigkeiten von 6, 8 und 10 ms-1 abgeblasen. Die abgetragene Sedimentmenge als auch die PM- Emissionen wurden am Ende der Messstrecke erfasst. Die Emissionspotentiale der Substrate nahmen in folgender Reihung ab: homogene Kohle > homogene Feinsande > heterogene Feinsande > heterogene Grobsande > heterogene (faserige) Kohle und lagen in den Bereichen 475 µgg-1 bis 22 µgg-1. Die Befeuchtung der sandigen Substrate auf ca. 2 M% erbrachte eine Reduzierung der PM-Emissionen um 95%, die der Kohle um 45%. Für die durch Winderosion ausgelösten PM-Emissionen ergab sich eine andere Reihenfolge der sandigen Substrate: Kohle > heterogene Feinsande > heterogene Grobsande > homogene Feinsande. Hier wurden vor allem durch den Impakt saltierender Sandkörner Staubpartikel freigesetzt. Für jede der Windgeschwindigkeiten ergab sich über die Zeit eine maximale Abtrags- und PM-Emissionsrate. Wurde diese erreicht, blieb die Oberfläche stabil und es erfolgten keine weiteren PM-Emissionen

P\u3csup\u3e3\u3c/sup\u3e: Phylogenetic posterior prediction in RevBayes

© The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. Tests of absolute model fit are crucial in model-based inference because poorly structured models can lead to biased parameter estimates. In Bayesian inference, posterior predictive simulations can be used to test absolute model fit. However, such tests have not been commonly practiced in phylogenetic inference due to a lack of convenient and flexible software. Here, we describe our newly implemented tests of model fit using posterior predictive testing, based on both data- and inference-based test statistics, in the phylogenetics software RevBayes. This new implementation makes a large spectrum of models available for use through a user-friendly and flexible interface

MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site dN/dS rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software

Posterior summarisation in Bayesian phylogenetics using Tracer 1.7

Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.status: publishe