Probabilistic short-term volcanic hazard in phases of unrest: A case study for tephra fallout

NASA Astrophysics Data System (ADS)

Selva, Jacopo; Costa, Antonio; Sandri, Laura; Macedonio, Giovanni; Marzocchi, Warner

2014-12-01

During volcanic crises, volcanologists estimate the impact of possible imminent eruptions usually through deterministic modeling of the effects of one or a few preestablished scenarios. Despite such an approach may bring an important information to the decision makers, the sole use of deterministic scenarios does not allow scientists to properly take into consideration all uncertainties, and it cannot be used to assess quantitatively the risk because the latter unavoidably requires a probabilistic approach. We present a model based on the concept of Bayesian event tree (hereinafter named BET_VH_ST, standing for Bayesian event tree for short-term volcanic hazard), for short-term near-real-time probabilistic volcanic hazard analysis formulated for any potential hazardous phenomenon accompanying an eruption. The specific goal of BET_VH_ST is to produce a quantitative assessment of the probability of exceedance of any potential level of intensity for a given volcanic hazard due to eruptions within restricted time windows (hours to days) in any area surrounding the volcano, accounting for all natural and epistemic uncertainties. BET_VH_ST properly assesses the conditional probability at each level of the event tree accounting for any relevant information derived from the monitoring system, theoretical models, and the past history of the volcano, propagating any relevant epistemic uncertainty underlying these assessments. As an application example of the model, we apply BET_VH_ST to assess short-term volcanic hazard related to tephra loading during Major Emergency Simulation Exercise, a major exercise at Mount Vesuvius that took place from 19 to 23 October 2006, consisting in a blind simulation of Vesuvius reactivation, from the early warning phase up to the final eruption, including the evacuation of a sample of about 2000 people from the area at risk. The results show that BET_VH_ST is able to produce short-term forecasts of the impact of tephra fall during a rapidly evolving crisis, accurately accounting for and propagating all uncertainties and enabling rational decision making under uncertainty.

Understanding the Scalability of Bayesian Network Inference using Clique Tree Growth Curves

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob

2009-01-01

Bayesian networks (BNs) are used to represent and efficiently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to perform computation in BNs is clique tree clustering and propagation. In this approach, BN computation consists of propagation in a clique tree compiled from a Bayesian network. There is a lack of understanding of how clique tree computation time, and BN computation time in more general, depends on variations in BN size and structure. On the one hand, complexity results tell us that many interesting BN queries are NP-hard or worse to answer, and it is not hard to find application BNs where the clique tree approach in practice cannot be used. On the other hand, it is well-known that tree-structured BNs can be used to answer probabilistic queries in polynomial time. In this article, we develop an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN's non-root nodes to the number of root nodes, or (ii) the expected number of moral edges in their moral graphs. Our approach is based on combining analytical and experimental results. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for each set. For the special case of bipartite BNs, we consequently have two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, we systematically increase the degree of the root nodes in bipartite Bayesian networks, and find that root clique growth is well-approximated by Gompertz growth curves. It is believed that this research improves the understanding of the scaling behavior of clique tree clustering, provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms, and presents an aid for analytical trade-off studies of clique tree clustering using growth curves.

Bayesian Ensemble Trees (BET) for Clustering and Prediction in Heterogeneous Data

PubMed Central

Duan, Leo L.; Clancy, John P.; Szczesniak, Rhonda D.

2016-01-01

We propose a novel “tree-averaging” model that utilizes the ensemble of classification and regression trees (CART). Each constituent tree is estimated with a subset of similar data. We treat this grouping of subsets as Bayesian Ensemble Trees (BET) and model them as a Dirichlet process. We show that BET determines the optimal number of trees by adapting to the data heterogeneity. Compared with the other ensemble methods, BET requires much fewer trees and shows equivalent prediction accuracy using weighted averaging. Moreover, each tree in BET provides variable selection criterion and interpretation for each subset. We developed an efficient estimating procedure with improved estimation strategies in both CART and mixture models. We demonstrate these advantages of BET with simulations and illustrate the approach with a real-world data example involving regression of lung function measurements obtained from patients with cystic fibrosis. Supplemental materials are available online. PMID:27524872

A Bayesian compound stochastic process for modeling nonstationary and nonhomogeneous sequence evolution.

PubMed

Blanquart, Samuel; Lartillot, Nicolas

2006-11-01

Variations of nucleotidic composition affect phylogenetic inference conducted under stationary models of evolution. In particular, they may cause unrelated taxa sharing similar base composition to be grouped together in the resulting phylogeny. To address this problem, we developed a nonstationary and nonhomogeneous model accounting for compositional biases. Unlike previous nonstationary models, which are branchwise, that is, assume that base composition only changes at the nodes of the tree, in our model, the process of compositional drift is totally uncoupled from the speciation events. In addition, the total number of events of compositional drift distributed across the tree is directly inferred from the data. We implemented the method in a Bayesian framework, relying on Markov Chain Monte Carlo algorithms, and applied it to several nucleotidic data sets. In most cases, the stationarity assumption was rejected in favor of our nonstationary model. In addition, we show that our method is able to resolve a well-known artifact. By Bayes factor evaluation, we compared our model with 2 previously developed nonstationary models. We show that the coupling between speciations and compositional shifts inherent to branchwise models may lead to an overparameterization, resulting in a lesser fit. In some cases, this leads to incorrect conclusions, concerning the nature of the compositional biases. In contrast, our compound model more flexibly adapts its effective number of parameters to the data sets under investigation. Altogether, our results show that accounting for nonstationary sequence evolution may require more elaborate and more flexible models than those currently used.

Revealing the ISO/IEC 9126-1 Clique Tree for COTS Software Evaluation

NASA Technical Reports Server (NTRS)

Morris, A. Terry

2007-01-01

Previous research has shown that acyclic dependency models, if they exist, can be extracted from software quality standards and that these models can be used to assess software safety and product quality. In the case of commercial off-the-shelf (COTS) software, the extracted dependency model can be used in a probabilistic Bayesian network context for COTS software evaluation. Furthermore, while experts typically employ Bayesian networks to encode domain knowledge, secondary structures (clique trees) from Bayesian network graphs can be used to determine the probabilistic distribution of any software variable (attribute) using any clique that contains that variable. Secondary structures, therefore, provide insight into the fundamental nature of graphical networks. This paper will apply secondary structure calculations to reveal the clique tree of the acyclic dependency model extracted from the ISO/IEC 9126-1 software quality standard. Suggestions will be provided to describe how the clique tree may be exploited to aid efficient transformation of an evaluation model.

A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction

PubMed Central

De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David

2016-01-01

Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. PMID:25281847

DLRS: gene tree evolution in light of a species tree.

PubMed

Sjöstrand, Joel; Sennblad, Bengt; Arvestad, Lars; Lagergren, Jens

2012-11-15

PrIME-DLRS (or colloquially: 'Delirious') is a phylogenetic software tool to simultaneously infer and reconcile a gene tree given a species tree. It accounts for duplication and loss events, a relaxed molecular clock and is intended for the study of homologous gene families, for example in a comparative genomics setting involving multiple species. PrIME-DLRS uses a Bayesian MCMC framework, where the input is a known species tree with divergence times and a multiple sequence alignment, and the output is a posterior distribution over gene trees and model parameters. PrIME-DLRS is available for Java SE 6+ under the New BSD License, and JAR files and source code can be downloaded from http://code.google.com/p/jprime/. There is also a slightly older C++ version available as a binary package for Ubuntu, with download instructions at http://prime.sbc.su.se. The C++ source code is available upon request. joel.sjostrand@scilifelab.se or jens.lagergren@scilifelab.se. PrIME-DLRS is based on a sound probabilistic model (Åkerborg et al., 2009) and has been thoroughly validated on synthetic and biological datasets (Supplementary Material online).

Calibrated birth-death phylogenetic time-tree priors for bayesian inference.

PubMed

Heled, Joseph; Drummond, Alexei J

2015-05-01

Here we introduce a general class of multiple calibration birth-death tree priors for use in Bayesian phylogenetic inference. All tree priors in this class separate ancestral node heights into a set of "calibrated nodes" and "uncalibrated nodes" such that the marginal distribution of the calibrated nodes is user-specified whereas the density ratio of the birth-death prior is retained for trees with equal values for the calibrated nodes. We describe two formulations, one in which the calibration information informs the prior on ranked tree topologies, through the (conditional) prior, and the other which factorizes the prior on divergence times and ranked topologies, thus allowing uniform, or any arbitrary prior distribution on ranked topologies. Although the first of these formulations has some attractive properties, the algorithm we present for computing its prior density is computationally intensive. However, the second formulation is always faster and computationally efficient for up to six calibrations. We demonstrate the utility of the new class of multiple-calibration tree priors using both small simulations and a real-world analysis and compare the results to existing schemes. The two new calibrated tree priors described in this article offer greater flexibility and control of prior specification in calibrated time-tree inference and divergence time dating, and will remove the need for indirect approaches to the assessment of the combined effect of calibration densities and tree priors in Bayesian phylogenetic inference. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks

PubMed Central

2017-01-01

Whole-genome sequencing of pathogens from host samples becomes more and more routine during infectious disease outbreaks. These data provide information on possible transmission events which can be used for further epidemiologic analyses, such as identification of risk factors for infectivity and transmission. However, the relationship between transmission events and sequence data is obscured by uncertainty arising from four largely unobserved processes: transmission, case observation, within-host pathogen dynamics and mutation. To properly resolve transmission events, these processes need to be taken into account. Recent years have seen much progress in theory and method development, but existing applications make simplifying assumptions that often break up the dependency between the four processes, or are tailored to specific datasets with matching model assumptions and code. To obtain a method with wider applicability, we have developed a novel approach to reconstruct transmission trees with sequence data. Our approach combines elementary models for transmission, case observation, within-host pathogen dynamics, and mutation, under the assumption that the outbreak is over and all cases have been observed. We use Bayesian inference with MCMC for which we have designed novel proposal steps to efficiently traverse the posterior distribution, taking account of all unobserved processes at once. This allows for efficient sampling of transmission trees from the posterior distribution, and robust estimation of consensus transmission trees. We implemented the proposed method in a new R package phybreak. The method performs well in tests of both new and published simulated data. We apply the model to five datasets on densely sampled infectious disease outbreaks, covering a wide range of epidemiological settings. Using only sampling times and sequences as data, our analyses confirmed the original results or improved on them: the more realistic infection times place more confidence in the inferred transmission trees. PMID:28545083

Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks.

PubMed

Klinkenberg, Don; Backer, Jantien A; Didelot, Xavier; Colijn, Caroline; Wallinga, Jacco

2017-05-01

Whole-genome sequencing of pathogens from host samples becomes more and more routine during infectious disease outbreaks. These data provide information on possible transmission events which can be used for further epidemiologic analyses, such as identification of risk factors for infectivity and transmission. However, the relationship between transmission events and sequence data is obscured by uncertainty arising from four largely unobserved processes: transmission, case observation, within-host pathogen dynamics and mutation. To properly resolve transmission events, these processes need to be taken into account. Recent years have seen much progress in theory and method development, but existing applications make simplifying assumptions that often break up the dependency between the four processes, or are tailored to specific datasets with matching model assumptions and code. To obtain a method with wider applicability, we have developed a novel approach to reconstruct transmission trees with sequence data. Our approach combines elementary models for transmission, case observation, within-host pathogen dynamics, and mutation, under the assumption that the outbreak is over and all cases have been observed. We use Bayesian inference with MCMC for which we have designed novel proposal steps to efficiently traverse the posterior distribution, taking account of all unobserved processes at once. This allows for efficient sampling of transmission trees from the posterior distribution, and robust estimation of consensus transmission trees. We implemented the proposed method in a new R package phybreak. The method performs well in tests of both new and published simulated data. We apply the model to five datasets on densely sampled infectious disease outbreaks, covering a wide range of epidemiological settings. Using only sampling times and sequences as data, our analyses confirmed the original results or improved on them: the more realistic infection times place more confidence in the inferred transmission trees.

Recursive algorithms for phylogenetic tree counting.

PubMed

Gavryushkina, Alexandra; Welch, David; Drummond, Alexei J

2013-10-28

In Bayesian phylogenetic inference we are interested in distributions over a space of trees. The number of trees in a tree space is an important characteristic of the space and is useful for specifying prior distributions. When all samples come from the same time point and no prior information available on divergence times, the tree counting problem is easy. However, when fossil evidence is used in the inference to constrain the tree or data are sampled serially, new tree spaces arise and counting the number of trees is more difficult. We describe an algorithm that is polynomial in the number of sampled individuals for counting of resolutions of a constraint tree assuming that the number of constraints is fixed. We generalise this algorithm to counting resolutions of a fully ranked constraint tree. We describe a quadratic algorithm for counting the number of possible fully ranked trees on n sampled individuals. We introduce a new type of tree, called a fully ranked tree with sampled ancestors, and describe a cubic time algorithm for counting the number of such trees on n sampled individuals. These algorithms should be employed for Bayesian Markov chain Monte Carlo inference when fossil data are included or data are serially sampled.

Estimating the Effective Sample Size of Tree Topologies from Bayesian Phylogenetic Analyses

PubMed Central

Lanfear, Robert; Hua, Xia; Warren, Dan L.

2016-01-01

Bayesian phylogenetic analyses estimate posterior distributions of phylogenetic tree topologies and other parameters using Markov chain Monte Carlo (MCMC) methods. Before making inferences from these distributions, it is important to assess their adequacy. To this end, the effective sample size (ESS) estimates how many truly independent samples of a given parameter the output of the MCMC represents. The ESS of a parameter is frequently much lower than the number of samples taken from the MCMC because sequential samples from the chain can be non-independent due to autocorrelation. Typically, phylogeneticists use a rule of thumb that the ESS of all parameters should be greater than 200. However, we have no method to calculate an ESS of tree topology samples, despite the fact that the tree topology is often the parameter of primary interest and is almost always central to the estimation of other parameters. That is, we lack a method to determine whether we have adequately sampled one of the most important parameters in our analyses. In this study, we address this problem by developing methods to estimate the ESS for tree topologies. We combine these methods with two new diagnostic plots for assessing posterior samples of tree topologies, and compare their performance on simulated and empirical data sets. Combined, the methods we present provide new ways to assess the mixing and convergence of phylogenetic tree topologies in Bayesian MCMC analyses. PMID:27435794

Phylogenetic inference under varying proportions of indel-induced alignment gaps

PubMed Central

Dwivedi, Bhakti; Gadagkar, Sudhindra R

2009-01-01

Background The effect of alignment gaps on phylogenetic accuracy has been the subject of numerous studies. In this study, we investigated the relationship between the total number of gapped sites and phylogenetic accuracy, when the gaps were introduced (by means of computer simulation) to reflect indel (insertion/deletion) events during the evolution of DNA sequences. The resulting (true) alignments were subjected to commonly used gap treatment and phylogenetic inference methods. Results (1) In general, there was a strong – almost deterministic – relationship between the amount of gap in the data and the level of phylogenetic accuracy when the alignments were very "gappy", (2) gaps resulting from deletions (as opposed to insertions) contributed more to the inaccuracy of phylogenetic inference, (3) the probabilistic methods (Bayesian, PhyML & "MLε, " a method implemented in DNAML in PHYLIP) performed better at most levels of gap percentage when compared to parsimony (MP) and distance (NJ) methods, with Bayesian analysis being clearly the best, (4) methods that treat gapped sites as missing data yielded less accurate trees when compared to those that attribute phylogenetic signal to the gapped sites (by coding them as binary character data – presence/absence, or as in the MLε method), and (5) in general, the accuracy of phylogenetic inference depended upon the amount of available data when the gaps resulted from mainly deletion events, and the amount of missing data when insertion events were equally likely to have caused the alignment gaps. Conclusion When gaps in an alignment are a consequence of indel events in the evolution of the sequences, the accuracy of phylogenetic analysis is likely to improve if: (1) alignment gaps are categorized as arising from insertion events or deletion events and then treated separately in the analysis, (2) the evolutionary signal provided by indels is harnessed in the phylogenetic analysis, and (3) methods that utilize the phylogenetic signal in indels are developed for distance methods too. When the true homology is known and the amount of gaps is 20 percent of the alignment length or less, the methods used in this study are likely to yield trees with 90–100 percent accuracy. PMID:19698168

Comparing nonparametric Bayesian tree priors for clonal reconstruction of tumors.

PubMed

Deshwar, Amit G; Vembu, Shankar; Morris, Quaid

2015-01-01

Statistical machine learning methods, especially nonparametric Bayesian methods, have become increasingly popular to infer clonal population structure of tumors. Here we describe the treeCRP, an extension of the Chinese restaurant process (CRP), a popular construction used in nonparametric mixture models, to infer the phylogeny and genotype of major subclonal lineages represented in the population of cancer cells. We also propose new split-merge updates tailored to the subclonal reconstruction problem that improve the mixing time of Markov chains. In comparisons with the tree-structured stick breaking prior used in PhyloSub, we demonstrate superior mixing and running time using the treeCRP with our new split-merge procedures. We also show that given the same number of samples, TSSB and treeCRP have similar ability to recover the subclonal structure of a tumor…

Hazard Assessment for POPOCATÉPETL Volcano Using Hasset: a Probability Event Tree Tool to Evaluate Future Eruptive Scenarios

NASA Astrophysics Data System (ADS)

Ferrés, D.; Reyes Pimentel, T. A.; Espinasa-Pereña, R.; Nieto, A.; Sobradelo, R.; Flores, X.; González Huesca, A. E.; Ramirez, A.

2013-05-01

Popocatépetl volcano is one of the most active in Latin America. During its last cycle of activity, beginning at the end of 1994, more than 40 episodes of dome construction and destruction have occurred inside the summit crater. Most of these episodes finished with eruptions of VEI 1-2. Eruptions of higher intensity were also registered in 1997, 2001 and 2009, of VEI≥3, which produced eruptive columns up to 8 km high and abundant and frequent ash falls on the villages at the eastern sector of the volcano. The January 22nd 2001 eruption also produced pyroclastic flows that followed several streams on the volcanic cone, reaching 4 to 6 km, and transforming to mudflows with ranges up to 15 km. The capital, Mexico City, is within the radius of 80 km from Popocatépetl volcano and can be affected by ash fall during the first months of the rainy season (May to July). Other important cities, such as Puebla and Atlixco, are located 15 to 30 km from the crater. Several villages of the states of México, Puebla and Morelos, which have a total population of 40,000 people, are inside the radius of 12 to 15 km, where the impacts of any of the products of an eruption, including pyroclastic flows, are possible. This high exposure of people and infrastructure around Popocatépetl volcano emphasizes the need of tools for early warning and the development of preventive actions to protect the population from volcanic phenomena. The diagnosis of the volcanic activity, based on the information provided by the monitoring systems, and the prognosis of the evolution of the volcano in the short-term is made by the Scientific Advisory Committee, formed by volcanologists of the National Autonomous University of Mexico, and by CENAPRED staff. From this prognosis, the alert level for the people is determined and it is spread by the code of the traffic light of volcanic alert. A volcanic event tree was constructed with the advisory of the scientific committee in the recent seismic-eruptive crisis of April-May 2012, in order to identify the most probable processes in which this unrest could have developed and to contribute to the diagnosis task. In this research, we propose a comparison between the processes identified in this preliminary volcanic event tree and another elaborated using a Hazard Assessment Event Tree probability tool (HASSET), built on a bayesian event tree structure, using mainly the information of the known eruptive history of Popocatépetl. The HASSET method is based on Bayesian Inference and is used to assess volcanic hazard of future eruptive scenarios, by evaluating the most relevant sources of uncertainty that play a role in estimating the future probability of occurrence of a specific volcanic event. The final goal is to find the most useful tools to make the diagnosis and prognosis of the Popocatépetl volcanic activity, integrating the known eruptive history of the volcano, the experience of the scientific committee and the information provided by the monitoring systems, in an interactive and user-friendly way.

Barcoding Neotropical birds: assessing the impact of nonmonophyly in a highly diverse group.

PubMed

Chaves, Bárbara R N; Chaves, Anderson V; Nascimento, Augusto C A; Chevitarese, Juliana; Vasconcelos, Marcelo F; Santos, Fabrício R

2015-07-01

In this study, we verified the power of DNA barcodes to discriminate Neotropical birds using Bayesian tree reconstructions of a total of 7404 COI sequences from 1521 species, including 55 Brazilian species with no previous barcode data. We found that 10.4% of species were nonmonophyletic, most likely due to inaccurate taxonomy, incomplete lineage sorting or hybridization. At least 0.5% of the sequences (2.5% of the sampled species) retrieved from GenBank were associated with database errors (poor-quality sequences, NuMTs, misidentification or unnoticed hybridization). Paraphyletic species (5.8% of the total) can be related to rapid speciation events leading to nonreciprocal monophyly between recently diverged sister species, or to absence of synapomorphies in the small COI region analysed. We also performed two series of genetic distance calculations under the K2P model for intraspecific and interspecific comparisons: the first included all COI sequences, and the second included only monophyletic taxa observed in the Bayesian trees. As expected, the mean and median pairwise distances were smaller for intraspecific than for interspecific comparisons. However, there was no precise 'barcode gap', which was shown to be larger in the monophyletic taxon data set than for the data from all species, as expected. Our results indicated that although database errors may explain some of the difficulties in the species discrimination of Neotropical birds, distance-based barcode assignment may also be compromised because of the high diversity of bird species and more complex speciation events in the Neotropics. © 2014 John Wiley & Sons Ltd.

Historical reconstruction of climatic and elevation preferences and the evolution of cloud forest-adapted tree ferns in Mesoamerica.

PubMed

Sosa, Victoria; Ornelas, Juan Francisco; Ramírez-Barahona, Santiago; Gándara, Etelvina

2016-01-01

Cloud forests, characterized by a persistent, frequent or seasonal low-level cloud cover and fragmented distribution, are one of the most threatened habitats, especially in the Neotropics. Tree ferns are among the most conspicuous elements in these forests, and ferns are restricted to regions in which minimum temperatures rarely drop below freezing and rainfall is high and evenly distributed around the year. Current phylogeographic data suggest that some of the cloud forest-adapted species remained in situ or expanded to the lowlands during glacial cycles and contracted allopatrically during the interglacials. Although the observed genetic signals of population size changes of cloud forest-adapted species including tree ferns correspond to predicted changes by Pleistocene climate change dynamics, the observed patterns of intraspecific lineage divergence showed temporal incongruence. Here we combined phylogenetic analyses, ancestral area reconstruction, and divergence time estimates with climatic and altitudinal data (environmental space) for phenotypic traits of tree fern species to make inferences about evolutionary processes in deep time. We used phylogenetic Bayesian inference and geographic and altitudinal distribution of tree ferns to investigate ancestral area and elevation and environmental preferences of Mesoamerican tree ferns. The phylogeny was then used to estimate divergence times and ask whether the ancestral area and elevation and environmental shifts were linked to climatic events and historical climatic preferences. Bayesian trees retrieved Cyathea, Alsophyla, Gymnosphaera and Sphaeropteris in monophyletic clades. Splits for species in these genera found in Mesoamerican cloud forests are recent, from the Neogene to the Quaternary, Australia was identified as the ancestral area for the clades of these genera, except for Gymnosphaera that was Mesoamerica. Climate tolerance was not divergent from hypothesized ancestors for the most significant variables or elevation. For elevational shifts, we found repeated change from low to high elevations. Our data suggest that representatives of Cyatheaceae main lineages migrated from Australia to Mesoamerican cloud forests in different times and have persisted in these environmentally unstable areas but extant species diverged recentrly from their ancestors.

Historical reconstruction of climatic and elevation preferences and the evolution of cloud forest-adapted tree ferns in Mesoamerica

PubMed Central

2016-01-01

Background Cloud forests, characterized by a persistent, frequent or seasonal low-level cloud cover and fragmented distribution, are one of the most threatened habitats, especially in the Neotropics. Tree ferns are among the most conspicuous elements in these forests, and ferns are restricted to regions in which minimum temperatures rarely drop below freezing and rainfall is high and evenly distributed around the year. Current phylogeographic data suggest that some of the cloud forest-adapted species remained in situ or expanded to the lowlands during glacial cycles and contracted allopatrically during the interglacials. Although the observed genetic signals of population size changes of cloud forest-adapted species including tree ferns correspond to predicted changes by Pleistocene climate change dynamics, the observed patterns of intraspecific lineage divergence showed temporal incongruence. Methods Here we combined phylogenetic analyses, ancestral area reconstruction, and divergence time estimates with climatic and altitudinal data (environmental space) for phenotypic traits of tree fern species to make inferences about evolutionary processes in deep time. We used phylogenetic Bayesian inference and geographic and altitudinal distribution of tree ferns to investigate ancestral area and elevation and environmental preferences of Mesoamerican tree ferns. The phylogeny was then used to estimate divergence times and ask whether the ancestral area and elevation and environmental shifts were linked to climatic events and historical climatic preferences. Results Bayesian trees retrieved Cyathea, Alsophyla, Gymnosphaera and Sphaeropteris in monophyletic clades. Splits for species in these genera found in Mesoamerican cloud forests are recent, from the Neogene to the Quaternary, Australia was identified as the ancestral area for the clades of these genera, except for Gymnosphaera that was Mesoamerica. Climate tolerance was not divergent from hypothesized ancestors for the most significant variables or elevation. For elevational shifts, we found repeated change from low to high elevations. Conclusions Our data suggest that representatives of Cyatheaceae main lineages migrated from Australia to Mesoamerican cloud forests in different times and have persisted in these environmentally unstable areas but extant species diverged recentrly from their ancestors. PMID:27896030

Bayesian models for comparative analysis integrating phylogenetic uncertainty.

PubMed

de Villemereuil, Pierre; Wells, Jessie A; Edwards, Robert D; Blomberg, Simon P

2012-06-28

Uncertainty in comparative analyses can come from at least two sources: a) phylogenetic uncertainty in the tree topology or branch lengths, and b) uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow) and inflated significance in hypothesis testing (e.g. p-values will be too small). Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible general purpose tool for phylogenetic comparative analyses, particularly for modelling in the face of phylogenetic uncertainty and accounting for measurement error or individual variation in explanatory variables. Code for all models is provided in the BUGS model description language.

Bayesian models for comparative analysis integrating phylogenetic uncertainty

PubMed Central

2012-01-01

Background Uncertainty in comparative analyses can come from at least two sources: a) phylogenetic uncertainty in the tree topology or branch lengths, and b) uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow) and inflated significance in hypothesis testing (e.g. p-values will be too small). Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. Methods We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. Results We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Conclusions Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible general purpose tool for phylogenetic comparative analyses, particularly for modelling in the face of phylogenetic uncertainty and accounting for measurement error or individual variation in explanatory variables. Code for all models is provided in the BUGS model description language. PMID:22741602

The space of ultrametric phylogenetic trees.

PubMed

Gavryushkin, Alex; Drummond, Alexei J

2016-08-21

The reliability of a phylogenetic inference method from genomic sequence data is ensured by its statistical consistency. Bayesian inference methods produce a sample of phylogenetic trees from the posterior distribution given sequence data. Hence the question of statistical consistency of such methods is equivalent to the consistency of the summary of the sample. More generally, statistical consistency is ensured by the tree space used to analyse the sample. In this paper, we consider two standard parameterisations of phylogenetic time-trees used in evolutionary models: inter-coalescent interval lengths and absolute times of divergence events. For each of these parameterisations we introduce a natural metric space on ultrametric phylogenetic trees. We compare the introduced spaces with existing models of tree space and formulate several formal requirements that a metric space on phylogenetic trees must possess in order to be a satisfactory space for statistical analysis, and justify them. We show that only a few known constructions of the space of phylogenetic trees satisfy these requirements. However, our results suggest that these basic requirements are not enough to distinguish between the two metric spaces we introduce and that the choice between metric spaces requires additional properties to be considered. Particularly, that the summary tree minimising the square distance to the trees from the sample might be different for different parameterisations. This suggests that further fundamental insight is needed into the problem of statistical consistency of phylogenetic inference methods. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Estimating phylogenetic relationships despite discordant gene trees across loci: the species tree of a diverse species group of feather mites (Acari: Proctophyllodidae).

PubMed

Knowles, Lacey L; Klimov, Pavel B

2011-11-01

With the increased availability of multilocus sequence data, the lack of concordance of gene trees estimated for independent loci has focused attention on both the biological processes producing the discord and the methodologies used to estimate phylogenetic relationships. What has emerged is a suite of new analytical tools for phylogenetic inference--species tree approaches. In contrast to traditional phylogenetic methods that are stymied by the idiosyncrasies of gene trees, approaches for estimating species trees explicitly take into account the cause of discord among loci and, in the process, provides a direct estimate of phylogenetic history (i.e. the history of species divergence, not divergence of specific loci). We illustrate the utility of species tree estimates with an analysis of a diverse group of feather mites, the pinnatus species group (genus Proctophyllodes). Discord among four sequenced nuclear loci is consistent with theoretical expectations, given the short time separating speciation events (as evident by short internodes relative to terminal branch lengths in the trees). Nevertheless, many of the relationships are well resolved in a Bayesian estimate of the species tree; the analysis also highlights ambiguous aspects of the phylogeny that require additional loci. The broad utility of species tree approaches is discussed, and specifically, their application to groups with high speciation rates--a history of diversification with particular prevalence in host/parasite systems where species interactions can drive rapid diversification.

Using Bayesian neural networks to classify forest scenes

NASA Astrophysics Data System (ADS)

Vehtari, Aki; Heikkonen, Jukka; Lampinen, Jouko; Juujarvi, Jouni

1998-10-01

We present results that compare the performance of Bayesian learning methods for neural networks on the task of classifying forest scenes into trees and background. Classification task is demanding due to the texture richness of the trees, occlusions of the forest scene objects and diverse lighting conditions under operation. This makes it difficult to determine which are optimal image features for the classification. A natural way to proceed is to extract many different types of potentially suitable features, and to evaluate their usefulness in later processing stages. One approach to cope with large number of features is to use Bayesian methods to control the model complexity. Bayesian learning uses a prior on model parameters, combines this with evidence from a training data, and the integrates over the resulting posterior to make predictions. With this method, we can use large networks and many features without fear of overfitting. For this classification task we compare two Bayesian learning methods for multi-layer perceptron (MLP) neural networks: (1) The evidence framework of MacKay uses a Gaussian approximation to the posterior weight distribution and maximizes with respect to hyperparameters. (2) In a Markov Chain Monte Carlo (MCMC) method due to Neal, the posterior distribution of the network parameters is numerically integrated using the MCMC method. As baseline classifiers for comparison we use (3) MLP early stop committee, (4) K-nearest-neighbor and (5) Classification And Regression Tree.

Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

PubMed

Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

2017-10-11

Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

Phylogeny of the cycads based on multiple single-copy nuclear genes: congruence of concatenated parsimony, likelihood and species tree inference methods

PubMed Central

Salas-Leiva, Dayana E.; Meerow, Alan W.; Calonje, Michael; Griffith, M. Patrick; Francisco-Ortega, Javier; Nakamura, Kyoko; Stevenson, Dennis W.; Lewis, Carl E.; Namoff, Sandra

2013-01-01

Background and aims Despite a recent new classification, a stable phylogeny for the cycads has been elusive, particularly regarding resolution of Bowenia, Stangeria and Dioon. In this study, five single-copy nuclear genes (SCNGs) are applied to the phylogeny of the order Cycadales. The specific aim is to evaluate several gene tree–species tree reconciliation approaches for developing an accurate phylogeny of the order, to contrast them with concatenated parsimony analysis and to resolve the erstwhile problematic phylogenetic position of these three genera. Methods DNA sequences of five SCNGs were obtained for 20 cycad species representing all ten genera of Cycadales. These were analysed with parsimony, maximum likelihood (ML) and three Bayesian methods of gene tree–species tree reconciliation, using Cycas as the outgroup. A calibrated date estimation was developed with Bayesian methods, and biogeographic analysis was also conducted. Key Results Concatenated parsimony, ML and three species tree inference methods resolve exactly the same tree topology with high support at most nodes. Dioon and Bowenia are the first and second branches of Cycadales after Cycas, respectively, followed by an encephalartoid clade (Macrozamia–Lepidozamia–Encephalartos), which is sister to a zamioid clade, of which Ceratozamia is the first branch, and in which Stangeria is sister to Microcycas and Zamia. Conclusions A single, well-supported phylogenetic hypothesis of the generic relationships of the Cycadales is presented. However, massive extinction events inferred from the fossil record that eliminated broader ancestral distributions within Zamiaceae compromise accurate optimization of ancestral biogeographical areas for that hypothesis. While major lineages of Cycadales are ancient, crown ages of all modern genera are no older than 12 million years, supporting a recent hypothesis of mostly Miocene radiations. This phylogeny can contribute to an accurate infrafamilial classification of Zamiaceae. PMID:23997230

Rearrangement moves on rooted phylogenetic networks

PubMed Central

Gambette, Philippe; van Iersel, Leo; Jones, Mark; Scornavacca, Celine

2017-01-01

Phylogenetic tree reconstruction is usually done by local search heuristics that explore the space of the possible tree topologies via simple rearrangements of their structure. Tree rearrangement heuristics have been used in combination with practically all optimization criteria in use, from maximum likelihood and parsimony to distance-based principles, and in a Bayesian context. Their basic components are rearrangement moves that specify all possible ways of generating alternative phylogenies from a given one, and whose fundamental property is to be able to transform, by repeated application, any phylogeny into any other phylogeny. Despite their long tradition in tree-based phylogenetics, very little research has gone into studying similar rearrangement operations for phylogenetic network—that is, phylogenies explicitly representing scenarios that include reticulate events such as hybridization, horizontal gene transfer, population admixture, and recombination. To fill this gap, we propose “horizontal” moves that ensure that every network of a certain complexity can be reached from any other network of the same complexity, and “vertical” moves that ensure reachability between networks of different complexities. When applied to phylogenetic trees, our horizontal moves—named rNNI and rSPR—reduce to the best-known moves on rooted phylogenetic trees, nearest-neighbor interchange and rooted subtree pruning and regrafting. Besides a number of reachability results—separating the contributions of horizontal and vertical moves—we prove that rNNI moves are local versions of rSPR moves, and provide bounds on the sizes of the rNNI neighborhoods. The paper focuses on the most biologically meaningful versions of phylogenetic networks, where edges are oriented and reticulation events clearly identified. Moreover, our rearrangement moves are robust to the fact that networks with higher complexity usually allow a better fit with the data. Our goal is to provide a solid basis for practical phylogenetic network reconstruction. PMID:28763439

MDTS: automatic complex materials design using Monte Carlo tree search.

PubMed

M Dieb, Thaer; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-01-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

MDTS: automatic complex materials design using Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Dieb, Thaer M.; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-12-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

Competition alters tree growth responses to climate at individual and stand scales

Treesearch

Kevin R. Ford; Ian K. Breckheimer; Jerry F. Franklin; James A. Freund; Steve J. Kroiss; Andrew J. Larson; Elinore J. Theobald; Janneke HilleRisLambers

2017-01-01

Understanding how climate affects tree growth is essential for assessing climate change impacts on forests but can be confounded by effects of competition, which strongly influences tree responses to climate. We characterized the joint influences of tree size, competition, and climate on diameter growth using hierarchical Bayesian methods applied to permanent sample...

BAYESIAN METHODS FOR REGIONAL-SCALE EUTROPHICATION MODELS. (R830887)

EPA Science Inventory

We demonstrate a Bayesian classification and regression tree (CART) approach to link multiple environmental stressors to biological responses and quantify uncertainty in model predictions. Such an approach can: (1) report prediction uncertainty, (2) be consistent with the amou...

Bayesian, maximum parsimony and UPGMA models for inferring the phylogenies of antelopes using mitochondrial markers.

PubMed

Khan, Haseeb A; Arif, Ibrahim A; Bahkali, Ali H; Al Farhan, Ahmad H; Al Homaidan, Ali A

2008-10-06

This investigation was aimed to compare the inference of antelope phylogenies resulting from the 16S rRNA, cytochrome-b (cyt-b) and d-loop segments of mitochondrial DNA using three different computational models including Bayesian (BA), maximum parsimony (MP) and unweighted pair group method with arithmetic mean (UPGMA). The respective nucleotide sequences of three Oryx species (Oryx leucoryx, Oryx dammah and Oryx gazella) and an out-group (Addax nasomaculatus) were aligned and subjected to BA, MP and UPGMA models for comparing the topologies of respective phylogenetic trees. The 16S rRNA region possessed the highest frequency of conserved sequences (97.65%) followed by cyt-b (94.22%) and d-loop (87.29%). There were few transitions (2.35%) and none transversions in 16S rRNA as compared to cyt-b (5.61% transitions and 0.17% transversions) and d-loop (11.57% transitions and 1.14% transversions) while comparing the four taxa. All the three mitochondrial segments clearly differentiated the genus Addax from Oryx using the BA or UPGMA models. The topologies of all the gamma-corrected Bayesian trees were identical irrespective of the marker type. The UPGMA trees resulting from 16S rRNA and d-loop sequences were also identical (Oryx dammah grouped with Oryx leucoryx) to Bayesian trees except that the UPGMA tree based on cyt-b showed a slightly different phylogeny (Oryx dammah grouped with Oryx gazella) with a low bootstrap support. However, the MP model failed to differentiate the genus Addax from Oryx. These findings demonstrate the efficiency and robustness of BA and UPGMA methods for phylogenetic analysis of antelopes using mitochondrial markers.

Bayesian, Maximum Parsimony and UPGMA Models for Inferring the Phylogenies of Antelopes Using Mitochondrial Markers

PubMed Central

Khan, Haseeb A.; Arif, Ibrahim A.; Bahkali, Ali H.; Al Farhan, Ahmad H.; Al Homaidan, Ali A.

2008-01-01

This investigation was aimed to compare the inference of antelope phylogenies resulting from the 16S rRNA, cytochrome-b (cyt-b) and d-loop segments of mitochondrial DNA using three different computational models including Bayesian (BA), maximum parsimony (MP) and unweighted pair group method with arithmetic mean (UPGMA). The respective nucleotide sequences of three Oryx species (Oryx leucoryx, Oryx dammah and Oryx gazella) and an out-group (Addax nasomaculatus) were aligned and subjected to BA, MP and UPGMA models for comparing the topologies of respective phylogenetic trees. The 16S rRNA region possessed the highest frequency of conserved sequences (97.65%) followed by cyt-b (94.22%) and d-loop (87.29%). There were few transitions (2.35%) and none transversions in 16S rRNA as compared to cyt-b (5.61% transitions and 0.17% transversions) and d-loop (11.57% transitions and 1.14% transversions) while comparing the four taxa. All the three mitochondrial segments clearly differentiated the genus Addax from Oryx using the BA or UPGMA models. The topologies of all the gamma-corrected Bayesian trees were identical irrespective of the marker type. The UPGMA trees resulting from 16S rRNA and d-loop sequences were also identical (Oryx dammah grouped with Oryx leucoryx) to Bayesian trees except that the UPGMA tree based on cyt-b showed a slightly different phylogeny (Oryx dammah grouped with Oryx gazella) with a low bootstrap support. However, the MP model failed to differentiate the genus Addax from Oryx. These findings demonstrate the efficiency and robustness of BA and UPGMA methods for phylogenetic analysis of antelopes using mitochondrial markers. PMID:19204824

Demographic expansion of two Tamarix species along the Yellow River caused by geological events and climate change in the Pleistocene.

PubMed

Liang, Hong-Yan; Feng, Zhi-Pei; Pei, Bing; Li, Yong; Yang, Xi-Tian

2018-01-08

The geological events and climatic fluctuations during the Pleistocene played important roles in shaping patterns of species distribution. However, few studies have evaluated the patterns of species distribution that were influenced by the Yellow River. The present work analyzed the demography of two endemic tree species that are widely distributed along the Yellow River, Tamarix austromongolica and Tamarix chinensis, to understand the role of the Yellow River and Pleistocene climate in shaping their distribution patterns. The most common chlorotype, chlorotype 1, was found in all populations, and its divergence time could be dated back to 0.19 million years ago (Ma). This dating coincides well with the formation of the modern Yellow River and the timing of Marine Isotope Stages 5e-6 (MIS 5e-6). Bayesian reconstructions along with models of paleodistribution revealed that these two species experienced a demographic expansion in population size during the Quaternary period. Approximate Bayesian computation analyses supported a scenario of expansion approximately from the upper to lower reaches of the Yellow River. Our results provide support for the roles of the Yellow River and the Pleistocene climate in driving demographic expansion of the populations of T. austromongolica and T. chinensis. These findings are useful for understanding the effects of geological events and past climatic fluctuations on species distribution patterns.

Supermatrix and species tree methods resolve phylogenetic relationships within the big cats, Panthera (Carnivora: Felidae).

PubMed

Davis, Brian W; Li, Gang; Murphy, William J

2010-07-01

The pantherine lineage of cats diverged from the remainder of modern Felidae less than 11 million years ago and consists of the five big cats of the genus Panthera, the lion, tiger, jaguar, leopard, and snow leopard, as well as the closely related clouded leopard. A significant problem exists with respect to the precise phylogeny of these highly threatened great cats. Despite multiple publications on the subject, no two molecular studies have reconstructed Panthera with the same topology. These evolutionary relationships remain unresolved partially due to the recent and rapid radiation of pantherines in the Pliocene, individual speciation events occurring within less than 1 million years, and probable introgression between lineages following their divergence. We provide an alternative, highly supported interpretation of the evolutionary history of the pantherine lineage using novel and published DNA sequence data from the autosomes, both sex chromosomes and the mitochondrial genome. New sequences were generated for 39 single-copy regions of the felid Y chromosome, as well as four mitochondrial and four autosomal gene segments, totaling 28.7 kb. Phylogenetic analysis of these new data, combined with all published data in GenBank, highlighted the prevalence of phylogenetic disparities stemming either from the amplification of a mitochondrial to nuclear translocation event (numt), or errors in species identification. Our 47.6 kb combined dataset was analyzed as a supermatrix and with respect to individual partitions using maximum likelihood and Bayesian phylogenetic inference, in conjunction with Bayesian Estimation of Species Trees (BEST) which accounts for heterogeneous gene histories. Our results yield a robust consensus topology supporting the monophyly of lion and leopard, with jaguar sister to these species, as well as a sister species relationship of tiger and snow leopard. These results highlight new avenues for the study of speciation genomics and understanding the historical events surrounding the origin of the members of this lineage. Copyright 2010 Elsevier Inc. All rights reserved.

Decision-Tree Program

NASA Technical Reports Server (NTRS)

Buntine, Wray

1994-01-01

IND computer program introduces Bayesian and Markov/maximum-likelihood (MML) methods and more-sophisticated methods of searching in growing trees. Produces more-accurate class-probability estimates important in applications like diagnosis. Provides range of features and styles with convenience for casual user, fine-tuning for advanced user or for those interested in research. Consists of four basic kinds of routines: data-manipulation, tree-generation, tree-testing, and tree-display. Written in C language.

The evolution of virulence in primate malaria parasites based on Bayesian reconstructions of ancestral states.

PubMed

Garamszegi, László Zsolt

2011-02-01

Plasmodium parasites, the causative agents of malaria, are generally considered as harmful parasites, but many of them cause mild symptoms. Little is known about the evolutionary history and phylogenetic constraints that generate this interspecific variation in virulence due to uncertainties about the phylogenetic associations of parasites. Here, to account for such phylogenetic uncertainty, phylogenetic methods based on Bayesian statistics were followed in combination with sequence data from five genes to estimate the ancestral state of virulence in primate Plasmodium parasites. When recent parasites were categorised according to the damage caused to the host, Bayesian estimates of ancestral states indicated that the acquisition of a harmful host exploitation strategy is more likely to be a recent evolutionary event than a result of an ancient change in a character state altering virulence. On the contrary, there was more evidence for moderate host exploitation having a deep origin along the phylogenetic tree. Moreover, the evolution of host severity is determined by the phylogenetic relationships of parasites, as severity gains did not appear randomly on the evolutionary tree. Such phylogenetic constraints can be mediated by the acquisition of virulence genes. As the impact of a parasite on a host is the result of both the parasite's investment in reproduction and host sensitivity, virulence was also estimated by calculating peak parasitemia after eliminating host effects. A directional random-walk evolutionary model showed that the ancestral primate malarias reproduced at very low parasitemia in their hosts. Consequently, the extreme variation in the outcome of malaria infection in different host species can be better understood in light of the phylogeny of parasites. Copyright © 2010 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

System Analysis by Mapping a Fault-tree into a Bayesian-network

NASA Astrophysics Data System (ADS)

Sheng, B.; Deng, C.; Wang, Y. H.; Tang, L. H.

2018-05-01

In view of the limitations of fault tree analysis in reliability assessment, Bayesian Network (BN) has been studied as an alternative technology. After a brief introduction to the method for mapping a Fault Tree (FT) into an equivalent BN, equations used to calculate the structure importance degree, the probability importance degree and the critical importance degree are presented. Furthermore, the correctness of these equations is proved mathematically. Combining with an aircraft landing gear’s FT, an equivalent BN is developed and analysed. The results show that richer and more accurate information have been achieved through the BN method than the FT, which demonstrates that the BN is a superior technique in both reliability assessment and fault diagnosis.

Maximum likelihood inference implies a high, not a low, ancestral haploid chromosome number in Araceae, with a critique of the bias introduced by ‘x’

PubMed Central

Cusimano, Natalie; Sousa, Aretuza; Renner, Susanne S.

2012-01-01

Background and Aims For 84 years, botanists have relied on calculating the highest common factor for series of haploid chromosome numbers to arrive at a so-called basic number, x. This was done without consistent (reproducible) reference to species relationships and frequencies of different numbers in a clade. Likelihood models that treat polyploidy, chromosome fusion and fission as events with particular probabilities now allow reconstruction of ancestral chromosome numbers in an explicit framework. We have used a modelling approach to reconstruct chromosome number change in the large monocot family Araceae and to test earlier hypotheses about basic numbers in the family. Methods Using a maximum likelihood approach and chromosome counts for 26 % of the 3300 species of Araceae and representative numbers for each of the other 13 families of Alismatales, polyploidization events and single chromosome changes were inferred on a genus-level phylogenetic tree for 113 of the 117 genera of Araceae. Key Results The previously inferred basic numbers x = 14 and x = 7 are rejected. Instead, maximum likelihood optimization revealed an ancestral haploid chromosome number of n = 16, Bayesian inference of n = 18. Chromosome fusion (loss) is the predominant inferred event, whereas polyploidization events occurred less frequently and mainly towards the tips of the tree. Conclusions The bias towards low basic numbers (x) introduced by the algebraic approach to inferring chromosome number changes, prevalent among botanists, may have contributed to an unrealistic picture of ancestral chromosome numbers in many plant clades. The availability of robust quantitative methods for reconstructing ancestral chromosome numbers on molecular phylogenetic trees (with or without branch length information), with confidence statistics, makes the calculation of x an obsolete approach, at least when applied to large clades. PMID:22210850

A Kolmogorov-Smirnov test for the molecular clock based on Bayesian ensembles of phylogenies

PubMed Central

Antoneli, Fernando; Passos, Fernando M.; Lopes, Luciano R.

2018-01-01

Divergence date estimates are central to understand evolutionary processes and depend, in the case of molecular phylogenies, on tests of molecular clocks. Here we propose two non-parametric tests of strict and relaxed molecular clocks built upon a framework that uses the empirical cumulative distribution (ECD) of branch lengths obtained from an ensemble of Bayesian trees and well known non-parametric (one-sample and two-sample) Kolmogorov-Smirnov (KS) goodness-of-fit test. In the strict clock case, the method consists in using the one-sample Kolmogorov-Smirnov (KS) test to directly test if the phylogeny is clock-like, in other words, if it follows a Poisson law. The ECD is computed from the discretized branch lengths and the parameter λ of the expected Poisson distribution is calculated as the average branch length over the ensemble of trees. To compensate for the auto-correlation in the ensemble of trees and pseudo-replication we take advantage of thinning and effective sample size, two features provided by Bayesian inference MCMC samplers. Finally, it is observed that tree topologies with very long or very short branches lead to Poisson mixtures and in this case we propose the use of the two-sample KS test with samples from two continuous branch length distributions, one obtained from an ensemble of clock-constrained trees and the other from an ensemble of unconstrained trees. Moreover, in this second form the test can also be applied to test for relaxed clock models. The use of a statistically equivalent ensemble of phylogenies to obtain the branch lengths ECD, instead of one consensus tree, yields considerable reduction of the effects of small sample size and provides a gain of power. PMID:29300759

The impact of within-herd genetic variation upon inferred transmission trees for foot-and-mouth disease virus.

PubMed

Valdazo-González, Begoña; Kim, Jan T; Soubeyrand, Samuel; Wadsworth, Jemma; Knowles, Nick J; Haydon, Daniel T; King, Donald P

2015-06-01

Full-genome sequences have been used to monitor the fine-scale dynamics of epidemics caused by RNA viruses. However, the ability of this approach to confidently reconstruct transmission trees is limited by the knowledge of the genetic diversity of viruses that exist within different epidemiological units. In order to address this question, this study investigated the variability of 45 foot-and-mouth disease virus (FMDV) genome sequences (from 33 animals) that were collected during 2007 from eight premises (10 different herds) in the United Kingdom. Bayesian and statistical parsimony analysis demonstrated that these sequences exhibited clustering which was consistent with a transmission scenario describing herd-to-herd spread of the virus. As an alternative to analysing all of the available samples in future epidemics, the impact of randomly selecting one sequence from each of these herds was used to assess cost-effective methods that might be used to infer transmission trees during FMD outbreaks. Using these approaches, 85% and 91% of the resulting topologies were either identical or differed by only one edge from a reference tree comprising all of the sequences generated within the outbreak. The sequence distances that accrued during sequential transmission events between epidemiological units was estimated to be 4.6 nucleotides, although the genetic variability between viruses recovered from chronic carrier animals was higher than between viruses from animals with acute-stage infection: an observation which poses challenges for the use of simple approaches to infer transmission trees. This study helps to develop strategies for sampling during FMD outbreaks, and provides data that will guide the development of further models to support control policies in the event of virus incursions into FMD free countries. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Estimating Bayesian Phylogenetic Information Content

PubMed Central

Lewis, Paul O.; Chen, Ming-Hui; Kuo, Lynn; Lewis, Louise A.; Fučíková, Karolina; Neupane, Suman; Wang, Yu-Bo; Shi, Daoyuan

2016-01-01

Measuring the phylogenetic information content of data has a long history in systematics. Here we explore a Bayesian approach to information content estimation. The entropy of the posterior distribution compared with the entropy of the prior distribution provides a natural way to measure information content. If the data have no information relevant to ranking tree topologies beyond the information supplied by the prior, the posterior and prior will be identical. Information in data discourages consideration of some hypotheses allowed by the prior, resulting in a posterior distribution that is more concentrated (has lower entropy) than the prior. We focus on measuring information about tree topology using marginal posterior distributions of tree topologies. We show that both the accuracy and the computational efficiency of topological information content estimation improve with use of the conditional clade distribution, which also allows topological information content to be partitioned by clade. We explore two important applications of our method: providing a compelling definition of saturation and detecting conflict among data partitions that can negatively affect analyses of concatenated data. [Bayesian; concatenation; conditional clade distribution; entropy; information; phylogenetics; saturation.] PMID:27155008

Tree Biomass Estimation of Chinese fir (Cunninghamia lanceolata) Based on Bayesian Method

PubMed Central

Zhang, Jianguo

2013-01-01

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass. PMID:24278198

Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.

PubMed

Zhang, Xiongqing; Duan, Aiguo; Zhang, Jianguo

2013-01-01

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation W = a(D2H)b was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass.

Probabilistic Approaches for Multi-Hazard Risk Assessment of Structures and Systems

NASA Astrophysics Data System (ADS)

Kwag, Shinyoung

Performance assessment of structures, systems, and components for multi-hazard scenarios has received significant attention in recent years. However, the concept of multi-hazard analysis is quite broad in nature and the focus of existing literature varies across a wide range of problems. In some cases, such studies focus on hazards that either occur simultaneously or are closely correlated with each other. For example, seismically induced flooding or seismically induced fires. In other cases, multi-hazard studies relate to hazards that are not dependent or correlated but have strong likelihood of occurrence at different times during the lifetime of a structure. The current approaches for risk assessment need enhancement to account for multi-hazard risks. It must be able to account for uncertainty propagation in a systems-level analysis, consider correlation among events or failure modes, and allow integration of newly available information from continually evolving simulation models, experimental observations, and field measurements. This dissertation presents a detailed study that proposes enhancements by incorporating Bayesian networks and Bayesian updating within a performance-based probabilistic framework. The performance-based framework allows propagation of risk as well as uncertainties in the risk estimates within a systems analysis. Unlike conventional risk assessment techniques such as a fault-tree analysis, a Bayesian network can account for statistical dependencies and correlations among events/hazards. The proposed approach is extended to develop a risk-informed framework for quantitative validation and verification of high fidelity system-level simulation tools. Validation of such simulations can be quite formidable within the context of a multi-hazard risk assessment in nuclear power plants. The efficiency of this approach lies in identification of critical events, components, and systems that contribute to the overall risk. Validation of any event or component on the critical path is relatively more important in a risk-informed environment. Significance of multi-hazard risk is also illustrated for uncorrelated hazards of earthquakes and high winds which may result in competing design objectives. It is also illustrated that the number of computationally intensive nonlinear simulations needed in performance-based risk assessment for external hazards can be significantly reduced by using the power of Bayesian updating in conjunction with the concept of equivalent limit-state.

Adaptation of Chain Event Graphs for use with Case-Control Studies in Epidemiology.

PubMed

Keeble, Claire; Thwaites, Peter Adam; Barber, Stuart; Law, Graham Richard; Baxter, Paul David

2017-09-26

Case-control studies are used in epidemiology to try to uncover the causes of diseases, but are a retrospective study design known to suffer from non-participation and recall bias, which may explain their decreased popularity in recent years. Traditional analyses report usually only the odds ratio for given exposures and the binary disease status. Chain event graphs are a graphical representation of a statistical model derived from event trees which have been developed in artificial intelligence and statistics, and only recently introduced to the epidemiology literature. They are a modern Bayesian technique which enable prior knowledge to be incorporated into the data analysis using the agglomerative hierarchical clustering algorithm, used to form a suitable chain event graph. Additionally, they can account for missing data and be used to explore missingness mechanisms. Here we adapt the chain event graph framework to suit scenarios often encountered in case-control studies, to strengthen this study design which is time and financially efficient. We demonstrate eight adaptations to the graphs, which consist of two suitable for full case-control study analysis, four which can be used in interim analyses to explore biases, and two which aim to improve the ease and accuracy of analyses. The adaptations are illustrated with complete, reproducible, fully-interpreted examples, including the event tree and chain event graph. Chain event graphs are used here for the first time to summarise non-participation, data collection techniques, data reliability, and disease severity in case-control studies. We demonstrate how these features of a case-control study can be incorporated into the analysis to provide further insight, which can help to identify potential biases and lead to more accurate study results.

Evaluating Great Lakes bald eagle nesting habitat with Bayesian inference

Treesearch

Teryl G. Grubb; William W. Bowerman; Allen J. Bath; John P. Giesy; D. V. Chip Weseloh

2003-01-01

Bayesian inference facilitated structured interpretation of a nonreplicated, experience-based survey of potential nesting habitat for bald eagles (Haliaeetus leucocephalus) along the five Great Lakes shorelines. We developed a pattern recognition (PATREC) model of our aerial search image with six habitat attributes: (a) tree cover, (b) proximity and...

HIV Migration Between Blood and Cerebrospinal Fluid or Semen Over Time

PubMed Central

Chaillon, Antoine; Gianella, Sara; Wertheim, Joel O.; Richman, Douglas D.; Mehta, Sanjay R.; Smith, David M.

2014-01-01

Previous studies reported associations between neuropathogenesis and human immunodeficiency virus (HIV) compartmentalization in cerebrospinal fluid (CSF) and between sexual transmission and human immunodeficiency virus type 1 (HIV) compartmentalization in semen. It remains unclear, however, how compartmentalization dynamics change over time. To address this, we used statistical methods and Bayesian phylogenetic approaches to reconstruct temporal dynamics of HIV migration between blood and CSF and between blood and the male genital tract. We investigated 11 HIV-infected individuals with paired semen and blood samples and 4 individuals with paired CSF and blood samples. Aligned partial HIV env sequences were analyzed by (1) phylogenetic reconstruction, using a Bayesian Markov-chain Monte Carlo approach; (2) evaluation of viral compartmentalization, using tree-based and distance-based methods; and (3) analysis of migration events, using a discrete Bayesian asymmetric phylogeographic approach of diffusion with Markov jump counts estimation. Finally, we evaluated potential correlates of viral gene flow across anatomical compartments. We observed bidirectional replenishment of viral compartments and asynchronous peaks of viral migration from and to blood over time, suggesting that disruption of viral compartment is transient and directionally selected. These findings imply that viral subpopulations in anatomical sites are an active part of the whole viral population and that compartmental reservoirs could have implications in future eradication studies. PMID:24302756

Fundamentals and Recent Developments in Approximate Bayesian Computation

PubMed Central

Lintusaari, Jarno; Gutmann, Michael U.; Dutta, Ritabrata; Kaski, Samuel; Corander, Jukka

2017-01-01

Abstract Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by only requiring that sampling from a model is possible. We explain here the fundamentals of ABC, review the classical algorithms, and highlight recent developments. [ABC; approximate Bayesian computation; Bayesian inference; likelihood-free inference; phylogenetics; simulator-based models; stochastic simulation models; tree-based models.] PMID:28175922

A phylogenetic study of Laeliinae (Orchidaceae) based on combined nuclear and plastid DNA sequences

PubMed Central

van den Berg, Cássio; Higgins, Wesley E.; Dressler, Robert L.; Whitten, W. Mark; Soto-Arenas, Miguel A.; Chase, Mark W.

2009-01-01

Background and Aims Laeliinae are a neotropical orchid subtribe with approx. 1500 species in 50 genera. In this study, an attempt is made to assess generic alliances based on molecular phylogenetic analysis of DNA sequence data. Methods Six DNA datasets were gathered: plastid trnL intron, trnL-F spacer, matK gene and trnK introns upstream and dowstream from matK and nuclear ITS rDNA. Data were analysed with maximum parsimony (MP) and Bayesian analysis with mixed models (BA). Key Results Although relationships between Laeliinae and outgroups are well supported, within the subtribe sequence variation is low considering the broad taxonomic range covered. Localized incongruence between the ITS and plastid trees was found. A combined tree followed the ITS trees more closely, but the levels of support obtained with MP were low. The Bayesian analysis recovered more well-supported nodes. The trees from combined MP and BA allowed eight generic alliances to be recognized within Laeliinae, all of which show trends in morphological characters but lack unambiguous synapomorphies. Conclusions By using combined plastid and nuclear DNA data in conjunction with mixed-models Bayesian inference, it is possible to delimit smaller groups within Laeliinae and discuss general patterns of pollination and hybridization compatibility. Furthermore, these small groups can now be used for further detailed studies to explain morphological evolution and diversification patterns within the subtribe. PMID:19423551

Species trees from consensus single nucleotide polymorphism (SNP) data: Testing phylogenetic approaches with simulated and empirical data.

PubMed

Schmidt-Lebuhn, Alexander N; Aitken, Nicola C; Chuah, Aaron

2017-11-01

Datasets of hundreds or thousands of SNPs (Single Nucleotide Polymorphisms) from multiple individuals per species are increasingly used to study population structure, species delimitation and shallow phylogenetics. The principal software tool to infer species or population trees from SNP data is currently the BEAST template SNAPP which uses a Bayesian coalescent analysis. However, it is computationally extremely demanding and tolerates only small amounts of missing data. We used simulated and empirical SNPs from plants (Australian Craspedia, Asteraceae, and Pelargonium, Geraniaceae) to compare species trees produced (1) by SNAPP, (2) using SVD quartets, and (3) using Bayesian and parsimony analysis with several different approaches to summarising data from multiple samples into one set of traits per species. Our aims were to explore the impact of tree topology and missing data on the results, and to test which data summarising and analyses approaches would best approximate the results obtained from SNAPP for empirical data. SVD quartets retrieved the correct topology from simulated data, as did SNAPP except in the case of a very unbalanced phylogeny. Both methods failed to retrieve the correct topology when large amounts of data were missing. Bayesian analysis of species level summary data scoring the two alleles of each SNP as independent characters and parsimony analysis of data scoring each SNP as one character produced trees with branch length distributions closest to the true trees on which SNPs were simulated. For empirical data, Bayesian inference and Dollo parsimony analysis of data scored allele-wise produced phylogenies most congruent with the results of SNAPP. In the case of study groups divergent enough for missing data to be phylogenetically informative (because of additional mutations preventing amplification of genomic fragments or bioinformatic establishment of homology), scoring of SNP data as a presence/absence matrix irrespective of allele content might be an additional option. As this depends on sampling across species being reasonably even and a random distribution of non-informative instances of missing data, however, further exploration of this approach is needed. Properly chosen data summary approaches to inferring species trees from SNP data may represent a potential alternative to currently available individual-level coalescent analyses especially for quick data exploration and when dealing with computationally demanding or patchy datasets. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Inferring Phylogenetic Networks Using PhyloNet.

PubMed

Wen, Dingqiao; Yu, Yun; Zhu, Jiafan; Nakhleh, Luay

2018-07-01

PhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or biallelic markers) is implemented. Maximum parsimony is based on an extension of the "minimizing deep coalescences" criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudolikelihood measure. PhyloNet summarizes the results of the various analyzes and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software.

Bayesian analysis of rare events

NASA Astrophysics Data System (ADS)

Straub, Daniel; Papaioannou, Iason; Betz, Wolfgang

2016-06-01

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.

Is the extremely rare Iberian endemic plant species Castrilanthemum debeauxii (Compositae, Anthemideae) a 'living fossil'? Evidence from a multi-locus species tree reconstruction.

PubMed

Tomasello, Salvatore; Álvarez, Inés; Vargas, Pablo; Oberprieler, Christoph

2015-01-01

The present study provides results of multi-species coalescent species tree analyses of DNA sequences sampled from multiple nuclear and plastid regions to infer the phylogenetic relationships among the members of the subtribe Leucanthemopsidinae (Compositae, Anthemideae), to which besides the annual Castrilanthemum debeauxii (Degen, Hervier & É.Rev.) Vogt & Oberp., one of the rarest flowering plant species of the Iberian Peninsula, two other unispecific genera (Hymenostemma, Prolongoa), and the polyploidy complex of the genus Leucanthemopsis belong. Based on sequence information from two single- to low-copy nuclear regions (C16, D35, characterised by Chapman et al. (2007)), the multi-copy region of the nrDNA internal transcribed spacer regions ITS1 and ITS2, and two intergenic spacer regions of the cpDNA gene trees were reconstructed using Bayesian inference methods. For the reconstruction of a multi-locus species tree we applied three different methods: (a) analysis of concatenated sequences using Bayesian inference (MrBayes), (b) a tree reconciliation approach by minimizing the number of deep coalescences (PhyloNet), and (c) a coalescent-based species-tree method in a Bayesian framework ((∗)BEAST). All three species tree reconstruction methods unequivocally support the close relationship of the subtribe with the hitherto unclassified genus Phalacrocarpum, the sister-group relationship of Castrilanthemum with the three remaining genera of the subtribe, and the further sister-group relationship of the clade of Hymenostemma+Prolongoa with a monophyletic genus Leucanthemopsis. Dating of the (∗)BEAST phylogeny supports the long-lasting (Early Miocene, 15-22Ma) taxonomical independence and the switch from the plesiomorphic perennial to the apomorphic annual life-form assumed for the Castrilanthemum lineage that may have occurred not earlier than in the Pliocene (3Ma) when the establishment of a Mediterranean climate with summer droughts triggered evolution towards annuality. Copyright © 2014 Elsevier Inc. All rights reserved.

Extensions and applications of ensemble-of-trees methods in machine learning

NASA Astrophysics Data System (ADS)

Bleich, Justin

Ensemble-of-trees algorithms have emerged to the forefront of machine learning due to their ability to generate high forecasting accuracy for a wide array of regression and classification problems. Classic ensemble methodologies such as random forests (RF) and stochastic gradient boosting (SGB) rely on algorithmic procedures to generate fits to data. In contrast, more recent ensemble techniques such as Bayesian Additive Regression Trees (BART) and Dynamic Trees (DT) focus on an underlying Bayesian probability model to generate the fits. These new probability model-based approaches show much promise versus their algorithmic counterparts, but also offer substantial room for improvement. The first part of this thesis focuses on methodological advances for ensemble-of-trees techniques with an emphasis on the more recent Bayesian approaches. In particular, we focus on extensions of BART in four distinct ways. First, we develop a more robust implementation of BART for both research and application. We then develop a principled approach to variable selection for BART as well as the ability to naturally incorporate prior information on important covariates into the algorithm. Next, we propose a method for handling missing data that relies on the recursive structure of decision trees and does not require imputation. Last, we relax the assumption of homoskedasticity in the BART model to allow for parametric modeling of heteroskedasticity. The second part of this thesis returns to the classic algorithmic approaches in the context of classification problems with asymmetric costs of forecasting errors. First we consider the performance of RF and SGB more broadly and demonstrate its superiority to logistic regression for applications in criminology with asymmetric costs. Next, we use RF to forecast unplanned hospital readmissions upon patient discharge with asymmetric costs taken into account. Finally, we explore the construction of stable decision trees for forecasts of violence during probation hearings in court systems.

Genetic Structure and Diversity of the Endangered Fir Tree of Lebanon (Abies cilicica Carr.): Implications for Conservation

PubMed Central

Awad, Lara; Fady, Bruno; Khater, Carla; Roig, Anne; Cheddadi, Rachid

2014-01-01

The threatened conifer Abies cilicica currently persists in Lebanon in geographically isolated forest patches. The impact of demographic and evolutionary processes on population genetic diversity and structure were assessed using 10 nuclear microsatellite loci. All remnant 15 local populations revealed a low genetic variation but a high recent effective population size. FST-based measures of population genetic differentiation revealed a low spatial genetic structure, but Bayesian analysis of population structure identified a significant Northeast-Southwest population structure. Populations showed significant but weak isolation-by-distance, indicating non-equilibrium conditions between dispersal and genetic drift. Bayesian assignment tests detected an asymmetric Northeast-Southwest migration involving some long-distance dispersal events. We suggest that the persistence and Northeast-Southwest geographic structure of Abies cilicica in Lebanon is the result of at least two demographic processes during its recent evolutionary history: (1) recent migration to currently marginal populations and (2) local persistence through altitudinal shifts along a mountainous topography. These results might help us better understand the mechanisms involved in the species response to expected climate change. PMID:24587219

Tree Species Traits but Not Diversity Mitigate Stem Breakage in a Subtropical Forest following a Rare and Extreme Ice Storm

PubMed Central

Nadrowski, Karin; Pietsch, Katherina; Baruffol, Martin; Both, Sabine; Gutknecht, Jessica; Bruelheide, Helge; Heklau, Heike; Kahl, Anja; Kahl, Tiemo; Niklaus, Pascal; Kröber, Wenzel; Liu, Xiaojuan; Mi, Xiangcheng; Michalski, Stefan; von Oheimb, Goddert; Purschke, Oliver; Schmid, Bernhard; Fang, Teng; Welk, Erik; Wirth, Christian

2014-01-01

Future climates are likely to include extreme events, which in turn have great impacts on ecological systems. In this study, we investigated possible effects that could mitigate stem breakage caused by a rare and extreme ice storm in a Chinese subtropical forest across a gradient of forest diversity. We used Bayesian modeling to correct stem breakage for tree size and variance components analysis to quantify the influence of taxon, leaf and wood functional traits, and stand level properties on the probability of stem breakage. We show that the taxon explained four times more variance in individual stem breakage than did stand level properties; trees with higher specific leaf area (SLA) were less susceptible to breakage. However, a large part of the variation at the taxon scale remained unexplained, implying that unmeasured or undefined traits could be used to predict damage caused by ice storms. When aggregated at the plot level, functional diversity and wood density increased after the ice storm. We suggest that for the adaption of forest management to climate change, much can still be learned from looking at functional traits at the taxon level. PMID:24879434

Bayesian analysis of rare events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straub, Daniel, E-mail: straub@tum.de; Papaioannou, Iason; Betz, Wolfgang

2016-06-01

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into themore » probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.« less

Introduction in IND and recursive partitioning

NASA Technical Reports Server (NTRS)

Buntine, Wray; Caruana, Rich

1991-01-01

This manual describes the IND package for learning tree classifiers from data. The package is an integrated C and C shell re-implementation of tree learning routines such as CART, C4, and various MDL and Bayesian variations. The package includes routines for experiment control, interactive operation, and analysis of tree building. The manual introduces the system and its many options, gives a basic review of tree learning, contains a guide to the literature and a glossary, and lists the manual pages for the routines and instructions on installation.

Bayesian Morphological Clock Methods Resurrect Placoderm Monophyly and Reveal Rapid Early Evolution in Jawed Vertebrates.

PubMed

King, Benedict; Qiao, Tuo; Lee, Michael S Y; Zhu, Min; Long, John A

2017-07-01

The phylogeny of early gnathostomes provides an important framework for understanding one of the most significant evolutionary events, the origin and diversification of jawed vertebrates. A series of recent cladistic analyses have suggested that the placoderms, an extinct group of armoured fish, form a paraphyletic group basal to all other jawed vertebrates. We revised and expanded this morphological data set, most notably by sampling autapomorphies in a similar way to parsimony-informative traits, thus ensuring this data (unlike most existing morphological data sets) satisfied an important assumption of Bayesian tip-dated morphological clock approaches. We also found problems with characters supporting placoderm paraphyly, including character correlation and incorrect codings. Analysis of this data set reveals that paraphyly and monophyly of core placoderms (excluding maxillate forms) are essentially equally parsimonious. The two alternative topologies have different root positions for the jawed vertebrates but are otherwise similar. However, analysis using tip-dated clock methods reveals strong support for placoderm monophyly, due to this analysis favoring trees with more balanced rates of evolution. Furthermore, enforcing placoderm paraphyly results in higher levels and unusual patterns of rate heterogeneity among branches, similar to that generated from simulated trees reconstructed with incorrect root positions. These simulations also show that Bayesian tip-dated clock methods outperform parsimony when the outgroup is largely uninformative (e.g., due to inapplicable characters), as might be the case here. The analysis also reveals that gnathostomes underwent a rapid burst of evolution during the Silurian period which declined during the Early Devonian. This rapid evolution during a period with few articulated fossils might partly explain the difficulty in ascertaining the root position of jawed vertebrates. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Comparing flood loss models of different complexity

NASA Astrophysics Data System (ADS)

Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Riggelsen, Carsten; Scherbaum, Frank; Merz, Bruno

2013-04-01

Any deliberation on flood risk requires the consideration of potential flood losses. In particular, reliable flood loss models are needed to evaluate cost-effectiveness of mitigation measures, to assess vulnerability, for comparative risk analysis and financial appraisal during and after floods. In recent years, considerable improvements have been made both concerning the data basis and the methodological approaches used for the development of flood loss models. Despite of that, flood loss models remain an important source of uncertainty. Likewise the temporal and spatial transferability of flood loss models is still limited. This contribution investigates the predictive capability of different flood loss models in a split sample cross regional validation approach. For this purpose, flood loss models of different complexity, i.e. based on different numbers of explaining variables, are learned from a set of damage records that was obtained from a survey after the Elbe flood in 2002. The validation of model predictions is carried out for different flood events in the Elbe and Danube river basins in 2002, 2005 and 2006 for which damage records are available from surveys after the flood events. The models investigated are a stage-damage model, the rule based model FLEMOps+r as well as novel model approaches which are derived using data mining techniques of regression trees and Bayesian networks. The Bayesian network approach to flood loss modelling provides attractive additional information concerning the probability distribution of both model predictions and explaining variables.

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

This CD contains files that support the talk (see CASI ID 20100021404). There are 24 models that relate to the ADAPT system and 1 Excel worksheet. In the paper an investigation into the use of Bayesian networks to construct large-scale diagnostic systems is described. The high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems are described in the talk. The data in the CD are the models of the 24 different power systems.

Investigating Processes of Neotropical Rain Forest Tree Diversification By Examining the Evolution and Historical Biogeography of the Protieae (BURSERACEAE)

NASA Astrophysics Data System (ADS)

Fine, P.; Zapata, F.; Daly, D.

2014-12-01

Andean uplift and the collision of North and South America are thought to have major implications for the diversification of the Neotropical biota. However, few studies have investigated how these geological events may have influenced diversification. We present a multilocus phylogeny of 102 Protieae taxa (73% of published species), sampled pantropically, to test hypotheses about the relative importance of dispersal, vicariance, habitat specialization, and biotic factors in the diversification of this ecologically dominant tribe of Neotropical trees. Bayesian fossil-calibrated analyses date the Protieae stem at 55 Mya. Biogeographic analyses reconstruct an initial late Oligocene/early Miocene radiation in Amazonia for Neotropical Protieae, with several subsequent late Miocene dispersal events to Central America, the Caribbean, Brazil's Atlantic Forest, and the Chocó. Regional phylogenetic structure results indicate frequent dispersal among regions throughout the Miocene and many instances of more recent regional in situ speciation. Habitat specialization to white sand or flooded soils was common, especially in Amazonia. There was one significant increase in diversification rate coincident with colonization of the Neotropics, followed by a gradual decrease consistent with models of diversity-dependent cladogenesis. Dispersal, biotic interactions, and habitat specialization are thus hypothesized to be the most important processes underlying the diversification of the Protieae.

Bayesian analysis of caustic-crossing microlensing events

NASA Astrophysics Data System (ADS)

Cassan, A.; Horne, K.; Kains, N.; Tsapras, Y.; Browne, P.

2010-06-01

Aims: Caustic-crossing binary-lens microlensing events are important anomalous events because they are capable of detecting an extrasolar planet companion orbiting the lens star. Fast and robust modelling methods are thus of prime interest in helping to decide whether a planet is detected by an event. Cassan introduced a new set of parameters to model binary-lens events, which are closely related to properties of the light curve. In this work, we explain how Bayesian priors can be added to this framework, and investigate on interesting options. Methods: We develop a mathematical formulation that allows us to compute analytically the priors on the new parameters, given some previous knowledge about other physical quantities. We explicitly compute the priors for a number of interesting cases, and show how this can be implemented in a fully Bayesian, Markov chain Monte Carlo algorithm. Results: Using Bayesian priors can accelerate microlens fitting codes by reducing the time spent considering physically implausible models, and helps us to discriminate between alternative models based on the physical plausibility of their parameters.

Prediction in Health Domain Using Bayesian Networks Optimization Based on Induction Learning Techniques

NASA Astrophysics Data System (ADS)

Felgaer, Pablo; Britos, Paola; García-Martínez, Ramón

A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and flexible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain.

Confronting a Process-based Model of Temperate Tree Transpiration with Data from Forests in Central Panama Exposed to Drought

NASA Astrophysics Data System (ADS)

Ewers, B. E.; Bretfeld, M.; Millar, D.; Hall, J. S.; Beverly, D.; Hall, J. S.; Ogden, F. L.; Mackay, D. S.

2016-12-01

Process-based models of tree impacts on the hydrologic cycle must include not only plant hydraulic limitations but also photosynthetic controls because plants lose water to gain carbon. The Terrestrial Regional Ecosystem Exchange Simulator (TREES) is one such model. TREES includes a Bayesian model-data fusion approach that provides rigorous tests of patterns in tree transpiration data against biophysical processes in the model. TREES has been extensively tested against many temperate tree data sets including those experiencing severe and lethal drought. We test TREES against data from sap flow-scaled transpiration in 76 tropical trees (representing 42 different species) in secondary forests of three different ages (8, 25, and 80+ years) located in the Panama Canal Watershed. These data were collected during the third driest El Niño-Southern Oscillation (ENSO) event on record in Panama during 2015/2016. Tree transpiration response to vapor pressure deficit and solar radiation was the same in the two older forests, but showed an additional response to limited soil moisture in the youngest forest. Volumetric water content at 30 and 50 cm depths was 8% lower in the 8 year old forest than in the 80+ year old forest. TREES could not simulate this difference in soil moisture without increasing simulated root area. TREES simulations were improved by including light response curves of leaf photosynthesis, root vulnerability to cavitation and canopy position impacts on light. TREES was able to simulate the anisohydric (loose stomatal regulation of leaf water potential) and isohydric (tight stomatal regulation) of the 73 trees species a priori indicating that species level information is not required. Analyses of posterior probability distributions indicates TREES model predictions of individual tree transpiration would likely be improved with more detailed root and soil moisture in all forest ages data with the most improvement likely in the 8 year old forest. Our results suggest that a biophysical tree transpiration model developed in temperate forests can be applied to the tropics and could be used to improve predictions of evapotranspiration from changing land cover in tropical hydrology models.

Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures

PubMed Central

Moore, Brian R.; Höhna, Sebastian; May, Michael R.; Rannala, Bruce; Huelsenbeck, John P.

2016-01-01

Bayesian analysis of macroevolutionary mixtures (BAMM) has recently taken the study of lineage diversification by storm. BAMM estimates the diversification-rate parameters (speciation and extinction) for every branch of a study phylogeny and infers the number and location of diversification-rate shifts across branches of a tree. Our evaluation of BAMM reveals two major theoretical errors: (i) the likelihood function (which estimates the model parameters from the data) is incorrect, and (ii) the compound Poisson process prior model (which describes the prior distribution of diversification-rate shifts across branches) is incoherent. Using simulation, we demonstrate that these theoretical issues cause statistical pathologies; posterior estimates of the number of diversification-rate shifts are strongly influenced by the assumed prior, and estimates of diversification-rate parameters are unreliable. Moreover, the inability to correctly compute the likelihood or to correctly specify the prior for rate-variable trees precludes the use of Bayesian approaches for testing hypotheses regarding the number and location of diversification-rate shifts using BAMM. PMID:27512038

Visualizing the Bayesian 2-test case: The effect of tree diagrams on medical decision making.

PubMed

Binder, Karin; Krauss, Stefan; Bruckmaier, Georg; Marienhagen, Jörg

2018-01-01

In medicine, diagnoses based on medical test results are probabilistic by nature. Unfortunately, cognitive illusions regarding the statistical meaning of test results are well documented among patients, medical students, and even physicians. There are two effective strategies that can foster insight into what is known as Bayesian reasoning situations: (1) translating the statistical information on the prevalence of a disease and the sensitivity and the false-alarm rate of a specific test for that disease from probabilities into natural frequencies, and (2) illustrating the statistical information with tree diagrams, for instance, or with other pictorial representation. So far, such strategies have only been empirically tested in combination for "1-test cases", where one binary hypothesis ("disease" vs. "no disease") has to be diagnosed based on one binary test result ("positive" vs. "negative"). However, in reality, often more than one medical test is conducted to derive a diagnosis. In two studies, we examined a total of 388 medical students from the University of Regensburg (Germany) with medical "2-test scenarios". Each student had to work on two problems: diagnosing breast cancer with mammography and sonography test results, and diagnosing HIV infection with the ELISA and Western Blot tests. In Study 1 (N = 190 participants), we systematically varied the presentation of statistical information ("only textual information" vs. "only tree diagram" vs. "text and tree diagram in combination"), whereas in Study 2 (N = 198 participants), we varied the kinds of tree diagrams ("complete tree" vs. "highlighted tree" vs. "pruned tree"). All versions were implemented in probability format (including probability trees) and in natural frequency format (including frequency trees). We found that natural frequency trees, especially when the question-related branches were highlighted, improved performance, but that none of the corresponding probabilistic visualizations did.

Geologic events coupled with Pleistocene climatic oscillations drove genetic variation of Omei treefrog (Rhacophorus omeimontis) in southern China.

PubMed

Li, Jun; Zhao, Mian; Wei, Shichao; Luo, Zhenhua; Wu, Hua

2015-12-21

Pleistocene climatic oscillations and historical geological events may both influence current patterns of genetic variation, and the species in southern China that faced unique climatic and topographical events have complex evolutionary histories. However, the relative contributions of climatic oscillations and geographical events to the genetic variation of these species remain undetermined. To investigate patterns of genetic variation and to test the hypotheses about the factors that shaped the distribution of this genetic variation in species of southern China, mitochondrial genes (cytochrome b and NADH dehydrogenase subunit 2) and nine microsatellite loci of the Omei tree frog (Rhacophorus omeimontis) were amplified in this study. The genetic diversity in the populations of R. omeimontis was high. The phylogenetic trees reconstructed from the mitochondrial DNA (mtDNA) haplotypes and the Bayesian genetic clustering analysis based on microsatellite data both revealed that all populations were divided into three lineages (SC, HG and YN). The two most recent splitting events among the lineages coincided with recent geological events (including the intense uplift of the Qinghai-Tibet Plateau, QTP and the subsequent movements of the Yun-Gui Plateau, YGP) and the Pleistocene glaciations. Significant expansion signals were not detected in mismatch analyses or neutrality tests. And the effective population size of each lineage was stable during the Pleistocene. Based on the results of this study, complex geological events (the recent dramatic uplift of the QTP and the subsequent movements of the YGP) and the Pleistocene glaciations were apparent drivers of the rapid divergence of the R. omeimontis lineages. Each diverged lineages survived in situ with limited gene exchanges, and the stable demographics of lineages indicate that the Pleistocene climatic oscillations were inconsequential for this species. The analysis of genetic variation in populations of R. omeimontis contributes to the understanding of the effects of changes in climate and of geographical events on the dynamic development of contemporary patterns of genetic variation in the species of southern China.

Bayesian Networks for Modeling Dredging Decisions

DTIC Science & Technology

2011-10-01

change scenarios. Arctic Expert elicitation Netica Bacon et al . 2002 Identify factors that might lead to a change in land use from farming to...tree) algorithms developed by Lauritzen and Spiegelhalter (1988) and Jensen et al . (1990). Statistical inference is simply the process of...causality when constructing a Bayesian network (Kjaerulff and Madsen 2008, Darwiche 2009, Marcot et al . 2006). A knowledge representation approach is the

A Mixtures-of-Trees Framework for Multi-Label Classification

PubMed Central

Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

2015-01-01

We propose a new probabilistic approach for multi-label classification that aims to represent the class posterior distribution P(Y|X). Our approach uses a mixture of tree-structured Bayesian networks, which can leverage the computational advantages of conditional tree-structured models and the abilities of mixtures to compensate for tree-structured restrictions. We develop algorithms for learning the model from data and for performing multi-label predictions using the learned model. Experiments on multiple datasets demonstrate that our approach outperforms several state-of-the-art multi-label classification methods. PMID:25927011

Introduction to IND and recursive partitioning, version 1.0

NASA Technical Reports Server (NTRS)

Buntine, Wray; Caruana, Rich

1991-01-01

This manual describes the IND package for learning tree classifiers from data. The package is an integrated C and C shell re-implementation of tree learning routines such as CART, C4, and various MDL and Bayesian variations. The package includes routines for experiment control, interactive operation, and analysis of tree building. The manual introduces the system and its many options, gives a basic review of tree learning, contains a guide to the literature and a glossary, lists the manual pages for the routines, and instructions on installation.

Global biogeography of scaly tree ferns (Cyatheaceae): evidence for Gondwanan vicariance and limited transoceanic dispersal

PubMed Central

Korall, Petra; Pryer, Kathleen M

2014-01-01

Aim Scaly tree ferns, Cyatheaceae, are a well-supported group of mostly tree-forming ferns found throughout the tropics, the subtropics and the south-temperate zone. Fossil evidence shows that the lineage originated in the Late Jurassic period. We reconstructed large-scale historical biogeographical patterns of Cyatheaceae and tested the hypothesis that some of the observed distribution patterns are in fact compatible, in time and space, with a vicariance scenario related to the break-up of Gondwana. Location Tropics, subtropics and south-temperate areas of the world. Methods The historical biogeography of Cyatheaceae was analysed in a maximum likelihood framework using Lagrange. The 78 ingroup taxa are representative of the geographical distribution of the entire family. The phylogenies that served as a basis for the analyses were obtained by Bayesian inference analyses of mainly previously published DNA sequence data using MrBayes. Lineage divergence dates were estimated in a Bayesian Markov chain Monte Carlo framework using beast. Results Cyatheaceae originated in the Late Jurassic in either South America or Australasia. Following a range expansion, the ancestral distribution of the marginate-scaled clade included both these areas, whereas Sphaeropteris is reconstructed as having its origin only in Australasia. Within the marginate-scaled clade, reconstructions of early divergences are hampered by the unresolved relationships among the Alsophila, Cyathea and Gymnosphaera lineages. Nevertheless, it is clear that the occurrence of the Cyathea and Sphaeropteris lineages in South America may be related to vicariance, whereas transoceanic dispersal needs to be inferred for the range shifts seen in Alsophila and Gymnosphaera. Main conclusions The evolutionary history of Cyatheaceae involves both Gondwanan vicariance scenarios as well as long-distance dispersal events. The number of transoceanic dispersals reconstructed for the family is rather few when compared with other fern lineages. We suggest that a causal relationship between reproductive mode (outcrossing) and dispersal limitations is the most plausible explanation for the pattern observed. PMID:25435648

Global biogeography of scaly tree ferns (Cyatheaceae): evidence for Gondwanan vicariance and limited transoceanic dispersal.

PubMed

Korall, Petra; Pryer, Kathleen M

2014-02-01

Scaly tree ferns, Cyatheaceae, are a well-supported group of mostly tree-forming ferns found throughout the tropics, the subtropics and the south-temperate zone. Fossil evidence shows that the lineage originated in the Late Jurassic period. We reconstructed large-scale historical biogeographical patterns of Cyatheaceae and tested the hypothesis that some of the observed distribution patterns are in fact compatible, in time and space, with a vicariance scenario related to the break-up of Gondwana. Tropics, subtropics and south-temperate areas of the world. The historical biogeography of Cyatheaceae was analysed in a maximum likelihood framework using Lagrange. The 78 ingroup taxa are representative of the geographical distribution of the entire family. The phylogenies that served as a basis for the analyses were obtained by Bayesian inference analyses of mainly previously published DNA sequence data using MrBayes. Lineage divergence dates were estimated in a Bayesian Markov chain Monte Carlo framework using beast. Cyatheaceae originated in the Late Jurassic in either South America or Australasia. Following a range expansion, the ancestral distribution of the marginate-scaled clade included both these areas, whereas Sphaeropteris is reconstructed as having its origin only in Australasia. Within the marginate-scaled clade, reconstructions of early divergences are hampered by the unresolved relationships among the Alsophila , Cyathea and Gymnosphaera lineages. Nevertheless, it is clear that the occurrence of the Cyathea and Sphaeropteris lineages in South America may be related to vicariance, whereas transoceanic dispersal needs to be inferred for the range shifts seen in Alsophila and Gymnosphaera . The evolutionary history of Cyatheaceae involves both Gondwanan vicariance scenarios as well as long-distance dispersal events. The number of transoceanic dispersals reconstructed for the family is rather few when compared with other fern lineages. We suggest that a causal relationship between reproductive mode (outcrossing) and dispersal limitations is the most plausible explanation for the pattern observed.

PyBetVH: A Python tool for probabilistic volcanic hazard assessment and for generation of Bayesian hazard curves and maps

NASA Astrophysics Data System (ADS)

Tonini, Roberto; Sandri, Laura; Anne Thompson, Mary

2015-06-01

PyBetVH is a completely new, free, open-source and cross-platform software implementation of the Bayesian Event Tree for Volcanic Hazard (BET_VH), a tool for estimating the probability of any magmatic hazardous phenomenon occurring in a selected time frame, accounting for all the uncertainties. New capabilities of this implementation include the ability to calculate hazard curves which describe the distribution of the exceedance probability as a function of intensity (e.g., tephra load) on a grid of points covering the target area. The computed hazard curves are (i) absolute (accounting for the probability of eruption in a given time frame, and for all the possible vent locations and eruptive sizes) and (ii) Bayesian (computed at different percentiles, in order to quantify the epistemic uncertainty). Such curves allow representation of the full information contained in the probabilistic volcanic hazard assessment (PVHA) and are well suited to become a main input to quantitative risk analyses. PyBetVH allows for interactive visualization of both the computed hazard curves, and the corresponding Bayesian hazard/probability maps. PyBetVH is designed to minimize the efforts of end users, making PVHA results accessible to people who may be less experienced in probabilistic methodologies, e.g. decision makers. The broad compatibility of Python language has also allowed PyBetVH to be installed on the VHub cyber-infrastructure, where it can be run online or downloaded at no cost. PyBetVH can be used to assess any type of magmatic hazard from any volcano. Here we illustrate how to perform a PVHA through PyBetVH using the example of analyzing tephra fallout from the Okataina Volcanic Centre (OVC), New Zealand, and highlight the range of outputs that the tool can generate.

Bayesian Models Leveraging Bioactivity and Cytotoxicity Information for Drug Discovery

PubMed Central

Ekins, Sean; Reynolds, Robert C.; Kim, Hiyun; Koo, Mi-Sun; Ekonomidis, Marilyn; Talaue, Meliza; Paget, Steve D.; Woolhiser, Lisa K.; Lenaerts, Anne J.; Bunin, Barry A.; Connell, Nancy; Freundlich, Joel S.

2013-01-01

SUMMARY Identification of unique leads represents a significant challenge in drug discovery. This hurdle is magnified in neglected diseases such as tuberculosis. We have leveraged public high-throughput screening (HTS) data, to experimentally validate virtual screening approach employing Bayesian models built with bioactivity information (single-event model) as well as bioactivity and cytotoxicity information (dual-event model). We virtually screen a commercial library and experimentally confirm actives with hit rates exceeding typical HTS results by 1-2 orders of magnitude. The first dual-event Bayesian model identified compounds with antitubercular whole-cell activity and low mammalian cell cytotoxicity from a published set of antimalarials. The most potent hit exhibits the in vitro activity and in vitro/in vivo safety profile of a drug lead. These Bayesian models offer significant economies in time and cost to drug discovery. PMID:23521795

The phylogenetic relationships of known mosquito (Diptera: Culicidae) mitogenomes.

PubMed

Chu, Hongliang; Li, Chunxiao; Guo, Xiaoxia; Zhang, Hengduan; Luo, Peng; Wu, Zhonghua; Wang, Gang; Zhao, Tongyan

2018-01-01

The known mosquito mitogenomes, containing a total of 34 species, which belong to five genera, were collected from GenBank, and the practicality and effectiveness of the variation in the complete mitochondrial DNA genome and portions of mitochondrial COI gene were assessed to reconstruct the phylogeny of mosquitoes. Phylogenetic trees were reconstructed on the basis of parsimony, maximum likelihood, and Bayesian (BI) methods. It is concluded that: (1) Both mitogenomes and COI gene support the monophly of following taxa: Subgenus Nyssorhynchus, Subgenus Cellia, Anopheles albitarsis complex, Anopheles gambiae complex, and Anopheles punctulatus group; (2) Genus Aedes is not monophyletic relative to Ochlerotatus vigilax; (3) The mitogenome results indicate a close relationship between Anopheles epiroticus and Anopheles gambiae complex, Anopheles dirus complex and Anopheles punctulatus group, respectively; (4) The Bayesian posterior probability (BPP) within phylogenetic tree reconstructed by mitogenomes is higher than COI tree. The results show that phylogenetic relationships reconstructed using the mitogenomes were more similar to those based on morphological data.

Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization.

PubMed

Nishio, Mizuho; Nishizawa, Mitsuo; Sugiyama, Osamu; Kojima, Ryosuke; Yakami, Masahiro; Kuroda, Tomohiro; Togashi, Kaori

2018-01-01

We aimed to evaluate a computer-aided diagnosis (CADx) system for lung nodule classification focussing on (i) usefulness of the conventional CADx system (hand-crafted imaging feature + machine learning algorithm), (ii) comparison between support vector machine (SVM) and gradient tree boosting (XGBoost) as machine learning algorithms, and (iii) effectiveness of parameter optimization using Bayesian optimization and random search. Data on 99 lung nodules (62 lung cancers and 37 benign lung nodules) were included from public databases of CT images. A variant of the local binary pattern was used for calculating a feature vector. SVM or XGBoost was trained using the feature vector and its corresponding label. Tree Parzen Estimator (TPE) was used as Bayesian optimization for parameters of SVM and XGBoost. Random search was done for comparison with TPE. Leave-one-out cross-validation was used for optimizing and evaluating the performance of our CADx system. Performance was evaluated using area under the curve (AUC) of receiver operating characteristic analysis. AUC was calculated 10 times, and its average was obtained. The best averaged AUC of SVM and XGBoost was 0.850 and 0.896, respectively; both were obtained using TPE. XGBoost was generally superior to SVM. Optimal parameters for achieving high AUC were obtained with fewer numbers of trials when using TPE, compared with random search. Bayesian optimization of SVM and XGBoost parameters was more efficient than random search. Based on observer study, AUC values of two board-certified radiologists were 0.898 and 0.822. The results show that diagnostic accuracy of our CADx system was comparable to that of radiologists with respect to classifying lung nodules.

Bayesian Design of Superiority Clinical Trials for Recurrent Events Data with Applications to Bleeding and Transfusion Events in Myelodyplastic Syndrome

PubMed Central

Chen, Ming-Hui; Zeng, Donglin; Hu, Kuolung; Jia, Catherine

2014-01-01

Summary In many biomedical studies, patients may experience the same type of recurrent event repeatedly over time, such as bleeding, multiple infections and disease. In this article, we propose a Bayesian design to a pivotal clinical trial in which lower risk myelodysplastic syndromes (MDS) patients are treated with MDS disease modifying therapies. One of the key study objectives is to demonstrate the investigational product (treatment) effect on reduction of platelet transfusion and bleeding events while receiving MDS therapies. In this context, we propose a new Bayesian approach for the design of superiority clinical trials using recurrent events frailty regression models. Historical recurrent events data from an already completed phase 2 trial are incorporated into the Bayesian design via the partial borrowing power prior of Ibrahim et al. (2012, Biometrics 68, 578–586). An efficient Gibbs sampling algorithm, a predictive data generation algorithm, and a simulation-based algorithm are developed for sampling from the fitting posterior distribution, generating the predictive recurrent events data, and computing various design quantities such as the type I error rate and power, respectively. An extensive simulation study is conducted to compare the proposed method to the existing frequentist methods and to investigate various operating characteristics of the proposed design. PMID:25041037

A Bayes linear Bayes method for estimation of correlated event rates.

PubMed

Quigley, John; Wilson, Kevin J; Walls, Lesley; Bedford, Tim

2013-12-01

Typically, full Bayesian estimation of correlated event rates can be computationally challenging since estimators are intractable. When estimation of event rates represents one activity within a larger modeling process, there is an incentive to develop more efficient inference than provided by a full Bayesian model. We develop a new subjective inference method for correlated event rates based on a Bayes linear Bayes model under the assumption that events are generated from a homogeneous Poisson process. To reduce the elicitation burden we introduce homogenization factors to the model and, as an alternative to a subjective prior, an empirical method using the method of moments is developed. Inference under the new method is compared against estimates obtained under a full Bayesian model, which takes a multivariate gamma prior, where the predictive and posterior distributions are derived in terms of well-known functions. The mathematical properties of both models are presented. A simulation study shows that the Bayes linear Bayes inference method and the full Bayesian model provide equally reliable estimates. An illustrative example, motivated by a problem of estimating correlated event rates across different users in a simple supply chain, shows how ignoring the correlation leads to biased estimation of event rates. © 2013 Society for Risk Analysis.

Tropical rainforests that persisted: inferences from the Quaternary demographic history of eight tree species in the Guiana shield.

PubMed

Barthe, Stéphanie; Binelli, Giorgio; Hérault, Bruno; Scotti-Saintagne, Caroline; Sabatier, Daniel; Scotti, Ivan

2017-02-01

How Quaternary climatic and geological disturbances influenced the composition of Neotropical forests is hotly debated. Rainfall and temperature changes during and/or immediately after the last glacial maximum (LGM) are thought to have strongly affected the geographical distribution and local abundance of tree species. The paucity of the fossil records in Neotropical forests prevents a direct reconstruction of such processes. To describe community-level historical trends in forest composition, we turned therefore to inferential methods based on the reconstruction of past demographic changes. In particular, we modelled the history of rainforests in the eastern Guiana Shield over a timescale of several thousand generations, through the application of approximate Bayesian computation and maximum-likelihood methods to diversity data at nuclear and chloroplast loci in eight species or subspecies of rainforest trees. Depending on the species and on the method applied, we detected population contraction, expansion or stability, with a general trend in favour of stability or expansion, with changes presumably having occurred during or after the LGM. These findings suggest that Guiana Shield rainforests have globally persisted, while expanding, through the Quaternary, but that different species have experienced different demographic events, with a trend towards the increase in frequency of light-demanding, disturbance-associated species. © 2016 John Wiley & Sons Ltd.

Species-richness of the Anopheles annulipes Complex (Diptera: Culicidae) Revealed by Tree and Model-Based Allozyme Clustering Analyses

DTIC Science & Technology

2007-01-01

including tree- based methods such as the unweighted pair group method of analysis ( UPGMA ) and Neighbour-joining (NJ) (Saitou & Nei, 1987). By...based Bayesian approach and the tree-based UPGMA and NJ cluster- ing methods. The results obtained suggest that far more species occur in the An...unlikely that groups that differ by more than these levels are conspecific. Genetic distances were clustered using the UPGMA and NJ algorithms in MEGA

Predicting Tree Mortality From Diameter Growth: A Comparison of Maximum Likelihood and Bayesian Approaches

Treesearch

Peter H. Wychoff; James S. Clark

2000-01-01

Ecologists and foresters have long noted a link between tree growth rate and mortality, and recent work suggests that i&erspecific differences in low growth tolerauce is a key force shaping forest structure. Little information is available, however, on the growth-mortality relationship for most species. We present three methods for estimating growth-mortality...

Calibrated tree priors for relaxed phylogenetics and divergence time estimation.

PubMed

Heled, Joseph; Drummond, Alexei J

2012-01-01

The use of fossil evidence to calibrate divergence time estimation has a long history. More recently, Bayesian Markov chain Monte Carlo has become the dominant method of divergence time estimation, and fossil evidence has been reinterpreted as the specification of prior distributions on the divergence times of calibration nodes. These so-called "soft calibrations" have become widely used but the statistical properties of calibrated tree priors in a Bayesian setting hashave not been carefully investigated. Here, we clarify that calibration densities, such as those defined in BEAST 1.5, do not represent the marginal prior distribution of the calibration node. We illustrate this with a number of analytical results on small trees. We also describe an alternative construction for a calibrated Yule prior on trees that allows direct specification of the marginal prior distribution of the calibrated divergence time, with or without the restriction of monophyly. This method requires the computation of the Yule prior conditional on the height of the divergence being calibrated. Unfortunately, a practical solution for multiple calibrations remains elusive. Our results suggest that direct estimation of the prior induced by specifying multiple calibration densities should be a prerequisite of any divergence time dating analysis.

Mitogenomes of two neotropical bird species and the multiple independent origin of mitochondrial gene orders in Passeriformes.

PubMed

Caparroz, Renato; Rocha, Amanda V; Cabanne, Gustavo S; Tubaro, Pablo; Aleixo, Alexandre; Lemmon, Emily M; Lemmon, Alan R

2018-06-01

At least four mitogenome arrangements occur in Passeriformes and differences among them are derived from an initial tandem duplication involving a segment containing the control region (CR), followed by loss or reduction of some parts of this segment. However, it is still unclear how often duplication events have occurred in this bird order. In this study, the mitogenomes from two species of Neotropical passerines (Sicalis olivascens and Lepidocolaptes angustirostris) with different gene arrangements were first determined. We also estimated how often duplication events occurred in Passeriformes and if the two CR copies demonstrate a pattern of concerted evolution in Sylvioidea. One tissue sample for each species was used to obtain the mitogenomes as a byproduct using next generation sequencing. The evolutionary history of mitogenome rearrangements was reconstructed mapping these characters onto a mitogenome Bayesian phylogenetic tree of Passeriformes. Finally, we performed a Bayesian analysis for both CRs from some Sylvioidea species in order to evaluate the evolutionary process involving these two copies. Both mitogenomes described comprise 2 rRNAs, 22 tRNAs, 13 protein-codon genes and the CR. However, S. olivascens has 16,768 bp showing the ancestral avian arrangement, while L. angustirostris has 16,973 bp and the remnant CR2 arrangement. Both species showed the expected gene order compared to their closest relatives. The ancestral state reconstruction suggesting at least six independent duplication events followed by partial deletions or loss of one copy in some lineages. Our results also provide evidence that both CRs in some Sylvioidea species seem to be maintained in an apparently functional state, perhaps by concerted evolution, and that this mechanism may be important for the evolution of the bird mitogenome.

A methodology for risk analysis based on hybrid Bayesian networks: application to the regasification system of liquefied natural gas onboard a floating storage and regasification unit.

PubMed

Martins, Marcelo Ramos; Schleder, Adriana Miralles; Droguett, Enrique López

2014-12-01

This article presents an iterative six-step risk analysis methodology based on hybrid Bayesian networks (BNs). In typical risk analysis, systems are usually modeled as discrete and Boolean variables with constant failure rates via fault trees. Nevertheless, in many cases, it is not possible to perform an efficient analysis using only discrete and Boolean variables. The approach put forward by the proposed methodology makes use of BNs and incorporates recent developments that facilitate the use of continuous variables whose values may have any probability distributions. Thus, this approach makes the methodology particularly useful in cases where the available data for quantification of hazardous events probabilities are scarce or nonexistent, there is dependence among events, or when nonbinary events are involved. The methodology is applied to the risk analysis of a regasification system of liquefied natural gas (LNG) on board an FSRU (floating, storage, and regasification unit). LNG is becoming an important energy source option and the world's capacity to produce LNG is surging. Large reserves of natural gas exist worldwide, particularly in areas where the resources exceed the demand. Thus, this natural gas is liquefied for shipping and the storage and regasification process usually occurs at onshore plants. However, a new option for LNG storage and regasification has been proposed: the FSRU. As very few FSRUs have been put into operation, relevant failure data on FSRU systems are scarce. The results show the usefulness of the proposed methodology for cases where the risk analysis must be performed under considerable uncertainty. © 2014 Society for Risk Analysis.

Genetic basis of climatic adaptation in scots pine by bayesian quantitative trait locus analysis.

PubMed Central

Hurme, P; Sillanpää, M J; Arjas, E; Repo, T; Savolainen, O

2000-01-01

We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an "open-pollinated backcross" progeny by collecting seeds of a single F(1) tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect. PMID:11063704

Resolving contradictory reconstructions of Alpine climate in 1540 - Using Nonlinearities in Tree Growth Response to Climate

NASA Astrophysics Data System (ADS)

Werner, J.; Tolwinski-ward, S. E.

2013-12-01

Reconstructions of Swiss climate based on documentary data suggest that the year 1540 was anomalously hot and dry (Wetter and Pfister 2013, Wetter et al in prep). They stand in stark contrast to reconstructions from tree ring data (Casty et al. 2005) in which 1540 climate is within the range of average conditions. In this contribution we combine documentary and dendrochronological sources of information and account for potential nonlinearities in the response of the tree ring signal to climate in order to resolve this apparent contradiction. Our reconstruction uses a Bayesian hierarchical model, with a nonlinear, mechanisms-based model for tree-ring data (Tolwinski-Ward et al. 2010) and a multinomial model for the documentary data. The results show that the extreme heat conditions documented in written crop records of 1540 cross a biological threshold above which the formation of latewood density is not limited by temperature. We thus demonstrate that the tree ring and documentary data for 1540 are in fact consistent within the ranges of uncertainty used to interpret each source of information, and together indicate anomalously hot and dry conditions in that year, although to a lesser extend as reconstructed by Wetter and Pfister (2013). Casty et al. "Temperature and precipitation variability in the European Alps since 1500", Int. J. Climatol. 25, 1855-1880 (2005) Tolwinski-Ward et al. "An efficient forward model of the climate controls on interannual variation in tree-ring width", Clim. Dyn. 36, 2419--2439 (2010) Werner and Tolwinski-Ward, in prep. Wetter and Pfister "An underestimated record breaking event: why summer 1540 was very likely warmer than 2003", Clim. Past 9, 41-56 (2013) Wetter et al. "The European Mega-drought of 1540 - an evidence-based Worst Case Scenario" (in prep.)

Data set for phylogenetic tree and RAMPAGE Ramachandran plot analysis of SODs in Gossypium raimondii and G. arboreum.

PubMed

Wang, Wei; Xia, Minxuan; Chen, Jie; Deng, Fenni; Yuan, Rui; Zhang, Xiaopei; Shen, Fafu

2016-12-01

The data presented in this paper is supporting the research article "Genome-Wide Analysis of Superoxide Dismutase Gene Family in Gossypium raimondii and G. arboreum" [1]. In this data article, we present phylogenetic tree showing dichotomy with two different clusters of SODs inferred by the Bayesian method of MrBayes (version 3.2.4), "Bayesian phylogenetic inference under mixed models" [2], Ramachandran plots of G. raimondii and G. arboreum SODs, the protein sequence used to generate 3D sructure of proteins and the template accession via SWISS-MODEL server, "SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information." [3] and motif sequences of SODs identified by InterProScan (version 4.8) with the Pfam database, "Pfam: the protein families database" [4].

Multivariate Bayesian modeling of known and unknown causes of events--an application to biosurveillance.

PubMed

Shen, Yanna; Cooper, Gregory F

2012-09-01

This paper investigates Bayesian modeling of known and unknown causes of events in the context of disease-outbreak detection. We introduce a multivariate Bayesian approach that models multiple evidential features of every person in the population. This approach models and detects (1) known diseases (e.g., influenza and anthrax) by using informative prior probabilities and (2) unknown diseases (e.g., a new, highly contagious respiratory virus that has never been seen before) by using relatively non-informative prior probabilities. We report the results of simulation experiments which support that this modeling method can improve the detection of new disease outbreaks in a population. A contribution of this paper is that it introduces a multivariate Bayesian approach for jointly modeling both known and unknown causes of events. Such modeling has general applicability in domains where the space of known causes is incomplete. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

ABrox-A user-friendly Python module for approximate Bayesian computation with a focus on model comparison.

PubMed

Mertens, Ulf Kai; Voss, Andreas; Radev, Stefan

2018-01-01

We give an overview of the basic principles of approximate Bayesian computation (ABC), a class of stochastic methods that enable flexible and likelihood-free model comparison and parameter estimation. Our new open-source software called ABrox is used to illustrate ABC for model comparison on two prominent statistical tests, the two-sample t-test and the Levene-Test. We further highlight the flexibility of ABC compared to classical Bayesian hypothesis testing by computing an approximate Bayes factor for two multinomial processing tree models. Last but not least, throughout the paper, we introduce ABrox using the accompanied graphical user interface.

Investigating processes of neotropical rain forest tree diversification by examining the evolution and historical biogeography of the Protieae (Burseraceae).

PubMed

Fine, Paul V A; Zapata, Felipe; Daly, Douglas C

2014-07-01

Andean uplift and the collision of North and South America are thought to have major implications for the diversification of the Neotropical biota. However, few studies have investigated how these geological events may have influenced diversification. We present a multilocus phylogeny of 102 Protieae taxa (73% of published species), sampled pantropically, to test hypotheses about the relative importance of dispersal, vicariance, habitat specialization, and biotic factors in the diversification of this ecologically dominant tribe of Neotropical trees. Bayesian fossil-calibrated analyses date the Protieae stem at 55 Mya. Biogeographic analyses reconstruct an initial late Oligocene/early Miocene radiation in Amazonia for Neotropical Protieae, with several subsequent late Miocene dispersal events to Central America, the Caribbean, Brazil's Atlantic Forest, and the Chocó. Regional phylogenetic structure results indicate frequent dispersal among regions throughout the Miocene and many instances of more recent regional in situ speciation. Habitat specialization to white sand or flooded soils was common, especially in Amazonia. There was one significant increase in diversification rate coincident with colonization of the Neotropics, followed by a gradual decrease consistent with models of diversity-dependent cladogenesis. Dispersal, biotic interactions, and habitat specialization are thus hypothesized to be the most important processes underlying the diversification of the Protieae. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Numerical study on the sequential Bayesian approach for radioactive materials detection

NASA Astrophysics Data System (ADS)

Qingpei, Xiang; Dongfeng, Tian; Jianyu, Zhu; Fanhua, Hao; Ge, Ding; Jun, Zeng

2013-01-01

A new detection method, based on the sequential Bayesian approach proposed by Candy et al., offers new horizons for the research of radioactive detection. Compared with the commonly adopted detection methods incorporated with statistical theory, the sequential Bayesian approach offers the advantages of shorter verification time during the analysis of spectra that contain low total counts, especially in complex radionuclide components. In this paper, a simulation experiment platform implanted with the methodology of sequential Bayesian approach was developed. Events sequences of γ-rays associating with the true parameters of a LaBr3(Ce) detector were obtained based on an events sequence generator using Monte Carlo sampling theory to study the performance of the sequential Bayesian approach. The numerical experimental results are in accordance with those of Candy. Moreover, the relationship between the detection model and the event generator, respectively represented by the expected detection rate (Am) and the tested detection rate (Gm) parameters, is investigated. To achieve an optimal performance for this processor, the interval of the tested detection rate as a function of the expected detection rate is also presented.

Inferences of biogeographical histories within subfamily Hyacinthoideae using S-DIVA and Bayesian binary MCMC analysis implemented in RASP (Reconstruct Ancestral State in Phylogenies)

PubMed Central

Ali, Syed Shujait; Yu, Yan; Pfosser, Martin; Wetschnig, Wolfgang

2012-01-01

Background and Aims Subfamily Hyacinthoideae (Hyacinthaceae) comprises more than 400 species. Members are distributed in sub-Saharan Africa, Madagascar, India, eastern Asia, the Mediterranean region and Eurasia. Hyacinthoideae, like many other plant lineages, show disjunct distribution patterns. The aim of this study was to reconstruct the biogeographical history of Hyacinthoideae based on phylogenetic analyses, to find the possible ancestral range of Hyacinthoideae and to identify factors responsible for the current disjunct distribution pattern. Methods Parsimony and Bayesian approaches were applied to obtain phylogenetic trees, based on sequences of the trnL-F region. Biogeographical inferences were obtained by applying statistical dispersal-vicariance analysis (S-DIVA) and Bayesian binary MCMC (BBM) analysis implemented in RASP (Reconstruct Ancestral State in Phylogenies). Key Results S-DIVA and BBM analyses suggest that the Hyacinthoideae clade seem to have originated in sub-Saharan Africa. Dispersal and vicariance played vital roles in creating the disjunct distribution pattern. Results also suggest an early dispersal to the Mediterranean region, and thus the northward route (from sub-Saharan Africa to Mediterranean) of dispersal is plausible for members of subfamily Hyacinthoideae. Conclusions Biogeographical analyses reveal that subfamily Hyacinthoideae has originated in sub-Saharan Africa. S-DIVA indicates an early dispersal event to the Mediterranean region followed by a vicariance event, which resulted in Hyacintheae and Massonieae tribes. By contrast, BBM analysis favours dispersal to the Mediterranean region, eastern Asia and Europe. Biogeographical analysis suggests that sub-Saharan Africa and the Mediterranean region have played vital roles as centres of diversification and radiation within subfamily Hyacinthoideae. In this bimodal distribution pattern, sub-Saharan Africa is the primary centre of diversity and the Mediterranean region is the secondary centre of diversity. Sub-Saharan Africa was the source area for radiation toward Madagascar, the Mediterranean region and India. Radiations occurred from the Mediterranean region to eastern Asia, Europe, western Asia and India. PMID:22039008

Higher level phylogeny and the first divergence time estimation of Heteroptera (Insecta: Hemiptera) based on multiple genes.

PubMed

Li, Min; Tian, Ying; Zhao, Ying; Bu, Wenjun

2012-01-01

Heteroptera, or true bugs, are the largest, morphologically diverse and economically important group of insects with incomplete metamorphosis. However, the phylogenetic relationships within Heteroptera are still in dispute and most of the previous studies were based on morphological characters or with single gene (partial or whole 18S rDNA). Besides, so far, divergence time estimates for Heteroptera totally rely on the fossil record, while no studies have been performed on molecular divergence rates. Here, for the first time, we used maximum parsimony (MP), maximum likelihood (ML) and Bayesian inference (BI) with multiple genes (18S rDNA, 28S rDNA, 16S rDNA and COI) to estimate phylogenetic relationships among the infraorders, and meanwhile, the Penalized Likelihood (r8s) and Bayesian (BEAST) molecular dating methods were employed to estimate divergence time of higher taxa of this suborder. Major results of the present study included: Nepomorpha was placed as the most basal clade in all six trees (MP trees, ML trees and Bayesian trees of nuclear gene data and four-gene combined data, respectively) with full support values. The sister-group relationship of Cimicomorpha and Pentatomomorpha was also strongly supported. Nepomorpha originated in early Triassic and the other six infraorders originated in a very short period of time in middle Triassic. Cimicomorpha and Pentatomomorpha underwent a radiation at family level in Cretaceous, paralleling the proliferation of the flowering plants. Our results indicated that the higher-group radiations within hemimetabolous Heteroptera were simultaneously with those of holometabolous Coleoptera and Diptera which took place in the Triassic. While the aquatic habitat was colonized by Nepomorpha already in the Triassic, the Gerromorpha independently adapted to the semi-aquatic habitat in the Early Jurassic.

Higher Level Phylogeny and the First Divergence Time Estimation of Heteroptera (Insecta: Hemiptera) Based on Multiple Genes

PubMed Central

Zhao, Ying; Bu, Wenjun

2012-01-01

Heteroptera, or true bugs, are the largest, morphologically diverse and economically important group of insects with incomplete metamorphosis. However, the phylogenetic relationships within Heteroptera are still in dispute and most of the previous studies were based on morphological characters or with single gene (partial or whole 18S rDNA). Besides, so far, divergence time estimates for Heteroptera totally rely on the fossil record, while no studies have been performed on molecular divergence rates. Here, for the first time, we used maximum parsimony (MP), maximum likelihood (ML) and Bayesian inference (BI) with multiple genes (18S rDNA, 28S rDNA, 16S rDNA and COI) to estimate phylogenetic relationships among the infraorders, and meanwhile, the Penalized Likelihood (r8s) and Bayesian (BEAST) molecular dating methods were employed to estimate divergence time of higher taxa of this suborder. Major results of the present study included: Nepomorpha was placed as the most basal clade in all six trees (MP trees, ML trees and Bayesian trees of nuclear gene data and four-gene combined data, respectively) with full support values. The sister-group relationship of Cimicomorpha and Pentatomomorpha was also strongly supported. Nepomorpha originated in early Triassic and the other six infraorders originated in a very short period of time in middle Triassic. Cimicomorpha and Pentatomomorpha underwent a radiation at family level in Cretaceous, paralleling the proliferation of the flowering plants. Our results indicated that the higher-group radiations within hemimetabolous Heteroptera were simultaneously with those of holometabolous Coleoptera and Diptera which took place in the Triassic. While the aquatic habitat was colonized by Nepomorpha already in the Triassic, the Gerromorpha independently adapted to the semi-aquatic habitat in the Early Jurassic. PMID:22384163

Interpreting the Climatic Effects on Xylem Functional Traits in Two Mediterranean Oak Species: The Role of Extreme Climatic Events.

PubMed

Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio

2016-01-01

In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions.

Interpreting the Climatic Effects on Xylem Functional Traits in Two Mediterranean Oak Species: The Role of Extreme Climatic Events

PubMed Central

Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio

2016-01-01

In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions. PMID:27532008

Comparing models for quantitative risk assessment: an application to the European Registry of foreign body injuries in children.

PubMed

Berchialla, Paola; Scarinzi, Cecilia; Snidero, Silvia; Gregori, Dario

2016-08-01

Risk Assessment is the systematic study of decisions subject to uncertain consequences. An increasing interest has been focused on modeling techniques like Bayesian Networks since their capability of (1) combining in the probabilistic framework different type of evidence including both expert judgments and objective data; (2) overturning previous beliefs in the light of the new information being received and (3) making predictions even with incomplete data. In this work, we proposed a comparison among Bayesian Networks and other classical Quantitative Risk Assessment techniques such as Neural Networks, Classification Trees, Random Forests and Logistic Regression models. Hybrid approaches, combining both Classification Trees and Bayesian Networks, were also considered. Among Bayesian Networks, a clear distinction between purely data-driven approach and combination of expert knowledge with objective data is made. The aim of this paper consists in evaluating among this models which best can be applied, in the framework of Quantitative Risk Assessment, to assess the safety of children who are exposed to the risk of inhalation/insertion/aspiration of consumer products. The issue of preventing injuries in children is of paramount importance, in particular where product design is involved: quantifying the risk associated to product characteristics can be of great usefulness in addressing the product safety design regulation. Data of the European Registry of Foreign Bodies Injuries formed the starting evidence for risk assessment. Results showed that Bayesian Networks appeared to have both the ease of interpretability and accuracy in making prediction, even if simpler models like logistic regression still performed well. © The Author(s) 2013.

Accurate Phylogenetic Tree Reconstruction from Quartets: A Heuristic Approach

PubMed Central

Reaz, Rezwana; Bayzid, Md. Shamsuzzoha; Rahman, M. Sohel

2014-01-01

Supertree methods construct trees on a set of taxa (species) combining many smaller trees on the overlapping subsets of the entire set of taxa. A ‘quartet’ is an unrooted tree over taxa, hence the quartet-based supertree methods combine many -taxon unrooted trees into a single and coherent tree over the complete set of taxa. Quartet-based phylogeny reconstruction methods have been receiving considerable attentions in the recent years. An accurate and efficient quartet-based method might be competitive with the current best phylogenetic tree reconstruction methods (such as maximum likelihood or Bayesian MCMC analyses), without being as computationally intensive. In this paper, we present a novel and highly accurate quartet-based phylogenetic tree reconstruction method. We performed an extensive experimental study to evaluate the accuracy and scalability of our approach on both simulated and biological datasets. PMID:25117474

Decadal-scale ecosystem memory reveals interactive effects of drought and insect defoliation on boreal forest productivity

NASA Astrophysics Data System (ADS)

Itter, M.; D'Orangeville, L.; Dawson, A.; Kneeshaw, D.; Finley, A. O.

2017-12-01

Drought and insect defoliation have lasting impacts on the dynamics of the boreal forest. Impacts are expected to worsen under global climate change as hotter, drier conditions forecast for much of the boreal increase the frequency and severity of drought and defoliation events. Contemporary ecological theory predicts physiological feedbacks in tree responses to drought and defoliation amplify impacts potentially causing large-scale productivity losses and forest mortality. Quantifying the interactive impacts of drought and insect defoliation on regional forest health is difficult given delayed and persistent responses to disturbance events. We developed a Bayesian hierarchical model to estimate forest growth responses to interactions between drought and insect defoliation by species and size class. Delayed and persistent responses to past drought and defoliation were quantified using empirical memory functions allowing for improved detection of interactions. The model was applied to tree-ring data from stands in Western (Alberta) and Eastern (Québec) regions of the Canadian boreal forest with different species compositions, disturbance regimes, and regional climates. Western stands experience chronic water deficit and forest tent caterpillar (FTC) defoliation; Eastern stands experience irregular water deficit and spruce budworm (SBW) defoliation. Ecosystem memory to past water deficit peaked in the year previous to growth and decayed to zero within 5 (West) to 8 (East) years; memory to past defoliation ranged from 8 (West) to 12 (East) years. The drier regional climate and faster FTC defoliation dynamics (compared to SBW) likely contribute to shorter ecosystem memory in the West. Drought and defoliation had the largest negative impact on large-diameter, host tree growth. Surprisingly, a positive interaction was observed between drought and defoliation for large-diameter, non-host trees likely due to reduced stand-level competition for water. Results highlight the temporal persistence of drought and defoliation stress on boreal forest growth dynamics and provide an empirical estimate of their interactive effects with explicit uncertainty.

Bayesian truthing and experimental validation in homeland security and defense

NASA Astrophysics Data System (ADS)

Jannson, Tomasz; Forrester, Thomas; Wang, Wenjian; Kostrzewski, Andrew; Pradhan, Ranjit

2014-05-01

In this paper we discuss relations between Bayesian Truthing (experimental validation), Bayesian statistics, and Binary Sensing in the context of selected Homeland Security and Intelligence, Surveillance, Reconnaissance (ISR) optical and nonoptical application scenarios. The basic Figure of Merit (FoM) is Positive Predictive Value (PPV), as well as false positives and false negatives. By using these simple binary statistics, we can analyze, classify, and evaluate a broad variety of events including: ISR; natural disasters; QC; and terrorism-related, GIS-related, law enforcement-related, and other C3I events.

The Estimation of Tree Posterior Probabilities Using Conditional Clade Probability Distributions

PubMed Central

Larget, Bret

2013-01-01

In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample. [Bayesian phylogenetics; conditional clade distributions; improved accuracy; posterior probabilities of trees.] PMID:23479066

Tree Classification Software

NASA Technical Reports Server (NTRS)

Buntine, Wray

1993-01-01

This paper introduces the IND Tree Package to prospective users. IND does supervised learning using classification trees. This learning task is a basic tool used in the development of diagnosis, monitoring and expert systems. The IND Tree Package was developed as part of a NASA project to semi-automate the development of data analysis and modelling algorithms using artificial intelligence techniques. The IND Tree Package integrates features from CART and C4 with newer Bayesian and minimum encoding methods for growing classification trees and graphs. The IND Tree Package also provides an experimental control suite on top. The newer features give improved probability estimates often required in diagnostic and screening tasks. The package comes with a manual, Unix 'man' entries, and a guide to tree methods and research. The IND Tree Package is implemented in C under Unix and was beta-tested at university and commercial research laboratories in the United States.

Temporal and spatial diversification of Pteroglossus araçaris (AVES: Ramphastidae) in the neotropics: constant rate of diversification does not support an increase in radiation during the Pleistocene.

PubMed

Patel, Swati; Weckstein, Jason D; Patané, José S L; Bates, John M; Aleixo, Alexandre

2011-01-01

We use the small-bodied toucan genus Pteroglossus to test hypotheses about diversification in the lowland Neotropics. We sequenced three mitochondrial genes and one nuclear intron from all Pteroglossus species and used these data to reconstruct phylogenetic trees based on maximum parsimony, maximum likelihood, and Bayesian analyses. These phylogenetic trees were used to make inferences regarding both the pattern and timing of diversification for the group. We used the uplift of the Talamanca highlands of Costa Rica and western Panama as a geologic calibration for estimating divergence times on the Pteroglossus tree and compared these results with a standard molecular clock calibration. Then, we used likelihood methods to model the rate of diversification. Based on our analyses, the onset of the Pteroglossus radiation predates the Pleistocene, which has been predicted to have played a pivotal role in diversification in the Amazon rainforest biota. We found a constant rate of diversification in Pteroglossus evolutionary history, and thus no support that events during the Pleistocene caused an increase in diversification. We compare our data to other avian phylogenies to better understand major biogeographic events in the Neotropics. These comparisons support recurring forest connections between the Amazonian and Atlantic forests, and the splitting of cis/trans Andean species after the final uplift of the Andes. At the subspecies level, there is evidence for reciprocal monophyly and groups are often separated by major rivers, demonstrating the important role of rivers in causing or maintaining divergence. Because some of the results presented here conflict with current taxonomy of Pteroglossus, new taxonomic arrangements are suggested. Copyright © 2010 Elsevier Inc. All rights reserved.

Using of bayesian networks to estimate the probability of "NATECH" scenario occurrence

NASA Astrophysics Data System (ADS)

Dobes, Pavel; Dlabka, Jakub; Jelšovská, Katarína; Polorecká, Mária; Baudišová, Barbora; Danihelka, Pavel

2015-04-01

In the twentieth century, implementation of Bayesian statistics and probability was not much used (may be it wasn't a preferred approach) in the area of natural and industrial risk analysis and management. Neither it was used within analysis of so called NATECH accidents (chemical accidents triggered by natural events, such as e.g. earthquakes, floods, lightning etc.; ref. E. Krausmann, 2011, doi:10.5194/nhess-11-921-2011). Main role, from the beginning, played here so called "classical" frequentist probability (ref. Neyman, 1937), which rely up to now especially on the right/false results of experiments and monitoring and didn't enable to count on expert's beliefs, expectations and judgements (which is, on the other hand, one of the once again well known pillars of Bayessian approach to probability). In the last 20 or 30 years, there is possible to observe, through publications and conferences, the Renaissance of Baysssian statistics into many scientific disciplines (also into various branches of geosciences). The necessity of a certain level of trust in expert judgment within risk analysis is back? After several decades of development on this field, it could be proposed following hypothesis (to be checked): "We couldn't estimate probabilities of complex crisis situations and their TOP events (many NATECH events could be classified as crisis situations or emergencies), only by classical frequentist approach, but also by using of Bayessian approach (i.e. with help of prestaged Bayessian Network including expert belief and expectation as well as classical frequentist inputs). Because - there is not always enough quantitative information from monitoring of historical emergencies, there could be several dependant or independant variables necessary to consider and in generally - every emergency situation always have a little different run." In this topic, team of authors presents its proposal of prestaged typized Bayessian network model for specified NATECH scenario (heavy rainfalls AND/OR melting snow OR earthquake -> landslides AND/OR floods -> major chemical accident), comparing it with "Black Box approach" and with so called "Bow-tie approach" (ref. C. A. Brebbia, Risk Analysis VIII, p.103-111 , WIT Press, 2012) - visualisation of development of the scenario with possibility to calculate frequencies (TOP event of the scenario, developed both ways down to initation events and upwards to end accidental events, using Fault Tree Analysis and Event Tree Analysis methods). This model can include also possible terrorist attack on the chemical facility with potential of major release of chemical into the environmental compartments (water, soil, air), with the goal to threaten environmental safety in the specific area. The study was supported by the project no. VG20132015128 "Increasing of the Environmental Safety & Security by the Prevention of Industrial Chemicals Misuse to the Terrorism", supported by the Ministry of the Interior of the Czech Republic through Security Research Programme, 2013-2015.

Molecular systematics of the new world screech-owls (Megascops: Aves, Strigidae): biogeographic and taxonomic implications.

PubMed

Dantas, Sidnei M; Weckstein, Jason D; Bates, John M; Krabbe, Niels K; Cadena, Carlos Daniel; Robbins, Mark B; Valderrama, Eugenio; Aleixo, Alexandre

2016-01-01

Megascops screech-owls are endemic to the New World and range from southern Canada to the southern cone of South America. The 22 currently recognized Megascops species occupy a wide range of habitats and elevations, from desert to humid montane forest, and from sea level to the Andean tree line. Species and subspecies diagnoses of Megascops are notoriously difficult due to subtle plumage differences among taxa with frequent plumage polymorphism. Using three mitochondrial and three nuclear genes we estimated a phylogeny for all but one Megascops species. Phylogenies were estimated with Maximum Likelihood and Bayesian Inference, and a Bayesian chronogram was reconstructed to assess the spatio-temporal context of Megascops diversification. Megascops was paraphyletic in the recovered tree topologies if the Puerto Rican endemic M. nudipes is included in the genus. However, the remaining taxa are monophyletic and form three major clades: (1) M. choliba, M. koepckeae, M. albogularis, M. clarkii, and M. trichopsis; (2) M. petersoni, M. marshalli, M. hoyi, M. ingens, and M. colombianus; and (3) M. asio, M. kennicottii, M. cooperi, M. barbarus, M. sanctaecatarinae, M. roboratus, M. watsonii, M. atricapilla, M. guatemalae, and M. vermiculatus. Megascops watsonii is paraphyletic with some individuals more closely related to M. atricapilla than to other members in that polytypic species. Also, allopatric populations of some other Megascops species were highly divergent, with levels of genetic differentiation greater than between some recognized species-pairs. Diversification within the genus is hypothesized to have taken place during the last 8 million years, with a likely origin in Central America. The genus later expanded over much of the Americas and then diversified via multiple dispersal events from the Andes into the Neotropical lowlands. Copyright © 2015 Elsevier Inc. All rights reserved.

The probabilistic convolution tree: efficient exact Bayesian inference for faster LC-MS/MS protein inference.

PubMed

Serang, Oliver

2014-01-01

Exact Bayesian inference can sometimes be performed efficiently for special cases where a function has commutative and associative symmetry of its inputs (called "causal independence"). For this reason, it is desirable to exploit such symmetry on big data sets. Here we present a method to exploit a general form of this symmetry on probabilistic adder nodes by transforming those probabilistic adder nodes into a probabilistic convolution tree with which dynamic programming computes exact probabilities. A substantial speedup is demonstrated using an illustration example that can arise when identifying splice forms with bottom-up mass spectrometry-based proteomics. On this example, even state-of-the-art exact inference algorithms require a runtime more than exponential in the number of splice forms considered. By using the probabilistic convolution tree, we reduce the runtime to O(k log(k)2) and the space to O(k log(k)) where k is the number of variables joined by an additive or cardinal operator. This approach, which can also be used with junction tree inference, is applicable to graphs with arbitrary dependency on counting variables or cardinalities and can be used on diverse problems and fields like forward error correcting codes, elemental decomposition, and spectral demixing. The approach also trivially generalizes to multiple dimensions.

The Probabilistic Convolution Tree: Efficient Exact Bayesian Inference for Faster LC-MS/MS Protein Inference

PubMed Central

Serang, Oliver

2014-01-01

Exact Bayesian inference can sometimes be performed efficiently for special cases where a function has commutative and associative symmetry of its inputs (called “causal independence”). For this reason, it is desirable to exploit such symmetry on big data sets. Here we present a method to exploit a general form of this symmetry on probabilistic adder nodes by transforming those probabilistic adder nodes into a probabilistic convolution tree with which dynamic programming computes exact probabilities. A substantial speedup is demonstrated using an illustration example that can arise when identifying splice forms with bottom-up mass spectrometry-based proteomics. On this example, even state-of-the-art exact inference algorithms require a runtime more than exponential in the number of splice forms considered. By using the probabilistic convolution tree, we reduce the runtime to and the space to where is the number of variables joined by an additive or cardinal operator. This approach, which can also be used with junction tree inference, is applicable to graphs with arbitrary dependency on counting variables or cardinalities and can be used on diverse problems and fields like forward error correcting codes, elemental decomposition, and spectral demixing. The approach also trivially generalizes to multiple dimensions. PMID:24626234

Enhancements to the Bayesian Infrasound Source Location Method

DTIC Science & Technology

2012-09-01

ENHANCEMENTS TO THE BAYESIAN INFRASOUND SOURCE LOCATION METHOD Omar E. Marcillo, Stephen J. Arrowsmith, Rod W. Whitaker, and Dale N. Anderson Los...ABSTRACT We report on R&D that is enabling enhancements to the Bayesian Infrasound Source Location (BISL) method for infrasound event location...the Bayesian Infrasound Source Location Method 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER

Bayesian Analysis for Risk Assessment of Selected Medical Events in Support of the Integrated Medical Model Effort

NASA Technical Reports Server (NTRS)

Gilkey, Kelly M.; Myers, Jerry G.; McRae, Michael P.; Griffin, Elise A.; Kallrui, Aditya S.

2012-01-01

The Exploration Medical Capability project is creating a catalog of risk assessments using the Integrated Medical Model (IMM). The IMM is a software-based system intended to assist mission planners in preparing for spaceflight missions by helping them to make informed decisions about medical preparations and supplies needed for combating and treating various medical events using Probabilistic Risk Assessment. The objective is to use statistical analyses to inform the IMM decision tool with estimated probabilities of medical events occurring during an exploration mission. Because data regarding astronaut health are limited, Bayesian statistical analysis is used. Bayesian inference combines prior knowledge, such as data from the general U.S. population, the U.S. Submarine Force, or the analog astronaut population located at the NASA Johnson Space Center, with observed data for the medical condition of interest. The posterior results reflect the best evidence for specific medical events occurring in flight. Bayes theorem provides a formal mechanism for combining available observed data with data from similar studies to support the quantification process. The IMM team performed Bayesian updates on the following medical events: angina, appendicitis, atrial fibrillation, atrial flutter, dental abscess, dental caries, dental periodontal disease, gallstone disease, herpes zoster, renal stones, seizure, and stroke.

Monte Carlo Simulation of Markov, Semi-Markov, and Generalized Semi- Markov Processes in Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

English, Thomas

2005-01-01

A standard tool of reliability analysis used at NASA-JSC is the event tree. An event tree is simply a probability tree, with the probabilities determining the next step through the tree specified at each node. The nodal probabilities are determined by a reliability study of the physical system at work for a particular node. The reliability study performed at a node is typically referred to as a fault tree analysis, with the potential of a fault tree existing.for each node on the event tree. When examining an event tree it is obvious why the event tree/fault tree approach has been adopted. Typical event trees are quite complex in nature, and the event tree/fault tree approach provides a systematic and organized approach to reliability analysis. The purpose of this study was two fold. Firstly, we wanted to explore the possibility that a semi-Markov process can create dependencies between sojourn times (the times it takes to transition from one state to the next) that can decrease the uncertainty when estimating time to failures. Using a generalized semi-Markov model, we studied a four element reliability model and were able to demonstrate such sojourn time dependencies. Secondly, we wanted to study the use of semi-Markov processes to introduce a time variable into the event tree diagrams that are commonly developed in PRA (Probabilistic Risk Assessment) analyses. Event tree end states which change with time are more representative of failure scenarios than are the usual static probability-derived end states.

Gene trees, species trees, and morphology converge on a similar phylogeny of living gars (Actinopterygii: Holostei: Lepisosteidae), an ancient clade of ray-finned fishes.

PubMed

Wright, Jeremy J; David, Solomon R; Near, Thomas J

2012-06-01

Extant gars represent the remaining members of a formerly diverse assemblage of ancient ray-finned fishes and have been the subject of multiple phylogenetic analyses using morphological data. Here, we present the first hypothesis of phylogenetic relationships among living gar species based on molecular data, through the examination of gene tree heterogeneity and coalescent species tree analyses of a portion of one mitochondrial (COI) and seven nuclear (ENC1, myh6, plagl2, S7 ribosomal protein intron 1, sreb2, tbr1, and zic1) genes. Individual gene trees displayed varying degrees of resolution with regards to species-level relationships, and the gene trees inferred from COI and the S7 intron were the only two that were completely resolved. Coalescent species tree analyses of nuclear genes resulted in a well-resolved and strongly supported phylogenetic tree of living gar species, for which Bayesian posterior node support was further improved by the inclusion of the mitochondrial gene. Species-level relationships among gars inferred from our molecular data set were highly congruent with previously published morphological phylogenies, with the exception of the placement of two species, Lepisosteus osseus and L. platostomus. Re-examination of the character coding used by previous authors provided partial resolution of this topological discordance, resulting in broad concordance in the phylogenies inferred from individual genes, the coalescent species tree analysis, and morphology. The completely resolved phylogeny inferred from the molecular data set with strong Bayesian posterior support at all nodes provided insights into the potential for introgressive hybridization and patterns of allopatric speciation in the evolutionary history of living gars, as well as a solid foundation for future examinations of functional diversification and evolutionary stasis in a "living fossil" lineage. Copyright © 2012 Elsevier Inc. All rights reserved.

Credible occurrence probabilities for extreme geophysical events: earthquakes, volcanic eruptions, magnetic storms

USGS Publications Warehouse

Love, Jeffrey J.

2012-01-01

Statistical analysis is made of rare, extreme geophysical events recorded in historical data -- counting the number of events $k$ with sizes that exceed chosen thresholds during specific durations of time $\\tau$. Under transformations that stabilize data and model-parameter variances, the most likely Poisson-event occurrence rate, $k/\\tau$, applies for frequentist inference and, also, for Bayesian inference with a Jeffreys prior that ensures posterior invariance under changes of variables. Frequentist confidence intervals and Bayesian (Jeffreys) credibility intervals are approximately the same and easy to calculate: $(1/\\tau)[(\\sqrt{k} - z/2)^{2},(\\sqrt{k} + z/2)^{2}]$, where $z$ is a parameter that specifies the width, $z=1$ ($z=2$) corresponding to $1\\sigma$, $68.3\\%$ ($2\\sigma$, $95.4\\%$). If only a few events have been observed, as is usually the case for extreme events, then these "error-bar" intervals might be considered to be relatively wide. From historical records, we estimate most likely long-term occurrence rates, 10-yr occurrence probabilities, and intervals of frequentist confidence and Bayesian credibility for large earthquakes, explosive volcanic eruptions, and magnetic storms.

Support vector machines

NASA Technical Reports Server (NTRS)

Garay, Michael J.; Mazzoni, Dominic; Davies, Roger; Wagstaff, Kiri

2004-01-01

Support Vector Machines (SVMs) are a type of supervised learning algorith,, other examples of which are Artificial Neural Networks (ANNs), Decision Trees, and Naive Bayesian Classifiers. Supervised learning algorithms are used to classify objects labled by a 'supervisor' - typically a human 'expert.'.

A Comparative Study to Predict Student’s Performance Using Educational Data Mining Techniques

NASA Astrophysics Data System (ADS)

Uswatun Khasanah, Annisa; Harwati

2017-06-01

Student’s performance prediction is essential to be conducted for a university to prevent student fail. Number of student drop out is one of parameter that can be used to measure student performance and one important point that must be evaluated in Indonesia university accreditation. Data Mining has been widely used to predict student’s performance, and data mining that applied in this field usually called as Educational Data Mining. This study conducted Feature Selection to select high influence attributes with student performance in Department of Industrial Engineering Universitas Islam Indonesia. Then, two popular classification algorithm, Bayesian Network and Decision Tree, were implemented and compared to know the best prediction result. The outcome showed that student’s attendance and GPA in the first semester were in the top rank from all Feature Selection methods, and Bayesian Network is outperforming Decision Tree since it has higher accuracy rate.

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

Phylogenetics of tribe Orchideae (Orchidaceae: Orchidoideae) based on combined DNA matrices: inferences regarding timing of diversification and evolution of pollination syndromes

PubMed Central

Inda, Luis A.; Pimentel, Manuel; Chase, Mark W.

2012-01-01

Background and aims Tribe Orchideae (Orchidaceae: Orchidoideae) comprises around 62 mostly terrestrial genera, which are well represented in the Northern Temperate Zone and less frequently in tropical areas of both the Old and New Worlds. Phylogenetic relationships within this tribe have been studied previously using only nuclear ribosomal DNA (nuclear ribosomal internal transcribed spacer, nrITS). However, different parts of the phylogenetic tree in these analyses were weakly supported, and integrating information from different plant genomes is clearly necessary in orchids, where reticulate evolution events are putatively common. The aims of this study were to: (1) obtain a well-supported and dated phylogenetic hypothesis for tribe Orchideae, (ii) assess appropriateness of recent nomenclatural changes in this tribe in the last decade, (3) detect possible examples of reticulate evolution and (4) analyse in a temporal context evolutionary trends for subtribe Orchidinae with special emphasis on pollination systems. Methods The analyses included 118 samples, belonging to 103 species and 25 genera, for three DNA regions (nrITS, mitochondrial cox1 intron and plastid rpl16 intron). Bayesian and maximum-parsimony methods were used to construct a well-supported and dated tree. Evolutionary trends in the subtribe were analysed using Bayesian and maximum-likelihood methods of character evolution. Key Results The dated phylogenetic tree strongly supported the recently recircumscribed generic concepts of Bateman and collaborators. Moreover, it was found that Orchidinae have diversified in the Mediterranean basin during the last 15 million years, and one potential example of reticulate evolution in the subtribe was identified. In Orchidinae, pollination systems have shifted on numerous occasions during the last 23 million years. Conclusions The results indicate that ancestral Orchidinae were hymenopteran-pollinated, food-deceptive plants and that these traits have been dominant throughout the evolutionary history of the subtribe in the Mediterranean. Evidence was also obtained that the onset of sexual deception might be linked to an increase in labellum size, and the possibility is discussed that diversification in Orchidinae developed in parallel with diversification of bees and wasps from the Miocene onwards. PMID:22539542

Large-scale pattern of genetic differentiation within African rainforest trees: insights on the roles of ecological gradients and past climate changes on the evolution of Erythrophleum spp (Fabaceae).

PubMed

Duminil, Jerome; Brown, Richard P; Ewédjè, Eben-Ezer B K; Mardulyn, Patrick; Doucet, Jean-Louis; Hardy, Olivier J

2013-09-12

The evolutionary events that have shaped biodiversity patterns in the African rainforests are still poorly documented. Past forest fragmentation and ecological gradients have been advocated as important drivers of genetic differentiation but their respective roles remain unclear. Using nuclear microsatellites (nSSRs) and chloroplast non-coding sequences (pDNA), we characterised the spatial genetic structure of Erythrophleum (Fabaceae) forest trees in West and Central Africa (Guinea Region, GR). This widespread genus displays a wide ecological amplitude and taxonomists recognize two forest tree species, E. ivorense and E. suaveolens, which are difficult to distinguish in the field and often confused. Bayesian-clustering applied on nSSRs of a blind sample of 648 specimens identified three major gene pools showing no or very limited introgression. They present parapatric distributions correlated to rainfall gradients and forest types. One gene pool is restricted to coastal evergreen forests and corresponds to E. ivorense; a second one is found in gallery forests from the dry forest zone of West Africa and North-West Cameroon and corresponds to West-African E. suaveolens; the third gene pool occurs in semi-evergreen forests and corresponds to Central African E. suaveolens. These gene pools have mostly unique pDNA haplotypes but they do not form reciprocally monophyletic clades. Nevertheless, pDNA molecular dating indicates that the divergence between E. ivorense and Central African E. suaveolens predates the Pleistocene. Further Bayesian-clustering applied within each major gene pool identified diffuse genetic discontinuities (minor gene pools displaying substantial introgression) at a latitude between 0 and 2°N in Central Africa for both species, and at a longitude between 5° and 8°E for E. ivorense. Moreover, we detected evidence of past population declines which are consistent with historical habitat fragmentation induced by Pleistocene climate changes. Overall, deep genetic differentiation (major gene pools) follows ecological gradients that may be at the origin of speciation, while diffuse differentiation (minor gene pools) are tentatively interpreted as the signature of past forest fragmentation induced by past climate changes.

Large-scale pattern of genetic differentiation within African rainforest trees: insights on the roles of ecological gradients and past climate changes on the evolution of Erythrophleum spp (Fabaceae)

PubMed Central

2013-01-01

Background The evolutionary events that have shaped biodiversity patterns in the African rainforests are still poorly documented. Past forest fragmentation and ecological gradients have been advocated as important drivers of genetic differentiation but their respective roles remain unclear. Using nuclear microsatellites (nSSRs) and chloroplast non-coding sequences (pDNA), we characterised the spatial genetic structure of Erythrophleum (Fabaceae) forest trees in West and Central Africa (Guinea Region, GR). This widespread genus displays a wide ecological amplitude and taxonomists recognize two forest tree species, E. ivorense and E. suaveolens, which are difficult to distinguish in the field and often confused. Results Bayesian-clustering applied on nSSRs of a blind sample of 648 specimens identified three major gene pools showing no or very limited introgression. They present parapatric distributions correlated to rainfall gradients and forest types. One gene pool is restricted to coastal evergreen forests and corresponds to E. ivorense; a second one is found in gallery forests from the dry forest zone of West Africa and North-West Cameroon and corresponds to West-African E. suaveolens; the third gene pool occurs in semi-evergreen forests and corresponds to Central African E. suaveolens. These gene pools have mostly unique pDNA haplotypes but they do not form reciprocally monophyletic clades. Nevertheless, pDNA molecular dating indicates that the divergence between E. ivorense and Central African E. suaveolens predates the Pleistocene. Further Bayesian-clustering applied within each major gene pool identified diffuse genetic discontinuities (minor gene pools displaying substantial introgression) at a latitude between 0 and 2°N in Central Africa for both species, and at a longitude between 5° and 8°E for E. ivorense. Moreover, we detected evidence of past population declines which are consistent with historical habitat fragmentation induced by Pleistocene climate changes. Conclusions Overall, deep genetic differentiation (major gene pools) follows ecological gradients that may be at the origin of speciation, while diffuse differentiation (minor gene pools) are tentatively interpreted as the signature of past forest fragmentation induced by past climate changes. PMID:24028582

Evolutionary inference via the Poisson Indel Process.

PubMed

Bouchard-Côté, Alexandre; Jordan, Michael I

2013-01-22

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

Evolutionary inference via the Poisson Indel Process

PubMed Central

Bouchard-Côté, Alexandre; Jordan, Michael I.

2013-01-01

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114–124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments. PMID:23275296

Derivation of Failure Rates and Probability of Failures for the International Space Station Probabilistic Risk Assessment Study

NASA Technical Reports Server (NTRS)

Vitali, Roberto; Lutomski, Michael G.

2004-01-01

National Aeronautics and Space Administration s (NASA) International Space Station (ISS) Program uses Probabilistic Risk Assessment (PRA) as part of its Continuous Risk Management Process. It is used as a decision and management support tool to not only quantify risk for specific conditions, but more importantly comparing different operational and management options to determine the lowest risk option and provide rationale for management decisions. This paper presents the derivation of the probability distributions used to quantify the failure rates and the probability of failures of the basic events employed in the PRA model of the ISS. The paper will show how a Bayesian approach was used with different sources of data including the actual ISS on orbit failures to enhance the confidence in results of the PRA. As time progresses and more meaningful data is gathered from on orbit failures, an increasingly accurate failure rate probability distribution for the basic events of the ISS PRA model can be obtained. The ISS PRA has been developed by mapping the ISS critical systems such as propulsion, thermal control, or power generation into event sequences diagrams and fault trees. The lowest level of indenture of the fault trees was the orbital replacement units (ORU). The ORU level was chosen consistently with the level of statistically meaningful data that could be obtained from the aerospace industry and from the experts in the field. For example, data was gathered for the solenoid valves present in the propulsion system of the ISS. However valves themselves are composed of parts and the individual failure of these parts was not accounted for in the PRA model. In other words the failure of a spring within a valve was considered a failure of the valve itself.

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

PubMed

Johnston, Iain G; Williams, Ben P

2016-02-24

Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

Estimating Tree Height-Diameter Models with the Bayesian Method

PubMed Central

Duan, Aiguo; Zhang, Jianguo; Xiang, Congwei

2014-01-01

Six candidate height-diameter models were used to analyze the height-diameter relationships. The common methods for estimating the height-diameter models have taken the classical (frequentist) approach based on the frequency interpretation of probability, for example, the nonlinear least squares method (NLS) and the maximum likelihood method (ML). The Bayesian method has an exclusive advantage compared with classical method that the parameters to be estimated are regarded as random variables. In this study, the classical and Bayesian methods were used to estimate six height-diameter models, respectively. Both the classical method and Bayesian method showed that the Weibull model was the “best” model using data1. In addition, based on the Weibull model, data2 was used for comparing Bayesian method with informative priors with uninformative priors and classical method. The results showed that the improvement in prediction accuracy with Bayesian method led to narrower confidence bands of predicted value in comparison to that for the classical method, and the credible bands of parameters with informative priors were also narrower than uninformative priors and classical method. The estimated posterior distributions for parameters can be set as new priors in estimating the parameters using data2. PMID:24711733

Estimating tree height-diameter models with the Bayesian method.

PubMed

Zhang, Xiongqing; Duan, Aiguo; Zhang, Jianguo; Xiang, Congwei

2014-01-01

Six candidate height-diameter models were used to analyze the height-diameter relationships. The common methods for estimating the height-diameter models have taken the classical (frequentist) approach based on the frequency interpretation of probability, for example, the nonlinear least squares method (NLS) and the maximum likelihood method (ML). The Bayesian method has an exclusive advantage compared with classical method that the parameters to be estimated are regarded as random variables. In this study, the classical and Bayesian methods were used to estimate six height-diameter models, respectively. Both the classical method and Bayesian method showed that the Weibull model was the "best" model using data1. In addition, based on the Weibull model, data2 was used for comparing Bayesian method with informative priors with uninformative priors and classical method. The results showed that the improvement in prediction accuracy with Bayesian method led to narrower confidence bands of predicted value in comparison to that for the classical method, and the credible bands of parameters with informative priors were also narrower than uninformative priors and classical method. The estimated posterior distributions for parameters can be set as new priors in estimating the parameters using data2.

A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems.

PubMed

Yin, Weiwei; Garimalla, Swetha; Moreno, Alberto; Galinski, Mary R; Styczynski, Mark P

2015-08-28

There are increasing efforts to bring high-throughput systems biology techniques to bear on complex animal model systems, often with a goal of learning about underlying regulatory network structures (e.g., gene regulatory networks). However, complex animal model systems typically have significant limitations on cohort sizes, number of samples, and the ability to perform follow-up and validation experiments. These constraints are particularly problematic for many current network learning approaches, which require large numbers of samples and may predict many more regulatory relationships than actually exist. Here, we test the idea that by leveraging the accuracy and efficiency of classifiers, we can construct high-quality networks that capture important interactions between variables in datasets with few samples. We start from a previously-developed tree-like Bayesian classifier and generalize its network learning approach to allow for arbitrary depth and complexity of tree-like networks. Using four diverse sample networks, we demonstrate that this approach performs consistently better at low sample sizes than the Sparse Candidate Algorithm, a representative approach for comparison because it is known to generate Bayesian networks with high positive predictive value. We develop and demonstrate a resampling-based approach to enable the identification of a viable root for the learned tree-like network, important for cases where the root of a network is not known a priori. We also develop and demonstrate an integrated resampling-based approach to the reduction of variable space for the learning of the network. Finally, we demonstrate the utility of this approach via the analysis of a transcriptional dataset of a malaria challenge in a non-human primate model system, Macaca mulatta, suggesting the potential to capture indicators of the earliest stages of cellular differentiation during leukopoiesis. We demonstrate that by starting from effective and efficient approaches for creating classifiers, we can identify interesting tree-like network structures with significant ability to capture the relationships in the training data. This approach represents a promising strategy for inferring networks with high positive predictive value under the constraint of small numbers of samples, meeting a need that will only continue to grow as more high-throughput studies are applied to complex model systems.

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

PubMed Central

Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals’ daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient. PMID:28076375

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.

PubMed

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient.

Delimiting cryptic pathogen species causing apple Valsa canker with multilocus data

PubMed Central

Wang, Xuli; Zang, Rui; Yin, Zhiyuan; Kang, Zhensheng; Huang, Lili

2014-01-01

Fungal diseases are posing tremendous threats to global economy and food safety. Among them, Valsa canker, caused by fungi of Valsa and their Cytospora anamorphs, has been a serious threat to fruit and forest trees and is one of the most destructive diseases of apple in East Asia, particularly. Accurate and robust delimitation of pathogen species is not only essential for the development of effective disease control programs, but also will advance our understanding of the emergence of plant diseases. However, species delimitation is especially difficult in Valsa because of the high variability of morphological traits and in many cases the lack of the teleomorph. In this study, we delimitated species boundary for pathogens causing apple Valsa canker with a multifaceted approach. Based on three independent loci, the internal transcribed spacer (ITS), β-tubulin (Btu), and translation elongation factor-1 alpha (EF1α), we inferred gene trees with both maximum likelihood and Bayesian methods, estimated species tree with Bayesian multispecies coalescent approaches, and validated species tree with Bayesian species delimitation. Through divergence time estimation and ancestral host reconstruction, we tested the possible underlying mechanisms for fungal speciation and host-range change. Our results proved that two varieties of the former morphological species V. mali represented two distinct species, V. mali and V. pyri, which diverged about 5 million years ago, much later than the divergence of their preferred hosts, excluding a scenario of fungi–host co-speciation. The marked different thermal preferences and contrasting pathogenicity in cross-inoculation suggest ecological divergences between the two species. Apple was the most likely ancestral host for both V. mali and V. pyri. Host-range expansion led to the occurrence of V. pyri on both pear and apple. Our results also represent an example in which ITS data might underestimate species diversity. PMID:24834333

Bayesian truthing as experimental verification of C4ISR sensors

NASA Astrophysics Data System (ADS)

Jannson, Tomasz; Forrester, Thomas; Romanov, Volodymyr; Wang, Wenjian; Nielsen, Thomas; Kostrzewski, Andrew

2015-05-01

In this paper, the general methodology for experimental verification/validation of C4ISR and other sensors' performance, is presented, based on Bayesian inference, in general, and binary sensors, in particular. This methodology, called Bayesian Truthing, defines Performance Metrics for binary sensors in: physics, optics, electronics, medicine, law enforcement, C3ISR, QC, ATR (Automatic Target Recognition), terrorism related events, and many others. For Bayesian Truthing, the sensing medium itself is not what is truly important; it is how the decision process is affected.

Insights into plant water uptake from xylem-water isotope measurements in two tropical catchments with contrasting moisture conditions

USGS Publications Warehouse

Evaristo, Jaivime; McDonnell, Jeffrey J.; Scholl, Martha A.; Bruijnzeel, L. Adrian; Chun, Kwok P.

2016-01-01

Water transpired by trees has long been assumed to be sourced from the same subsurface water stocks that contribute to groundwater recharge and streamflow. However, recent investigations using dual water stable isotopes have shown an apparent ecohydrological separation between tree-transpired water and stream water. Here we present evidence for such ecohydrological separation in two tropical environments in Puerto Rico where precipitation seasonality is relatively low and where precipitation is positively correlated with primary productivity. We determined the stable isotope signature of xylem water of 30 mahogany (Swietenia spp.) trees sampled during two periods with contrasting moisture status. Our results suggest that the separation between transpiration water and groundwater recharge/streamflow water might be related less to the temporal phasing of hydrologic inputs and primary productivity, and more to the fundamental processes that drive evaporative isotopic enrichment of residual soil water within the soil matrix. The lack of an evaporative signature of both groundwater and streams in the study area suggests that these water balance components have a water source that is transported quickly to deeper subsurface storage compared to waters that trees use. A Bayesian mixing model used to partition source water proportions of xylem water showed that groundwater contribution was greater for valley-bottom, riparian trees than for ridge-top trees. Groundwater contribution was also greater at the xeric site than at the mesic–hydric site. These model results (1) underline the utility of a simple linear mixing model, implemented in a Bayesian inference framework, in quantifying source water contributions at sites with contrasting physiographic characteristics, and (2) highlight the informed judgement that should be made in interpreting mixing model results, of import particularly in surveying groundwater use patterns by vegetation from regional to global scales. 

Towards a formal genealogical classification of the Lezgian languages (North Caucasus): testing various phylogenetic methods on lexical data.

PubMed

Kassian, Alexei

2015-01-01

A lexicostatistical classification is proposed for 20 languages and dialects of the Lezgian group of the North Caucasian family, based on meticulously compiled 110-item wordlists, published as part of the Global Lexicostatistical Database project. The lexical data have been subsequently analyzed with the aid of the principal phylogenetic methods, both distance-based and character-based: Starling neighbor joining (StarlingNJ), Neighbor joining (NJ), Unweighted pair group method with arithmetic mean (UPGMA), Bayesian Markov chain Monte Carlo (MCMC), Unweighted maximum parsimony (UMP). Cognation indexes within the input matrix were marked by two different algorithms: traditional etymological approach and phonetic similarity, i.e., the automatic method of consonant classes (Levenshtein distances). Due to certain reasons (first of all, high lexicographic quality of the wordlists and a consensus about the Lezgian phylogeny among Caucasologists), the Lezgian database is a perfect testing area for appraisal of phylogenetic methods. For the etymology-based input matrix, all the phylogenetic methods, with the possible exception of UMP, have yielded trees that are sufficiently compatible with each other to generate a consensus phylogenetic tree of the Lezgian lects. The obtained consensus tree agrees with the traditional expert classification as well as some of the previously proposed formal classifications of this linguistic group. Contrary to theoretical expectations, the UMP method has suggested the least plausible tree of all. In the case of the phonetic similarity-based input matrix, the distance-based methods (StarlingNJ, NJ, UPGMA) have produced the trees that are rather close to the consensus etymology-based tree and the traditional expert classification, whereas the character-based methods (Bayesian MCMC, UMP) have yielded less likely topologies.

Towards a Formal Genealogical Classification of the Lezgian Languages (North Caucasus): Testing Various Phylogenetic Methods on Lexical Data

PubMed Central

Kassian, Alexei

2015-01-01

A lexicostatistical classification is proposed for 20 languages and dialects of the Lezgian group of the North Caucasian family, based on meticulously compiled 110-item wordlists, published as part of the Global Lexicostatistical Database project. The lexical data have been subsequently analyzed with the aid of the principal phylogenetic methods, both distance-based and character-based: Starling neighbor joining (StarlingNJ), Neighbor joining (NJ), Unweighted pair group method with arithmetic mean (UPGMA), Bayesian Markov chain Monte Carlo (MCMC), Unweighted maximum parsimony (UMP). Cognation indexes within the input matrix were marked by two different algorithms: traditional etymological approach and phonetic similarity, i.e., the automatic method of consonant classes (Levenshtein distances). Due to certain reasons (first of all, high lexicographic quality of the wordlists and a consensus about the Lezgian phylogeny among Caucasologists), the Lezgian database is a perfect testing area for appraisal of phylogenetic methods. For the etymology-based input matrix, all the phylogenetic methods, with the possible exception of UMP, have yielded trees that are sufficiently compatible with each other to generate a consensus phylogenetic tree of the Lezgian lects. The obtained consensus tree agrees with the traditional expert classification as well as some of the previously proposed formal classifications of this linguistic group. Contrary to theoretical expectations, the UMP method has suggested the least plausible tree of all. In the case of the phonetic similarity-based input matrix, the distance-based methods (StarlingNJ, NJ, UPGMA) have produced the trees that are rather close to the consensus etymology-based tree and the traditional expert classification, whereas the character-based methods (Bayesian MCMC, UMP) have yielded less likely topologies. PMID:25719456

Modeling the survival kinetics of Salmonella in tree nuts for use in risk assessment.

PubMed

Santillana Farakos, Sofia M; Pouillot, Régis; Anderson, Nathan; Johnson, Rhoma; Son, Insook; Van Doren, Jane

2016-06-16

Salmonella has been shown to survive in tree nuts over long periods of time. This survival capacity and its variability are key elements for risk assessment of Salmonella in tree nuts. The aim of this study was to develop a mathematical model to predict survival of Salmonella in tree nuts at ambient storage temperatures that considers variability and uncertainty separately and can easily be incorporated into a risk assessment model. Data on Salmonella survival on raw almonds, pecans, pistachios and walnuts were collected from the peer reviewed literature. The Weibull model was chosen as the baseline model and various fixed effect and mixed effect models were fit to the data. The best model identified through statistical analysis testing was then used to develop a hierarchical Bayesian model. Salmonella in tree nuts showed slow declines at temperatures ranging from 21°C to 24°C. A high degree of variability in survival was observed across tree nut studies reported in the literature. Statistical analysis results indicated that the best applicable model was a mixed effect model that included a fixed and random variation of δ per tree nut (which is the time it takes for the first log10 reduction) and a fixed variation of ρ per tree nut (parameter which defines the shape of the curve). Higher estimated survival rates (δ) were obtained for Salmonella on pistachios, followed in decreasing order by pecans, almonds and walnuts. The posterior distributions obtained from Bayesian inference were used to estimate the variability in the log10 decrease levels in survival for each tree nut, and the uncertainty of these estimates. These modeled uncertainty and variability distributions of the estimates can be used to obtain a complete exposure assessment of Salmonella in tree nuts when including time-temperature parameters for storage and consumption data. The statistical approach presented in this study may be applied to any studies that aim to develop predictive models to be implemented in a probabilistic exposure assessment or a quantitative microbial risk assessment. Published by Elsevier B.V.

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

Variable Discretisation for Anomaly Detection using Bayesian Networks

DTIC Science & Technology

2017-01-01

UNCLASSIFIED DST- Group –TR–3328 1 Introduction Bayesian network implementations usually require each variable to take on a finite number of mutually...UNCLASSIFIED Variable Discretisation for Anomaly Detection using Bayesian Networks Jonathan Legg National Security and ISR Division Defence Science...and Technology Group DST- Group –TR–3328 ABSTRACT Anomaly detection is the process by which low probability events are automatically found against a

The evolutionary host switches of Polychromophilus: a multi-gene phylogeny of the bat malaria genus suggests a second invasion of mammals by a haemosporidian parasite

PubMed Central

2012-01-01

Background The majority of Haemosporida species infect birds or reptiles, but many important genera, including Plasmodium, infect mammals. Dipteran vectors shared by avian, reptilian and mammalian Haemosporida, suggest multiple invasions of Mammalia during haemosporidian evolution; yet, phylogenetic analyses have detected only a single invasion event. Until now, several important mammal-infecting genera have been absent in these analyses. This study focuses on the evolutionary origin of Polychromophilus, a unique malaria genus that only infects bats (Microchiroptera) and is transmitted by bat flies (Nycteribiidae). Methods Two species of Polychromophilus were obtained from wild bats caught in Switzerland. These were molecularly characterized using four genes (asl, clpc, coI, cytb) from the three different genomes (nucleus, apicoplast, mitochondrion). These data were then combined with data of 60 taxa of Haemosporida available in GenBank. Bayesian inference, maximum likelihood and a range of rooting methods were used to test specific hypotheses concerning the phylogenetic relationships between Polychromophilus and the other haemosporidian genera. Results The Polychromophilus melanipherus and Polychromophilus murinus samples show genetically distinct patterns and group according to species. The Bayesian tree topology suggests that the monophyletic clade of Polychromophilus falls within the avian/saurian clade of Plasmodium and directed hypothesis testing confirms the Plasmodium origin. Conclusion Polychromophilus' ancestor was most likely a bird- or reptile-infecting Plasmodium before it switched to bats. The invasion of mammals as hosts has, therefore, not been a unique event in the evolutionary history of Haemosporida, despite the suspected costs of adapting to a new host. This was, moreover, accompanied by a switch in dipteran host. PMID:22356874

Treetrimmer: a method for phylogenetic dataset size reduction.

PubMed

Maruyama, Shinichiro; Eveleigh, Robert J M; Archibald, John M

2013-04-12

With rapid advances in genome sequencing and bioinformatics, it is now possible to generate phylogenetic trees containing thousands of operational taxonomic units (OTUs) from a wide range of organisms. However, use of rigorous tree-building methods on such large datasets is prohibitive and manual 'pruning' of sequence alignments is time consuming and raises concerns over reproducibility. There is a need for bioinformatic tools with which to objectively carry out such pruning procedures. Here we present 'TreeTrimmer', a bioinformatics procedure that removes unnecessary redundancy in large phylogenetic datasets, alleviating the size effect on more rigorous downstream analyses. The method identifies and removes user-defined 'redundant' sequences, e.g., orthologous sequences from closely related organisms and 'recently' evolved lineage-specific paralogs. Representative OTUs are retained for more rigorous re-analysis. TreeTrimmer reduces the OTU density of phylogenetic trees without sacrificing taxonomic diversity while retaining the original tree topology, thereby speeding up downstream computer-intensive analyses, e.g., Bayesian and maximum likelihood tree reconstructions, in a reproducible fashion.

BN-FLEMOps pluvial - A probabilistic multi-variable loss estimation model for pluvial floods

NASA Astrophysics Data System (ADS)

Roezer, V.; Kreibich, H.; Schroeter, K.; Doss-Gollin, J.; Lall, U.; Merz, B.

2017-12-01

Pluvial flood events, such as in Copenhagen (Denmark) in 2011, Beijing (China) in 2012 or Houston (USA) in 2016, have caused severe losses to urban dwellings in recent years. These floods are caused by storm events with high rainfall rates well above the design levels of urban drainage systems, which lead to inundation of streets and buildings. A projected increase in frequency and intensity of heavy rainfall events in many areas and an ongoing urbanization may increase pluvial flood losses in the future. For an efficient risk assessment and adaptation to pluvial floods, a quantification of the flood risk is needed. Few loss models have been developed particularly for pluvial floods. These models usually use simple waterlevel- or rainfall-loss functions and come with very high uncertainties. To account for these uncertainties and improve the loss estimation, we present a probabilistic multi-variable loss estimation model for pluvial floods based on empirical data. The model was developed in a two-step process using a machine learning approach and a comprehensive database comprising 783 records of direct building and content damage of private households. The data was gathered through surveys after four different pluvial flood events in Germany between 2005 and 2014. In a first step, linear and non-linear machine learning algorithms, such as tree-based and penalized regression models were used to identify the most important loss influencing factors among a set of 55 candidate variables. These variables comprise hydrological and hydraulic aspects, early warning, precaution, building characteristics and the socio-economic status of the household. In a second step, the most important loss influencing variables were used to derive a probabilistic multi-variable pluvial flood loss estimation model based on Bayesian Networks. Two different networks were tested: a score-based network learned from the data and a network based on expert knowledge. Loss predictions are made through Bayesian inference using Markov chain Monte Carlo (MCMC) sampling. With the ability to cope with incomplete information and use expert knowledge, as well as inherently providing quantitative uncertainty information, it is shown that loss models based on BNs are superior to deterministic approaches for pluvial flood risk assessment.

A new prior for bayesian anomaly detection: application to biosurveillance.

PubMed

Shen, Y; Cooper, G F

2010-01-01

Bayesian anomaly detection computes posterior probabilities of anomalous events by combining prior beliefs and evidence from data. However, the specification of prior probabilities can be challenging. This paper describes a Bayesian prior in the context of disease outbreak detection. The goal is to provide a meaningful, easy-to-use prior that yields a posterior probability of an outbreak that performs at least as well as a standard frequentist approach. If this goal is achieved, the resulting posterior could be usefully incorporated into a decision analysis about how to act in light of a possible disease outbreak. This paper describes a Bayesian method for anomaly detection that combines learning from data with a semi-informative prior probability over patterns of anomalous events. A univariate version of the algorithm is presented here for ease of illustration of the essential ideas. The paper describes the algorithm in the context of disease-outbreak detection, but it is general and can be used in other anomaly detection applications. For this application, the semi-informative prior specifies that an increased count over baseline is expected for the variable being monitored, such as the number of respiratory chief complaints per day at a given emergency department. The semi-informative prior is derived based on the baseline prior, which is estimated from using historical data. The evaluation reported here used semi-synthetic data to evaluate the detection performance of the proposed Bayesian method and a control chart method, which is a standard frequentist algorithm that is closest to the Bayesian method in terms of the type of data it uses. The disease-outbreak detection performance of the Bayesian method was statistically significantly better than that of the control chart method when proper baseline periods were used to estimate the baseline behavior to avoid seasonal effects. When using longer baseline periods, the Bayesian method performed as well as the control chart method. The time complexity of the Bayesian algorithm is linear in the number of the observed events being monitored, due to a novel, closed-form derivation that is introduced in the paper. This paper introduces a novel prior probability for Bayesian outbreak detection that is expressive, easy-to-apply, computationally efficient, and performs as well or better than a standard frequentist method.

The evolutionary relationships and age of Homo naledi: An assessment using dated Bayesian phylogenetic methods.

PubMed

Dembo, Mana; Radovčić, Davorka; Garvin, Heather M; Laird, Myra F; Schroeder, Lauren; Scott, Jill E; Brophy, Juliet; Ackermann, Rebecca R; Musiba, Chares M; de Ruiter, Darryl J; Mooers, Arne Ø; Collard, Mark

2016-08-01

Homo naledi is a recently discovered species of fossil hominin from South Africa. A considerable amount is already known about H. naledi but some important questions remain unanswered. Here we report a study that addressed two of them: "Where does H. naledi fit in the hominin evolutionary tree?" and "How old is it?" We used a large supermatrix of craniodental characters for both early and late hominin species and Bayesian phylogenetic techniques to carry out three analyses. First, we performed a dated Bayesian analysis to generate estimates of the evolutionary relationships of fossil hominins including H. naledi. Then we employed Bayes factor tests to compare the strength of support for hypotheses about the relationships of H. naledi suggested by the best-estimate trees. Lastly, we carried out a resampling analysis to assess the accuracy of the age estimate for H. naledi yielded by the dated Bayesian analysis. The analyses strongly supported the hypothesis that H. naledi forms a clade with the other Homo species and Australopithecus sediba. The analyses were more ambiguous regarding the position of H. naledi within the (Homo, Au. sediba) clade. A number of hypotheses were rejected, but several others were not. Based on the available craniodental data, Homo antecessor, Asian Homo erectus, Homo habilis, Homo floresiensis, Homo sapiens, and Au. sediba could all be the sister taxon of H. naledi. According to the dated Bayesian analysis, the most likely age for H. naledi is 912 ka. This age estimate was supported by the resampling analysis. Our findings have a number of implications. Most notably, they support the assignment of the new specimens to Homo, cast doubt on the claim that H. naledi is simply a variant of H. erectus, and suggest H. naledi is younger than has been previously proposed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Phylogenetic relationships of Malaysia’s long-tailed macaques, Macaca fascicularis, based on cytochrome b sequences

PubMed Central

Abdul-Latiff, Muhammad Abu Bakar; Ruslin, Farhani; Fui, Vun Vui; Abu, Mohd-Hashim; Rovie-Ryan, Jeffrine Japning; Abdul-Patah, Pazil; Lakim, Maklarin; Roos, Christian; Yaakop, Salmah; Md-Zain, Badrul Munir

2014-01-01

Abstract Phylogenetic relationships among Malaysia’s long-tailed macaques have yet to be established, despite abundant genetic studies of the species worldwide. The aims of this study are to examine the phylogenetic relationships of Macaca fascicularis in Malaysia and to test its classification as a morphological subspecies. A total of 25 genetic samples of M. fascicularis yielding 383 bp of Cytochrome b (Cyt b) sequences were used in phylogenetic analysis along with one sample each of M. nemestrina and M. arctoides used as outgroups. Sequence character analysis reveals that Cyt b locus is a highly conserved region with only 23% parsimony informative character detected among ingroups. Further analysis indicates a clear separation between populations originating from different regions; the Malay Peninsula versus Borneo Insular, the East Coast versus West Coast of the Malay Peninsula, and the island versus mainland Malay Peninsula populations. Phylogenetic trees (NJ, MP and Bayesian) portray a consistent clustering paradigm as Borneo’s population was distinguished from Peninsula’s population (99% and 100% bootstrap value in NJ and MP respectively and 1.00 posterior probability in Bayesian trees). The East coast population was separated from other Peninsula populations (64% in NJ, 66% in MP and 0.53 posterior probability in Bayesian). West coast populations were divided into 2 clades: the North-South (47%/54% in NJ, 26/26% in MP and 1.00/0.80 posterior probability in Bayesian) and Island-Mainland (93% in NJ, 90% in MP and 1.00 posterior probability in Bayesian). The results confirm the previous morphological assignment of 2 subspecies, M. f. fascicularis and M. f. argentimembris, in the Malay Peninsula. These populations should be treated as separate genetic entities in order to conserve the genetic diversity of Malaysia’s M. fascicularis. These findings are crucial in aiding the conservation management and translocation process of M. fascicularis populations in Malaysia. PMID:24899832

Phylogenetic relationships of Malaysia's long-tailed macaques, Macaca fascicularis, based on cytochrome b sequences.

PubMed

Abdul-Latiff, Muhammad Abu Bakar; Ruslin, Farhani; Fui, Vun Vui; Abu, Mohd-Hashim; Rovie-Ryan, Jeffrine Japning; Abdul-Patah, Pazil; Lakim, Maklarin; Roos, Christian; Yaakop, Salmah; Md-Zain, Badrul Munir

2014-01-01

Phylogenetic relationships among Malaysia's long-tailed macaques have yet to be established, despite abundant genetic studies of the species worldwide. The aims of this study are to examine the phylogenetic relationships of Macaca fascicularis in Malaysia and to test its classification as a morphological subspecies. A total of 25 genetic samples of M. fascicularis yielding 383 bp of Cytochrome b (Cyt b) sequences were used in phylogenetic analysis along with one sample each of M. nemestrina and M. arctoides used as outgroups. Sequence character analysis reveals that Cyt b locus is a highly conserved region with only 23% parsimony informative character detected among ingroups. Further analysis indicates a clear separation between populations originating from different regions; the Malay Peninsula versus Borneo Insular, the East Coast versus West Coast of the Malay Peninsula, and the island versus mainland Malay Peninsula populations. Phylogenetic trees (NJ, MP and Bayesian) portray a consistent clustering paradigm as Borneo's population was distinguished from Peninsula's population (99% and 100% bootstrap value in NJ and MP respectively and 1.00 posterior probability in Bayesian trees). The East coast population was separated from other Peninsula populations (64% in NJ, 66% in MP and 0.53 posterior probability in Bayesian). West coast populations were divided into 2 clades: the North-South (47%/54% in NJ, 26/26% in MP and 1.00/0.80 posterior probability in Bayesian) and Island-Mainland (93% in NJ, 90% in MP and 1.00 posterior probability in Bayesian). The results confirm the previous morphological assignment of 2 subspecies, M. f. fascicularis and M. f. argentimembris, in the Malay Peninsula. These populations should be treated as separate genetic entities in order to conserve the genetic diversity of Malaysia's M. fascicularis. These findings are crucial in aiding the conservation management and translocation process of M. fascicularis populations in Malaysia.

Direct evaluation of fault trees using object-oriented programming techniques

NASA Technical Reports Server (NTRS)

Patterson-Hine, F. A.; Koen, B. V.

1989-01-01

Object-oriented programming techniques are used in an algorithm for the direct evaluation of fault trees. The algorithm combines a simple bottom-up procedure for trees without repeated events with a top-down recursive procedure for trees with repeated events. The object-oriented approach results in a dynamic modularization of the tree at each step in the reduction process. The algorithm reduces the number of recursive calls required to solve trees with repeated events and calculates intermediate results as well as the solution of the top event. The intermediate results can be reused if part of the tree is modified. An example is presented in which the results of the algorithm implemented with conventional techniques are compared to those of the object-oriented approach.

Waveform-based Bayesian full moment tensor inversion and uncertainty determination for the induced seismicity in an oil/gas field

NASA Astrophysics Data System (ADS)

Gu, Chen; Marzouk, Youssef M.; Toksöz, M. Nafi

2018-03-01

Small earthquakes occur due to natural tectonic motions and are induced by oil and gas production processes. In many oil/gas fields and hydrofracking processes, induced earthquakes result from fluid extraction or injection. The locations and source mechanisms of these earthquakes provide valuable information about the reservoirs. Analysis of induced seismic events has mostly assumed a double-couple source mechanism. However, recent studies have shown a non-negligible percentage of non-double-couple components of source moment tensors in hydraulic fracturing events, assuming a full moment tensor source mechanism. Without uncertainty quantification of the moment tensor solution, it is difficult to determine the reliability of these source models. This study develops a Bayesian method to perform waveform-based full moment tensor inversion and uncertainty quantification for induced seismic events, accounting for both location and velocity model uncertainties. We conduct tests with synthetic events to validate the method, and then apply our newly developed Bayesian inversion approach to real induced seismicity in an oil/gas field in the sultanate of Oman—determining the uncertainties in the source mechanism and in the location of that event.

Predicting Tree Mortality Die-off Events Associated with Hotter Drought and Assessing Their Global Consequences via Ecoclimate Teleconnections.

NASA Astrophysics Data System (ADS)

Breshears, D. D.; Allen, C. D.; McDowell, N. G.; Adams, H. D.; Barnes, M.; Barron-Gafford, G.; Bradford, J. B.; Cobb, N.; Field, J. P.; Froend, R.; Fontaine, J. B.; Garcia, E.; Hardy, G. E. S. J.; Huxman, T. E.; Kala, J.; Lague, M. M.; Martinez-Yrizar, A.; Matusick, G.; Minor, D. M.; Moore, D. J.; Ng, M.; Ruthrof, K. X.; Saleska, S. R.; Stark, S. C.; Swann, A. L. S.; Villegas, J. C.; Williams, A. P.; Zou, C.

2017-12-01

Evidence that tree mortality is increasingly likely occur in extensive die-off events across the terrestrial biosphere continues to mount. The consequences of such extensive mortality events are potentially profound, not only for the locations where die-off events occur, but also for other locations that could be impacted via ecoclimate teleconnections, whereby the land surface changes associated with die-off in one location could alter atmospheric circulation patterns and affect vegetation elsewhere. Here, we (1) recap the background of tree mortality as an emerging environmental issue, (2) highlight recent advances that could help us improve predictions of the vulnerability to tree mortality, including the underlying importance of hydraulic failure, the potential to develop climatic envelopes specific to tree mortality events, and consideration of the role of heat waves; and (3) initial bounding simulations that indicate the potential for tree die-off events in different locations to alter ecoclimate teleconnections. As we move toward globally coordinated carbon accounting and management, the high vulnerability to tree die-off events and the potential for such events to affect vegetation elsewhere will both need to be accounted for.

Non-monophyly and intricate morphological evolution within the avian family Cettiidae revealed by multilocus analysis of a taxonomically densely sampled dataset

PubMed Central

2011-01-01

Background The avian family Cettiidae, including the genera Cettia, Urosphena, Tesia, Abroscopus and Tickellia and Orthotomus cucullatus, has recently been proposed based on analysis of a small number of loci and species. The close relationship of most of these taxa was unexpected, and called for a comprehensive study based on multiple loci and dense taxon sampling. In the present study, we infer the relationships of all except one of the species in this family using one mitochondrial and three nuclear loci. We use traditional gene tree methods (Bayesian inference, maximum likelihood bootstrapping, parsimony bootstrapping), as well as a recently developed Bayesian species tree approach (*BEAST) that accounts for lineage sorting processes that might produce discordance between gene trees. We also analyse mitochondrial DNA for a larger sample, comprising multiple individuals and a large number of subspecies of polytypic species. Results There are many topological incongruences among the single-locus trees, although none of these is strongly supported. The multi-locus tree inferred using concatenated sequences and the species tree agree well with each other, and are overall well resolved and well supported by the data. The main discrepancy between these trees concerns the most basal split. Both methods infer the genus Cettia to be highly non-monophyletic, as it is scattered across the entire family tree. Deep intraspecific divergences are revealed, and one or two species and one subspecies are inferred to be non-monophyletic (differences between methods). Conclusions The molecular phylogeny presented here is strongly inconsistent with the traditional, morphology-based classification. The remarkably high degree of non-monophyly in the genus Cettia is likely to be one of the most extraordinary examples of misconceived relationships in an avian genus. The phylogeny suggests instances of parallel evolution, as well as highly unequal rates of morphological divergence in different lineages. This complex morphological evolution apparently misled earlier taxonomists. These results underscore the well-known but still often neglected problem of basing classifications on overall morphological similarity. Based on the molecular data, a revised taxonomy is proposed. Although the traditional and species tree methods inferred much the same tree in the present study, the assumption by species tree methods that all species are monophyletic is a limitation in these methods, as some currently recognized species might have more complex histories. PMID:22142197

Under which conditions, additional monitoring data are worth gathering for improving decision making? Application of the VOI theory in the Bayesian Event Tree eruption forecasting framework

NASA Astrophysics Data System (ADS)

Loschetter, Annick; Rohmer, Jérémy

2016-04-01

Standard and new generation of monitoring observations provide in almost real-time important information about the evolution of the volcanic system. These observations are used to update the model and contribute to a better hazard assessment and to support decision making concerning potential evacuation. The framework BET_EF (based on Bayesian Event Tree) developed by INGV enables dealing with the integration of information from monitoring with the prospect of decision making. Using this framework, the objectives of the present work are i. to propose a method to assess the added value of information (within the Value Of Information (VOI) theory) from monitoring; ii. to perform sensitivity analysis on the different parameters that influence the VOI from monitoring. VOI consists in assessing the possible increase in expected value provided by gathering information, for instance through monitoring. Basically, the VOI is the difference between the value with information and the value without additional information in a Cost-Benefit approach. This theory is well suited to deal with situations that can be represented in the form of a decision tree such as the BET_EF tool. Reference values and ranges of variation (for sensitivity analysis) were defined for input parameters, based on data from the MESIMEX exercise (performed at Vesuvio volcano in 2006). Complementary methods for sensitivity analyses were implemented: local, global using Sobol' indices and regional using Contribution to Sample Mean and Variance plots. The results (specific to the case considered) obtained with the different techniques are in good agreement and enable answering the following questions: i. Which characteristics of monitoring are important for early warning (reliability)? ii. How do experts' opinions influence the hazard assessment and thus the decision? Concerning the characteristics of monitoring, the more influent parameters are the means rather than the variances for the case considered. For the parameters that concern expert setting, the weight attributed to monitoring measurement ω, the mean of thresholds, the economic context and the setting of the decision threshold are very influential. The interest of applying the VOI theory (more precisely the value of imperfect information) in the BET framework was demonstrated as support for helping experts in the setting of the monitoring system or for helping managers to decide the installation of additional monitoring systems. Acknowledgments: This work was carried out in the framework of the project MEDSUV. This project is funded under the call FP7 ENV.2012.6.4-2: Long-term monitoring experiment in geologically active regions of Europe prone to natural hazards: the Supersite concept. Grant agreement n°308665.

Bayesian network modelling of upper gastrointestinal bleeding

NASA Astrophysics Data System (ADS)

Aisha, Nazziwa; Shohaimi, Shamarina; Adam, Mohd Bakri

2013-09-01

Bayesian networks are graphical probabilistic models that represent causal and other relationships between domain variables. In the context of medical decision making, these models have been explored to help in medical diagnosis and prognosis. In this paper, we discuss the Bayesian network formalism in building medical support systems and we learn a tree augmented naive Bayes Network (TAN) from gastrointestinal bleeding data. The accuracy of the TAN in classifying the source of gastrointestinal bleeding into upper or lower source is obtained. The TAN achieves a high classification accuracy of 86% and an area under curve of 92%. A sensitivity analysis of the model shows relatively high levels of entropy reduction for color of the stool, history of gastrointestinal bleeding, consistency and the ratio of blood urea nitrogen to creatinine. The TAN facilitates the identification of the source of GIB and requires further validation.

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specifically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. (See CASI ID 20100021910 for supplemental data disk.)

Unraveling the rapid radiation of crested newts (Triturus cristatus superspecies) using complete mitogenomic sequences.

PubMed

Wielstra, Ben; Arntzen, Jan W

2011-06-14

The rapid radiation of crested newts (Triturus cristatus superspecies) comprises four morphotypes: 1) the T. karelinii group, 2) T. carnifex - T. macedonicus, 3) T. cristatus and 4) T. dobrogicus. These vary in body build and the number of rib-bearing pre-sacral vertebrae (NRBV). The phylogenetic relationships of the morphotypes have not yet been settled, despite several previous attempts, employing a variety of molecular markers. We here resolve the crested newt phylogeny by using complete mitochondrial genome sequences. Bayesian inference based on the mitogenomic data yields a fully bifurcating, significantly supported tree, though Maximum Likelihood inference yields low support values. The internal branches connecting the morphotypes are short relative to the terminal branches. Seen from the root of Triturus (NRBV = 13), a basal dichotomy separates the T. karelinii group (NRBV = 13) from the remaining crested newts. The next split divides the latter assortment into T. carnifex - T. macedonicus (NRBV = 14) versus T. cristatus (NRBV = 15) and T. dobrogicus (NRBV = 16 or 17). We argue that the Bayesian full mitochondrial DNA phylogeny is superior to previous attempts aiming to recover the crested newt species tree. Furthermore, our new phylogeny involves a maximally parsimonious interpretation of NRBV evolution. Calibrating the phylogeny allows us to evaluate potential drivers for crested newt cladogenesis. The split between the T. karelinii group and the three other morphotypes, at ca. 10.4 Ma, is associated with the separation of the Balkan and Anatolian landmasses (12-9 Ma). No currently known vicariant events can be ascribed to the other two splits, first at ca. 9.3 Ma, separating T. carnifex - T. macedonicus, and second at ca. 8.8 Ma, splitting T. cristatus and T. dobrogicus. The crested newt morphotypes differ in the duration of their annual aquatic period. We speculate on the role that this ecological differentiation could have played during speciation.

Rather than by direct acquisition via lateral gene transfer, GHF5 cellulases were passed on from early Pratylenchidae to root-knot and cyst nematodes.

PubMed

Rybarczyk-Mydłowska, Katarzyna; Maboreke, Hazel Ruvimbo; van Megen, Hanny; van den Elsen, Sven; Mooyman, Paul; Smant, Geert; Bakker, Jaap; Helder, Johannes

2012-11-21

Plant parasitic nematodes are unusual Metazoans as they are equipped with genes that allow for symbiont-independent degradation of plant cell walls. Among the cell wall-degrading enzymes, glycoside hydrolase family 5 (GHF5) cellulases are relatively well characterized, especially for high impact parasites such as root-knot and cyst nematodes. Interestingly, ancestors of extant nematodes most likely acquired these GHF5 cellulases from a prokaryote donor by one or multiple lateral gene transfer events. To obtain insight into the origin of GHF5 cellulases among evolutionary advanced members of the order Tylenchida, cellulase biodiversity data from less distal family members were collected and analyzed. Single nematodes were used to obtain (partial) genomic sequences of cellulases from representatives of the genera Meloidogyne, Pratylenchus, Hirschmanniella and Globodera. Combined Bayesian analysis of ≈ 100 cellulase sequences revealed three types of catalytic domains (A, B, and C). Represented by 84 sequences, type B is numerically dominant, and the overall topology of the catalytic domain type shows remarkable resemblance with trees based on neutral (= pathogenicity-unrelated) small subunit ribosomal DNA sequences. Bayesian analysis further suggested a sister relationship between the lesion nematode Pratylenchus thornei and all type B cellulases from root-knot nematodes. Yet, the relationship between the three catalytic domain types remained unclear. Superposition of intron data onto the cellulase tree suggests that types B and C are related, and together distinct from type A that is characterized by two unique introns. All Tylenchida members investigated here harbored one or multiple GHF5 cellulases. Three types of catalytic domains are distinguished, and the presence of at least two types is relatively common among plant parasitic Tylenchida. Analysis of coding sequences of cellulases suggests that root-knot and cyst nematodes did not acquire this gene directly by lateral genes transfer. More likely, these genes were passed on by ancestors of a family nowadays known as the Pratylenchidae.

Bayesian Statistical Inference in Ion-Channel Models with Exact Missed Event Correction.

PubMed

Epstein, Michael; Calderhead, Ben; Girolami, Mark A; Sivilotti, Lucia G

2016-07-26

The stochastic behavior of single ion channels is most often described as an aggregated continuous-time Markov process with discrete states. For ligand-gated channels each state can represent a different conformation of the channel protein or a different number of bound ligands. Single-channel recordings show only whether the channel is open or shut: states of equal conductance are aggregated, so transitions between them have to be inferred indirectly. The requirement to filter noise from the raw signal further complicates the modeling process, as it limits the time resolution of the data. The consequence of the reduced bandwidth is that openings or shuttings that are shorter than the resolution cannot be observed; these are known as missed events. Postulated models fitted using filtered data must therefore explicitly account for missed events to avoid bias in the estimation of rate parameters and therefore assess parameter identifiability accurately. In this article, we present the first, to our knowledge, Bayesian modeling of ion-channels with exact missed events correction. Bayesian analysis represents uncertain knowledge of the true value of model parameters by considering these parameters as random variables. This allows us to gain a full appreciation of parameter identifiability and uncertainty when estimating values for model parameters. However, Bayesian inference is particularly challenging in this context as the correction for missed events increases the computational complexity of the model likelihood. Nonetheless, we successfully implemented a two-step Markov chain Monte Carlo method that we called "BICME", which performs Bayesian inference in models of realistic complexity. The method is demonstrated on synthetic and real single-channel data from muscle nicotinic acetylcholine channels. We show that parameter uncertainty can be characterized more accurately than with maximum-likelihood methods. Our code for performing inference in these ion channel models is publicly available. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Bayesian Approach for Flexible Modeling of Semicompeting Risks Data

PubMed Central

Han, Baoguang; Yu, Menggang; Dignam, James J.; Rathouz, Paul J.

2016-01-01

Summary Semicompeting risks data arise when two types of events, non-terminal and terminal, are observed. When the terminal event occurs first, it censors the non-terminal event, but not vice versa. To account for possible dependent censoring of the non-terminal event by the terminal event and to improve prediction of the terminal event using the non-terminal event information, it is crucial to model their association properly. Motivated by a breast cancer clinical trial data analysis, we extend the well-known illness-death models to allow flexible random effects to capture heterogeneous association structures in the data. Our extension also represents a generalization of the popular shared frailty models that usually assume that the non-terminal event does not affect the hazards of the terminal event beyond a frailty term. We propose a unified Bayesian modeling approach that can utilize existing software packages for both model fitting and individual specific event prediction. The approach is demonstrated via both simulation studies and a breast cancer data set analysis. PMID:25274445

Low frequency full waveform seismic inversion within a tree based Bayesian framework

NASA Astrophysics Data System (ADS)

Ray, Anandaroop; Kaplan, Sam; Washbourne, John; Albertin, Uwe

2018-01-01

Limited illumination, insufficient offset, noisy data and poor starting models can pose challenges for seismic full waveform inversion. We present an application of a tree based Bayesian inversion scheme which attempts to mitigate these problems by accounting for data uncertainty while using a mildly informative prior about subsurface structure. We sample the resulting posterior model distribution of compressional velocity using a trans-dimensional (trans-D) or Reversible Jump Markov chain Monte Carlo method in the wavelet transform domain of velocity. This allows us to attain rapid convergence to a stationary distribution of posterior models while requiring a limited number of wavelet coefficients to define a sampled model. Two synthetic, low frequency, noisy data examples are provided. The first example is a simple reflection + transmission inverse problem, and the second uses a scaled version of the Marmousi velocity model, dominated by reflections. Both examples are initially started from a semi-infinite half-space with incorrect background velocity. We find that the trans-D tree based approach together with parallel tempering for navigating rugged likelihood (i.e. misfit) topography provides a promising, easily generalized method for solving large-scale geophysical inverse problems which are difficult to optimize, but where the true model contains a hierarchy of features at multiple scales.

Fitting models of continuous trait evolution to incompletely sampled comparative data using approximate Bayesian computation.

PubMed

Slater, Graham J; Harmon, Luke J; Wegmann, Daniel; Joyce, Paul; Revell, Liam J; Alfaro, Michael E

2012-03-01

In recent years, a suite of methods has been developed to fit multiple rate models to phylogenetic comparative data. However, most methods have limited utility at broad phylogenetic scales because they typically require complete sampling of both the tree and the associated phenotypic data. Here, we develop and implement a new, tree-based method called MECCA (Modeling Evolution of Continuous Characters using ABC) that uses a hybrid likelihood/approximate Bayesian computation (ABC)-Markov-Chain Monte Carlo approach to simultaneously infer rates of diversification and trait evolution from incompletely sampled phylogenies and trait data. We demonstrate via simulation that MECCA has considerable power to choose among single versus multiple evolutionary rate models, and thus can be used to test hypotheses about changes in the rate of trait evolution across an incomplete tree of life. We finally apply MECCA to an empirical example of body size evolution in carnivores, and show that there is no evidence for an elevated rate of body size evolution in the pinnipeds relative to terrestrial carnivores. ABC approaches can provide a useful alternative set of tools for future macroevolutionary studies where likelihood-dependent approaches are lacking. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Species Tree Inference Using a Mixture Model.

PubMed

Ullah, Ikram; Parviainen, Pekka; Lagergren, Jens

2015-09-01

Species tree reconstruction has been a subject of substantial research due to its central role across biology and medicine. A species tree is often reconstructed using a set of gene trees or by directly using sequence data. In either of these cases, one of the main confounding phenomena is the discordance between a species tree and a gene tree due to evolutionary events such as duplications and losses. Probabilistic methods can resolve the discordance by coestimating gene trees and the species tree but this approach poses a scalability problem for larger data sets. We present MixTreEM-DLRS: A two-phase approach for reconstructing a species tree in the presence of gene duplications and losses. In the first phase, MixTreEM, a novel structural expectation maximization algorithm based on a mixture model is used to reconstruct a set of candidate species trees, given sequence data for monocopy gene families from the genomes under study. In the second phase, PrIME-DLRS, a method based on the DLRS model (Åkerborg O, Sennblad B, Arvestad L, Lagergren J. 2009. Simultaneous Bayesian gene tree reconstruction and reconciliation analysis. Proc Natl Acad Sci U S A. 106(14):5714-5719), is used for selecting the best species tree. PrIME-DLRS can handle multicopy gene families since DLRS, apart from modeling sequence evolution, models gene duplication and loss using a gene evolution model (Arvestad L, Lagergren J, Sennblad B. 2009. The gene evolution model and computing its associated probabilities. J ACM. 56(2):1-44). We evaluate MixTreEM-DLRS using synthetic and biological data, and compare its performance with a recent genome-scale species tree reconstruction method PHYLDOG (Boussau B, Szöllősi GJ, Duret L, Gouy M, Tannier E, Daubin V. 2013. Genome-scale coestimation of species and gene trees. Genome Res. 23(2):323-330) as well as with a fast parsimony-based algorithm Duptree (Wehe A, Bansal MS, Burleigh JG, Eulenstein O. 2008. Duptree: a program for large-scale phylogenetic analyses using gene tree parsimony. Bioinformatics 24(13):1540-1541). Our method is competitive with PHYLDOG in terms of accuracy and runs significantly faster and our method outperforms Duptree in accuracy. The analysis constituted by MixTreEM without DLRS may also be used for selecting the target species tree, yielding a fast and yet accurate algorithm for larger data sets. MixTreEM is freely available at http://prime.scilifelab.se/mixtreem/. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

An introduction to using Bayesian linear regression with clinical data.

PubMed

Baldwin, Scott A; Larson, Michael J

2017-11-01

Statistical training psychology focuses on frequentist methods. Bayesian methods are an alternative to standard frequentist methods. This article provides researchers with an introduction to fundamental ideas in Bayesian modeling. We use data from an electroencephalogram (EEG) and anxiety study to illustrate Bayesian models. Specifically, the models examine the relationship between error-related negativity (ERN), a particular event-related potential, and trait anxiety. Methodological topics covered include: how to set up a regression model in a Bayesian framework, specifying priors, examining convergence of the model, visualizing and interpreting posterior distributions, interval estimates, expected and predicted values, and model comparison tools. We also discuss situations where Bayesian methods can outperform frequentist methods as well has how to specify more complicated regression models. Finally, we conclude with recommendations about reporting guidelines for those using Bayesian methods in their own research. We provide data and R code for replicating our analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Corrected placement of Mus-Rattus fossil calibration forces precision in the molecular tree of rodents.

PubMed

Kimura, Yuri; Hawkins, Melissa T R; McDonough, Molly M; Jacobs, Louis L; Flynn, Lawrence J

2015-09-28

Time calibration derived from the fossil record is essential for molecular phylogenetic and evolutionary studies. Fossil mice and rats, discovered in the Siwalik Group of Pakistan, have served as one of the best-known fossil calibration points in molecular phylogenic studies. Although these fossils have been widely used as the 12 Ma date for the Mus/Rattus split or a more basal split, conclusive paleontological evidence for the nodal assignments has been absent. This study analyzes newly recognized characters that demonstrate lineage separation in the fossil record of Siwalik murines and examines the most reasonable nodal placement of the diverging lineages in a molecular phylogenetic tree by ancestral state reconstruction. Our specimen-based approach strongly indicates that Siwalik murines of the Karnimata clade are fossil members of the Arvicanthini-Otomyini-Millardini clade, which excludes Rattus and its relatives. Combining the new interpretation with the widely accepted hypothesis that the Progonomys clade includes Mus, the lineage separation event in the Siwalik fossil record represents the Mus/Arvicanthis split. Our test analysis on Bayesian age estimates shows that this new calibration point provides more accurate estimates of murine divergence than previous applications. Thus, we define this fossil calibration point and refine two other fossil-based points for molecular dating.

Corrected placement of Mus-Rattus fossil calibration forces precision in the molecular tree of rodents

PubMed Central

Kimura, Yuri; Hawkins, Melissa T. R.; McDonough, Molly M.; Jacobs, Louis L.; Flynn, Lawrence J.

2015-01-01

Time calibration derived from the fossil record is essential for molecular phylogenetic and evolutionary studies. Fossil mice and rats, discovered in the Siwalik Group of Pakistan, have served as one of the best-known fossil calibration points in molecular phylogenic studies. Although these fossils have been widely used as the 12 Ma date for the Mus/Rattus split or a more basal split, conclusive paleontological evidence for the nodal assignments has been absent. This study analyzes newly recognized characters that demonstrate lineage separation in the fossil record of Siwalik murines and examines the most reasonable nodal placement of the diverging lineages in a molecular phylogenetic tree by ancestral state reconstruction. Our specimen-based approach strongly indicates that Siwalik murines of the Karnimata clade are fossil members of the Arvicanthini-Otomyini-Millardini clade, which excludes Rattus and its relatives. Combining the new interpretation with the widely accepted hypothesis that the Progonomys clade includes Mus, the lineage separation event in the Siwalik fossil record represents the Mus/Arvicanthis split. Our test analysis on Bayesian age estimates shows that this new calibration point provides more accurate estimates of murine divergence than previous applications. Thus, we define this fossil calibration point and refine two other fossil-based points for molecular dating. PMID:26411391

Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

PubMed

Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

2011-12-01

This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

Phylogenetic Relationships of American Willows (Salix L., Salicaceae)

PubMed Central

Lauron-Moreau, Aurélien; Pitre, Frédéric E.; Argus, George W.; Labrecque, Michel; Brouillet, Luc

2015-01-01

Salix L. is the largest genus in the family Salicaceae (450 species). Several classifications have been published, but taxonomic subdivision has been under continuous revision. Our goal is to establish the phylogenetic structure of the genus using molecular data on all American willows, using three DNA markers. This complete phylogeny of American willows allows us to propose a biogeographic framework for the evolution of the genus. Material was obtained for the 122 native and introduced willow species of America. Sequences were obtained from the ITS (ribosomal nuclear DNA) and two plastid regions, matK and rbcL. Phylogenetic analyses (parsimony, maximum likelihood, Bayesian inference) were performed on the data. Geographic distribution was mapped onto the tree. The species tree provides strong support for a division of the genus into two subgenera, Salix and Vetrix. Subgenus Salix comprises temperate species from the Americas and Asia, and their disjunction may result from Tertiary events. Subgenus Vetrix is composed of boreo-arctic species of the Northern Hemisphere and their radiation may coincide with the Quaternary glaciations. Sixteen species have ambiguous positions; genetic diversity is lower in subg. Vetrix. A molecular phylogeny of all species of American willows has been inferred. It needs to be tested and further resolved using other molecular data. Nonetheless, the genus clearly has two clades that have distinct biogeographic patterns. PMID:25880993

Recent colonization of the Galápagos by the tree Geoffroea spinosa Jacq. (Leguminosae).

PubMed

Caetano, S; Currat, M; Pennington, R T; Prado, D; Excoffier, L; Naciri, Y

2012-06-01

This study puts together genetic data and an approximate bayesian computation (ABC) approach to infer the time at which the tree Geoffroea spinosa colonized the Galápagos Islands. The genetic diversity and differentiation between Peru and Galápagos population samples, estimated using three chloroplast spacers and six microsatellite loci, reveal significant differences between two mainland regions separated by the Andes mountains (Inter Andean vs. Pacific Coast) as well as a significant genetic differentiation of island populations. Microsatellites identify two distinct geographical clusters, the Galápagos and the mainland, and chloroplast markers show a private haplotype in the Galápagos. The nuclear distinctiveness of the Inter Andean populations suggests current restricted pollen flow, but chloroplast points to cross-Andean dispersals via seeds, indicating that the Andes might not be an effective biogeographical barrier. The ABC analyses clearly point to the colonization of the Galápagos within the last 160,000 years and possibly as recently as 4750 years ago (475 generations). Founder events associated with colonization of the two islands where the species occurs are detected, with Española having been colonized after Floreana. We discuss two nonmutually exclusive possibilities for the colonization of the Galápagos, recent natural dispersal vs. human introduction. © 2012 Blackwell Publishing Ltd.

Forest tree responses to extreme drought and some biotic events: Towards a selection according to hazard tolerance?

NASA Astrophysics Data System (ADS)

Bréda, Nathalie; Badeau, Vincent

2008-09-01

The aim of this paper is to illustrate how some extreme events could affect forest ecosystems. Forest tree response can be analysed using dendroecological methods, as tree-ring widths are strongly controlled by climatic or biotic events. Years with such events induce similar tree responses and are called pointer years. They can result from extreme climatic events like frost, a heat wave, spring water logging, drought or insect damage… Forest tree species showed contrasting responses to climatic hazards, depending on their sensitivity to water shortage or temperature hardening, as illustrated from our dendrochronological database. For foresters, a drought or a pest disease is an extreme event if visible and durable symptoms are induced (leaf discolouration, leaf loss, perennial organs mortality, tree dieback and mortality). These symptoms here are shown, lagging one or several years behind a climatic or biotic event, from forest decline cases in progress since the 2003 drought or attributed to previous severe droughts or defoliations in France. Tree growth or vitality recovery is illustrated, and the functional interpretation of the long lasting memory of trees is discussed. A coupled approach linking dendrochronology and ecophysiology helps in discussing vulnerability of forest stands, and suggests management advices in order to mitigate extreme drought and cope with selective mortality.

Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

DTIC Science & Technology

2016-01-05

SECURITY CLASSIFICATION OF: The research objective of this proposal was to develop a predictive Bayesian kernel approach to model count data based on...several predictive variables. Such an approach, which we refer to as the Poisson Bayesian kernel model , is able to model the rate of occurrence of...which adds specificity to the model and can make nonlinear data more manageable. Early results show that the 1. REPORT DATE (DD-MM-YYYY) 4. TITLE

Coalescent methods for estimating phylogenetic trees.

PubMed

Liu, Liang; Yu, Lili; Kubatko, Laura; Pearl, Dennis K; Edwards, Scott V

2009-10-01

We review recent models to estimate phylogenetic trees under the multispecies coalescent. Although the distinction between gene trees and species trees has come to the fore of phylogenetics, only recently have methods been developed that explicitly estimate species trees. Of the several factors that can cause gene tree heterogeneity and discordance with the species tree, deep coalescence due to random genetic drift in branches of the species tree has been modeled most thoroughly. Bayesian approaches to estimating species trees utilizes two likelihood functions, one of which has been widely used in traditional phylogenetics and involves the model of nucleotide substitution, and the second of which is less familiar to phylogeneticists and involves the probability distribution of gene trees given a species tree. Other recent parametric and nonparametric methods for estimating species trees involve parsimony criteria, summary statistics, supertree and consensus methods. Species tree approaches are an appropriate goal for systematics, appear to work well in some cases where concatenation can be misleading, and suggest that sampling many independent loci will be paramount. Such methods can also be challenging to implement because of the complexity of the models and computational time. In addition, further elaboration of the simplest of coalescent models will be required to incorporate commonly known issues such as deviation from the molecular clock, gene flow and other genetic forces.

Efficiency of nuclear and mitochondrial markers recovering and supporting known amniote groups.

PubMed

Lambret-Frotté, Julia; Perini, Fernando Araújo; de Moraes Russo, Claudia Augusta

2012-01-01

We have analysed the efficiency of all mitochondrial protein coding genes and six nuclear markers (Adora3, Adrb2, Bdnf, Irbp, Rag2 and Vwf) in reconstructing and statistically supporting known amniote groups (murines, rodents, primates, eutherians, metatherians, therians). The efficiencies of maximum likelihood, Bayesian inference, maximum parsimony, neighbor-joining and UPGMA were also evaluated, by assessing the number of correct and incorrect recovered groupings. In addition, we have compared support values using the conservative bootstrap test and the Bayesian posterior probabilities. First, no correlation was observed between gene size and marker efficiency in recovering or supporting correct nodes. As expected, tree-building methods performed similarly, even UPGMA that, in some cases, outperformed other most extensively used methods. Bayesian posterior probabilities tend to show much higher support values than the conservative bootstrap test, for correct and incorrect nodes. Our results also suggest that nuclear markers do not necessarily show a better performance than mitochondrial genes. The so-called dependency among mitochondrial markers was not observed comparing genome performances. Finally, the amniote groups with lowest recovery rates were therians and rodents, despite the morphological support for their monophyletic status. We suggest that, regardless of the tree-building method, a few carefully selected genes are able to unfold a detailed and robust scenario of phylogenetic hypotheses, particularly if taxon sampling is increased.

Predicting Rotator Cuff Tears Using Data Mining and Bayesian Likelihood Ratios

PubMed Central

Lu, Hsueh-Yi; Huang, Chen-Yuan; Su, Chwen-Tzeng; Lin, Chen-Chiang

2014-01-01

Objectives Rotator cuff tear is a common cause of shoulder diseases. Correct diagnosis of rotator cuff tears can save patients from further invasive, costly and painful tests. This study used predictive data mining and Bayesian theory to improve the accuracy of diagnosing rotator cuff tears by clinical examination alone. Methods In this retrospective study, 169 patients who had a preliminary diagnosis of rotator cuff tear on the basis of clinical evaluation followed by confirmatory MRI between 2007 and 2011 were identified. MRI was used as a reference standard to classify rotator cuff tears. The predictor variable was the clinical assessment results, which consisted of 16 attributes. This study employed 2 data mining methods (ANN and the decision tree) and a statistical method (logistic regression) to classify the rotator cuff diagnosis into “tear” and “no tear” groups. Likelihood ratio and Bayesian theory were applied to estimate the probability of rotator cuff tears based on the results of the prediction models. Results Our proposed data mining procedures outperformed the classic statistical method. The correction rate, sensitivity, specificity and area under the ROC curve of predicting a rotator cuff tear were statistical better in the ANN and decision tree models compared to logistic regression. Based on likelihood ratios derived from our prediction models, Fagan's nomogram could be constructed to assess the probability of a patient who has a rotator cuff tear using a pretest probability and a prediction result (tear or no tear). Conclusions Our predictive data mining models, combined with likelihood ratios and Bayesian theory, appear to be good tools to classify rotator cuff tears as well as determine the probability of the presence of the disease to enhance diagnostic decision making for rotator cuff tears. PMID:24733553

Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

NASA Astrophysics Data System (ADS)

Tsai, F. T. C.; Elshall, A. S.

2014-12-01

Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.

Genealogical Working Distributions for Bayesian Model Testing with Phylogenetic Uncertainty

PubMed Central

Baele, Guy; Lemey, Philippe; Suchard, Marc A.

2016-01-01

Marginal likelihood estimates to compare models using Bayes factors frequently accompany Bayesian phylogenetic inference. Approaches to estimate marginal likelihoods have garnered increased attention over the past decade. In particular, the introduction of path sampling (PS) and stepping-stone sampling (SS) into Bayesian phylogenetics has tremendously improved the accuracy of model selection. These sampling techniques are now used to evaluate complex evolutionary and population genetic models on empirical data sets, but considerable computational demands hamper their widespread adoption. Further, when very diffuse, but proper priors are specified for model parameters, numerical issues complicate the exploration of the priors, a necessary step in marginal likelihood estimation using PS or SS. To avoid such instabilities, generalized SS (GSS) has recently been proposed, introducing the concept of “working distributions” to facilitate—or shorten—the integration process that underlies marginal likelihood estimation. However, the need to fix the tree topology currently limits GSS in a coalescent-based framework. Here, we extend GSS by relaxing the fixed underlying tree topology assumption. To this purpose, we introduce a “working” distribution on the space of genealogies, which enables estimating marginal likelihoods while accommodating phylogenetic uncertainty. We propose two different “working” distributions that help GSS to outperform PS and SS in terms of accuracy when comparing demographic and evolutionary models applied to synthetic data and real-world examples. Further, we show that the use of very diffuse priors can lead to a considerable overestimation in marginal likelihood when using PS and SS, while still retrieving the correct marginal likelihood using both GSS approaches. The methods used in this article are available in BEAST, a powerful user-friendly software package to perform Bayesian evolutionary analyses. PMID:26526428

Testing for Independence between Evolutionary Processes.

PubMed

Behdenna, Abdelkader; Pothier, Joël; Abby, Sophie S; Lambert, Amaury; Achaz, Guillaume

2016-09-01

Evolutionary events co-occurring along phylogenetic trees usually point to complex adaptive phenomena, sometimes implicating epistasis. While a number of methods have been developed to account for co-occurrence of events on the same internal or external branch of an evolutionary tree, there is a need to account for the larger diversity of possible relative positions of events in a tree. Here we propose a method to quantify to what extent two or more evolutionary events are associated on a phylogenetic tree. The method is applicable to any discrete character, like substitutions within a coding sequence or gains/losses of a biological function. Our method uses a general approach to statistically test for significant associations between events along the tree, which encompasses both events inseparable on the same branch, and events genealogically ordered on different branches. It assumes that the phylogeny and themapping of branches is known without errors. We address this problem from the statistical viewpoint by a linear algebra representation of the localization of the evolutionary events on the tree.We compute the full probability distribution of the number of paired events occurring in the same branch or in different branches of the tree, under a null model of independence where each type of event occurs at a constant rate uniformly inthephylogenetic tree. The strengths andweaknesses of themethodare assessed via simulations;we then apply the method to explore the loss of cell motility in intracellular pathogens. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Learning oncogenetic networks by reducing to mixed integer linear programming.

PubMed

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

Species trees for the tree swallows (Genus Tachycineta): an alternative phylogenetic hypothesis to the mitochondrial gene tree.

PubMed

Dor, Roi; Carling, Matthew D; Lovette, Irby J; Sheldon, Frederick H; Winkler, David W

2012-10-01

The New World swallow genus Tachycineta comprises nine species that collectively have a wide geographic distribution and remarkable variation both within- and among-species in ecologically important traits. Existing phylogenetic hypotheses for Tachycineta are based on mitochondrial DNA sequences, thus they provide estimates of a single gene tree. In this study we sequenced multiple individuals from each species at 16 nuclear intron loci. We used gene concatenated approaches (Bayesian and maximum likelihood) as well as coalescent-based species tree inference to reconstruct phylogenetic relationships of the genus. We examined the concordance and conflict between the nuclear and mitochondrial trees and between concatenated and coalescent-based inferences. Our results provide an alternative phylogenetic hypothesis to the existing mitochondrial DNA estimate of phylogeny. This new hypothesis provides a more accurate framework in which to explore trait evolution and examine the evolution of the mitochondrial genome in this group. Copyright © 2012 Elsevier Inc. All rights reserved.

Continuous event monitoring via a Bayesian predictive approach.

PubMed

Di, Jianing; Wang, Daniel; Brashear, H Robert; Dragalin, Vladimir; Krams, Michael

2016-01-01

In clinical trials, continuous monitoring of event incidence rate plays a critical role in making timely decisions affecting trial outcome. For example, continuous monitoring of adverse events protects the safety of trial participants, while continuous monitoring of efficacy events helps identify early signals of efficacy or futility. Because the endpoint of interest is often the event incidence associated with a given length of treatment duration (e.g., incidence proportion of an adverse event with 2 years of dosing), assessing the event proportion before reaching the intended treatment duration becomes challenging, especially when the event onset profile evolves over time with accumulated exposure. In particular, in the earlier part of the study, ignoring censored subjects may result in significant bias in estimating the cumulative event incidence rate. Such a problem is addressed using a predictive approach in the Bayesian framework. In the proposed approach, experts' prior knowledge about both the frequency and timing of the event occurrence is combined with observed data. More specifically, during any interim look, each event-free subject will be counted with a probability that is derived using prior knowledge. The proposed approach is particularly useful in early stage studies for signal detection based on limited information. But it can also be used as a tool for safety monitoring (e.g., data monitoring committee) during later stage trials. Application of the approach is illustrated using a case study where the incidence rate of an adverse event is continuously monitored during an Alzheimer's disease clinical trial. The performance of the proposed approach is also assessed and compared with other Bayesian and frequentist methods via simulation. Copyright © 2015 John Wiley & Sons, Ltd.

Bayesian Total-Evidence Dating Reveals the Recent Crown Radiation of Penguins

PubMed Central

Heath, Tracy A.; Ksepka, Daniel T.; Stadler, Tanja; Welch, David; Drummond, Alexei J.

2017-01-01

The total-evidence approach to divergence time dating uses molecular and morphological data from extant and fossil species to infer phylogenetic relationships, species divergence times, and macroevolutionary parameters in a single coherent framework. Current model-based implementations of this approach lack an appropriate model for the tree describing the diversification and fossilization process and can produce estimates that lead to erroneous conclusions. We address this shortcoming by providing a total-evidence method implemented in a Bayesian framework. This approach uses a mechanistic tree prior to describe the underlying diversification process that generated the tree of extant and fossil taxa. Previous attempts to apply the total-evidence approach have used tree priors that do not account for the possibility that fossil samples may be direct ancestors of other samples, that is, ancestors of fossil or extant species or of clades. The fossilized birth–death (FBD) process explicitly models the diversification, fossilization, and sampling processes and naturally allows for sampled ancestors. This model was recently applied to estimate divergence times based on molecular data and fossil occurrence dates. We incorporate the FBD model and a model of morphological trait evolution into a Bayesian total-evidence approach to dating species phylogenies. We apply this method to extant and fossil penguins and show that the modern penguins radiated much more recently than has been previously estimated, with the basal divergence in the crown clade occurring at \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${\\sim}12.7$\\end{document} Ma and most splits leading to extant species occurring in the last 2 myr. Our results demonstrate that including stem-fossil diversity can greatly improve the estimates of the divergence times of crown taxa. The method is available in BEAST2 (version 2.4) software www.beast2.org with packages SA (version at least 1.1.4) and morph-models (version at least 1.0.4) installed. [Birth–death process; calibration; divergence times; MCMC; phylogenetics.] PMID:28173531

Development of a Bayesian Belief Network Runway Incursion Model

NASA Technical Reports Server (NTRS)

Green, Lawrence L.

2014-01-01

In a previous paper, a statistical analysis of runway incursion (RI) events was conducted to ascertain their relevance to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to perhaps several of the AvSP top ten TC. That data also identified several primary causes and contributing factors for RI events that served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events. The system-level BBN model will allow NASA to generically model the causes of RI events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of RI events in particular, and to improve runway safety in general. The development, structure and assessment of that BBN for RI events by a Subject Matter Expert panel are documented in this paper.

The Variability and Interpretation of Earthquake Source Mechanisms in The Geysers Geothermal Field From a Bayesian Standpoint Based on the Choice of a Noise Model

NASA Astrophysics Data System (ADS)

Mustać, Marija; Tkalčić, Hrvoje; Burky, Alexander L.

2018-01-01

Moment tensor (MT) inversion studies of events in The Geysers geothermal field mostly focused on microseismicity and found a large number of earthquakes with significant non-double-couple (non-DC) seismic radiation. Here we concentrate on the largest events in the area in recent years using a hierarchical Bayesian MT inversion. Initially, we show that the non-DC components of the MT can be reliably retrieved using regional waveform data from a small number of stations. Subsequently, we present results for a number of events and show that accounting for noise correlations can lead to retrieval of a lower isotropic (ISO) component and significantly different focal mechanisms. We compute the Bayesian evidence to compare solutions obtained with different assumptions of the noise covariance matrix. Although a diagonal covariance matrix produces a better waveform fit, inversions that account for noise correlations via an empirically estimated noise covariance matrix account for interdependences of data errors and are preferred from a Bayesian point of view. This implies that improper treatment of data noise in waveform inversions can result in fitting the noise and misinterpreting the non-DC components. Finally, one of the analyzed events is characterized as predominantly DC, while the others still have significant non-DC components, probably as a result of crack opening, which is a reasonable hypothesis for The Geysers geothermal field geological setting.

Rigorous Approach in Investigation of Seismic Structure and Source Characteristicsin Northeast Asia: Hierarchical and Trans-dimensional Bayesian Inversion

NASA Astrophysics Data System (ADS)

Mustac, M.; Kim, S.; Tkalcic, H.; Rhie, J.; Chen, Y.; Ford, S. R.; Sebastian, N.

2015-12-01

Conventional approaches to inverse problems suffer from non-linearity and non-uniqueness in estimations of seismic structures and source properties. Estimated results and associated uncertainties are often biased by applied regularizations and additional constraints, which are commonly introduced to solve such problems. Bayesian methods, however, provide statistically meaningful estimations of models and their uncertainties constrained by data information. In addition, hierarchical and trans-dimensional (trans-D) techniques are inherently implemented in the Bayesian framework to account for involved error statistics and model parameterizations, and, in turn, allow more rigorous estimations of the same. Here, we apply Bayesian methods throughout the entire inference process to estimate seismic structures and source properties in Northeast Asia including east China, the Korean peninsula, and the Japanese islands. Ambient noise analysis is first performed to obtain a base three-dimensional (3-D) heterogeneity model using continuous broadband waveforms from more than 300 stations. As for the tomography of surface wave group and phase velocities in the 5-70 s band, we adopt a hierarchical and trans-D Bayesian inversion method using Voronoi partition. The 3-D heterogeneity model is further improved by joint inversions of teleseismic receiver functions and dispersion data using a newly developed high-efficiency Bayesian technique. The obtained model is subsequently used to prepare 3-D structural Green's functions for the source characterization. A hierarchical Bayesian method for point source inversion using regional complete waveform data is applied to selected events from the region. The seismic structure and source characteristics with rigorously estimated uncertainties from the novel Bayesian methods provide enhanced monitoring and discrimination of seismic events in northeast Asia.

Fault Tree Analysis: An Operations Research Tool for Identifying and Reducing Undesired Events in Training.

ERIC Educational Resources Information Center

Barker, Bruce O.; Petersen, Paul D.

This paper explores the fault-tree analysis approach to isolating failure modes within a system. Fault tree investigates potentially undesirable events and then looks for failures in sequence that would lead to their occurring. Relationships among these events are symbolized by AND or OR logic gates, AND used when single events must coexist to…

Learning Instance-Specific Predictive Models

PubMed Central

Visweswaran, Shyam; Cooper, Gregory F.

2013-01-01

This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algorithm learns Markov blanket models, carries out Bayesian model averaging over a set of models to predict a target variable of the instance at hand, and employs an instance-specific heuristic to locate a set of suitable models to average over. We call this method the instance-specific Markov blanket (ISMB) algorithm. The ISMB algorithm was evaluated on 21 UCI data sets using five different performance measures and its performance was compared to that of several commonly used predictive algorithms, including nave Bayes, C4.5 decision tree, logistic regression, neural networks, k-Nearest Neighbor, Lazy Bayesian Rules, and AdaBoost. Over all the data sets, the ISMB algorithm performed better on average on all performance measures against all the comparison algorithms. PMID:25045325

Potential Use of a Bayesian Network for Discriminating Flash Type from Future GOES-R Geostationary Lightning Mapper (GLM) data

NASA Technical Reports Server (NTRS)

Solakiewiz, Richard; Koshak, William

2008-01-01

Continuous monitoring of the ratio of cloud flashes to ground flashes may provide a better understanding of thunderstorm dynamics, intensification, and evolution, and it may be useful in severe weather warning. The National Lighting Detection Network TM (NLDN) senses ground flashes with exceptional detection efficiency and accuracy over most of the continental United States. A proposed Geostationary Lightning Mapper (GLM) aboard the Geostationary Operational Environmental Satellite (GOES-R) will look at the western hemisphere, and among the lightning data products to be made available will be the fundamental optical flash parameters for both cloud and ground flashes: radiance, area, duration, number of optical groups, and number of optical events. Previous studies have demonstrated that the optical flash parameter statistics of ground and cloud lightning, which are observable from space, are significantly different. This study investigates a Bayesian network methodology for discriminating lightning flash type (ground or cloud) using the lightning optical data and ancillary GOES-R data. A Directed Acyclic Graph (DAG) is set up with lightning as a "root" and data observed by GLM as the "leaves." This allows for a direct calculation of the joint probability distribution function for the lighting type and radiance, area, etc. Initially, the conditional probabilities that will be required can be estimated from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) together with NLDN data. Directly manipulating the joint distribution will yield the conditional probability that a lightning flash is a ground flash given the evidence, which consists of the observed lightning optical data [and possibly cloud data retrieved from the GOES-R Advanced Baseline Imager (ABI) in a more mature Bayesian network configuration]. Later, actual GLM and NLDN data can be used to refine the estimates of the conditional probabilities used in the model; i.e., the Bayesian network is a learning network. Methods for efficient calculation of the conditional probabilities (e.g., an algorithm using junction trees), finding data conflicts, goodness of fit, and dealing with missing data will also be addressed.

Identifying the rooted species tree from the distribution of unrooted gene trees under the coalescent.

PubMed

Allman, Elizabeth S; Degnan, James H; Rhodes, John A

2011-06-01

Gene trees are evolutionary trees representing the ancestry of genes sampled from multiple populations. Species trees represent populations of individuals-each with many genes-splitting into new populations or species. The coalescent process, which models ancestry of gene copies within populations, is often used to model the probability distribution of gene trees given a fixed species tree. This multispecies coalescent model provides a framework for phylogeneticists to infer species trees from gene trees using maximum likelihood or Bayesian approaches. Because the coalescent models a branching process over time, all trees are typically assumed to be rooted in this setting. Often, however, gene trees inferred by traditional phylogenetic methods are unrooted. We investigate probabilities of unrooted gene trees under the multispecies coalescent model. We show that when there are four species with one gene sampled per species, the distribution of unrooted gene tree topologies identifies the unrooted species tree topology and some, but not all, information in the species tree edges (branch lengths). The location of the root on the species tree is not identifiable in this situation. However, for 5 or more species with one gene sampled per species, we show that the distribution of unrooted gene tree topologies identifies the rooted species tree topology and all its internal branch lengths. The length of any pendant branch leading to a leaf of the species tree is also identifiable for any species from which more than one gene is sampled.

Bayesian Inference for Signal-Based Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.

2015-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. SIG-VISA (Signal-based Vertically Integrated Seismic Analysis) is a system for global seismic monitoring through Bayesian inference on seismic signals. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of recent geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a global network of stations. We demonstrate recent progress in scaling up SIG-VISA to efficiently process the data stream of global signals recorded by the International Monitoring System (IMS), including comparisons against existing processing methods that show increased sensitivity from our signal-based model and in particular the ability to locate events (including aftershock sequences that can tax analyst processing) precisely from waveform correlation effects. We also provide a Bayesian analysis of an alleged low-magnitude event near the DPRK test site in May 2010 [1] [2], investigating whether such an event could plausibly be detected through automated processing in a signal-based monitoring system. [1] Zhang, Miao and Wen, Lianxing. "Seismological Evidence for a Low-Yield Nuclear Test on 12 May 2010 in North Korea". Seismological Research Letters, January/February 2015. [2] Richards, Paul. "A Seismic Event in North Korea on 12 May 2010". CTBTO SnT 2015 oral presentation, video at https://video-archive.ctbto.org/index.php/kmc/preview/partner_id/103/uiconf_id/4421629/entry_id/0_ymmtpps0/delivery/http

NET-VISA, a Bayesian method next-generation automatic association software. Latest developments and operational assessment.

NASA Astrophysics Data System (ADS)

Le Bras, Ronan; Kushida, Noriyuki; Mialle, Pierrick; Tomuta, Elena; Arora, Nimar

2017-04-01

The Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) has been developing a Bayesian method and software to perform the key step of automatic association of seismological, hydroacoustic, and infrasound (SHI) parametric data. In our preliminary testing in the CTBTO, NET_VISA shows much better performance than its currently operating automatic association module, with a rate for automatic events matching the analyst-reviewed events increased by 10%, signifying that the percentage of missed events is lowered by 40%. Initial tests involving analysts also showed that the new software will complete the automatic bulletins of the CTBTO by adding previously missed events. Because products by the CTBTO are also widely distributed to its member States as well as throughout the seismological community, the introduction of a new technology must be carried out carefully, and the first step of operational integration is to first use NET-VISA results within the interactive analysts' software so that the analysts can check the robustness of the Bayesian approach. We report on the latest results both on the progress for automatic processing and for the initial introduction of NET-VISA results in the analyst review process

A Bayesian framework for infrasound location

NASA Astrophysics Data System (ADS)

Modrak, Ryan T.; Arrowsmith, Stephen J.; Anderson, Dale N.

2010-04-01

We develop a framework for location of infrasound events using backazimuth and infrasonic arrival times from multiple arrays. Bayesian infrasonic source location (BISL) developed here estimates event location and associated credibility regions. BISL accounts for unknown source-to-array path or phase by formulating infrasonic group velocity as random. Differences between observed and predicted source-to-array traveltimes are partitioned into two additive Gaussian sources, measurement error and model error, the second of which accounts for the unknown influence of wind and temperature on path. By applying the technique to both synthetic tests and ground-truth events, we highlight the complementary nature of back azimuths and arrival times for estimating well-constrained event locations. BISL is an extension to methods developed earlier by Arrowsmith et al. that provided simple bounds on location using a grid-search technique.

STRIDE: Species Tree Root Inference from Gene Duplication Events.

PubMed

Emms, David M; Kelly, Steven

2017-12-01

The correct interpretation of any phylogenetic tree is dependent on that tree being correctly rooted. We present STRIDE, a fast, effective, and outgroup-free method for identification of gene duplication events and species tree root inference in large-scale molecular phylogenetic analyses. STRIDE identifies sets of well-supported in-group gene duplication events from a set of unrooted gene trees, and analyses these events to infer a probability distribution over an unrooted species tree for the location of its root. We show that STRIDE correctly identifies the root of the species tree in multiple large-scale molecular phylogenetic data sets spanning a wide range of timescales and taxonomic groups. We demonstrate that the novel probability model implemented in STRIDE can accurately represent the ambiguity in species tree root assignment for data sets where information is limited. Furthermore, application of STRIDE to outgroup-free inference of the origin of the eukaryotic tree resulted in a root probability distribution that provides additional support for leading hypotheses for the origin of the eukaryotes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Mining pharmacovigilance data using Bayesian logistic regression with James-Stein type shrinkage estimation.

PubMed

An, Lihua; Fung, Karen Y; Krewski, Daniel

2010-09-01

Spontaneous adverse event reporting systems are widely used to identify adverse reactions to drugs following their introduction into the marketplace. In this article, a James-Stein type shrinkage estimation strategy was developed in a Bayesian logistic regression model to analyze pharmacovigilance data. This method is effective in detecting signals as it combines information and borrows strength across medically related adverse events. Computer simulation demonstrated that the shrinkage estimator is uniformly better than the maximum likelihood estimator in terms of mean squared error. This method was used to investigate the possible association of a series of diabetic drugs and the risk of cardiovascular events using data from the Canada Vigilance Online Database.

Bayesian propensity scores for high-dimensional causal inference: A comparison of drug-eluting to bare-metal coronary stents.

PubMed

Spertus, Jacob V; Normand, Sharon-Lise T

2018-04-23

High-dimensional data provide many potential confounders that may bolster the plausibility of the ignorability assumption in causal inference problems. Propensity score methods are powerful causal inference tools, which are popular in health care research and are particularly useful for high-dimensional data. Recent interest has surrounded a Bayesian treatment of propensity scores in order to flexibly model the treatment assignment mechanism and summarize posterior quantities while incorporating variance from the treatment model. We discuss methods for Bayesian propensity score analysis of binary treatments, focusing on modern methods for high-dimensional Bayesian regression and the propagation of uncertainty. We introduce a novel and simple estimator for the average treatment effect that capitalizes on conjugacy of the beta and binomial distributions. Through simulations, we show the utility of horseshoe priors and Bayesian additive regression trees paired with our new estimator, while demonstrating the importance of including variance from the treatment regression model. An application to cardiac stent data with almost 500 confounders and 9000 patients illustrates approaches and facilitates comparison with existing alternatives. As measured by a falsifiability endpoint, we improved confounder adjustment compared with past observational research of the same problem. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining probabilistic hazard assessment with cost-benefit analysis to support decision making in a volcanic crisis from the Auckland Volcanic Field, New Zealand

NASA Astrophysics Data System (ADS)

Sandri, Laura; Jolly, Gill; Lindsay, Jan; Howe, Tracy; Marzocchi, Warner

2010-05-01

One of the main challenges of modern volcanology is to provide the public with robust and useful information for decision-making in land-use planning and in emergency management. From the scientific point of view, this translates into reliable and quantitative long- and short-term volcanic hazard assessment and eruption forecasting. Because of the complexity in characterizing volcanic events, and of the natural variability of volcanic processes, a probabilistic approach is more suitable than deterministic modeling. In recent years, two probabilistic codes have been developed for quantitative short- and long-term eruption forecasting (BET_EF) and volcanic hazard assessment (BET_VH). Both of them are based on a Bayesian Event Tree, in which volcanic events are seen as a chain of logical steps of increasing detail. At each node of the tree, the probability is computed by taking into account different sources of information, such as geological and volcanological models, past occurrences, expert opinion and numerical modeling of volcanic phenomena. Since it is a Bayesian tool, the output probability is not a single number, but a probability distribution accounting for aleatory and epistemic uncertainty. In this study, we apply BET_VH in order to quantify the long-term volcanic hazard due to base surge invasion in the region around Auckland, New Zealand's most populous city. Here, small basaltic eruptions from monogenetic cones pose a considerable risk to the city in case of phreatomagmatic activity: evidence for base surges are not uncommon in deposits from past events. Currently, we are particularly focussing on the scenario simulated during Exercise Ruaumoko, a national disaster exercise based on the build-up to an eruption in the Auckland Volcanic Field. Based on recent papers by Marzocchi and Woo, we suggest a possible quantitative strategy to link probabilistic scientific output and Boolean decision making. It is based on cost-benefit analysis, in which all costs and benefits of mitigation actions have to be evaluated and compared, weighting them with the probability of occurrence of a specific threatening volcanic event. An action should be taken when the benefit of that action outweighs the costs. It is worth remarking that this strategy does not guarantee to recommend a decision that we would have taken with the benefit of hindsight. However, this strategy will be successful over the long-tem. Furthermore, it has the overwhelming advantage of providing a quantitative decision rule that is set before any emergency, and thus it will be justifiable at any stage of the process. In our present application, we are trying to set up a cost-benefit scheme for the call of an evacuation to protect people in the Auckland Volcanic Field against base surge invasion. Considering the heterogeneity of the urban environment and the size of the region at risk, we propose a cost-benefit scheme that is space dependent, to take into account higher costs when an eruption threatens sensible sites for the city and/or the nation, such as the international airport or the harbour. Finally, we compare our findings with the present Contingency Plan for Auckland.

77 FR 61024 - Notice of Public Meeting and Request for Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-05

... public meeting and public comments--The National Christmas Tree Lighting and the subsequent 26-day event... National Christmas Tree Lighting and the subsequent 26-day event. The general plan and theme for the event... comments and suggestions on the planning of the 2012 National Christmas Tree Lighting and the subsequent 26...

Bayesian regression model for recurrent event data with event-varying covariate effects and event effect.

PubMed

Lin, Li-An; Luo, Sheng; Davis, Barry R

2018-01-01

In the course of hypertension, cardiovascular disease events (e.g., stroke, heart failure) occur frequently and recurrently. The scientific interest in such study may lie in the estimation of treatment effect while accounting for the correlation among event times. The correlation among recurrent event times come from two sources: subject-specific heterogeneity (e.g., varied lifestyles, genetic variations, and other unmeasurable effects) and event dependence (i.e., event incidences may change the risk of future recurrent events). Moreover, event incidences may change the disease progression so that there may exist event-varying covariate effects (the covariate effects may change after each event) and event effect (the effect of prior events on the future events). In this article, we propose a Bayesian regression model that not only accommodates correlation among recurrent events from both sources, but also explicitly characterizes the event-varying covariate effects and event effect. This model is especially useful in quantifying how the incidences of events change the effects of covariates and risk of future events. We compare the proposed model with several commonly used recurrent event models and apply our model to the motivating lipid-lowering trial (LLT) component of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) (ALLHAT-LLT).

Bayesian regression model for recurrent event data with event-varying covariate effects and event effect

PubMed Central

Lin, Li-An; Luo, Sheng; Davis, Barry R.

2017-01-01

In the course of hypertension, cardiovascular disease events (e.g., stroke, heart failure) occur frequently and recurrently. The scientific interest in such study may lie in the estimation of treatment effect while accounting for the correlation among event times. The correlation among recurrent event times come from two sources: subject-specific heterogeneity (e.g., varied lifestyles, genetic variations, and other unmeasurable effects) and event dependence (i.e., event incidences may change the risk of future recurrent events). Moreover, event incidences may change the disease progression so that there may exist event-varying covariate effects (the covariate effects may change after each event) and event effect (the effect of prior events on the future events). In this article, we propose a Bayesian regression model that not only accommodates correlation among recurrent events from both sources, but also explicitly characterizes the event-varying covariate effects and event effect. This model is especially useful in quantifying how the incidences of events change the effects of covariates and risk of future events. We compare the proposed model with several commonly used recurrent event models and apply our model to the motivating lipid-lowering trial (LLT) component of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) (ALLHAT-LLT). PMID:29755162

Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

PubMed

Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

2011-01-01

Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

Bayesian averaging over Decision Tree models for trauma severity scoring.

PubMed

Schetinin, V; Jakaite, L; Krzanowski, W

2018-01-01

Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the "gold" standard of screening a patient's conditions for predicting survival probability, based on logistic regression modelling, which is used in trauma care for clinical purposes and quality audit. This methodology is based on theoretical assumptions about data and uncertainties. Models induced within such an approach have exposed a number of problems, providing unexplained fluctuation of predicted survival and low accuracy of estimating uncertainty intervals within which predictions are made. Bayesian method, which in theory is capable of providing accurate predictions and uncertainty estimates, has been adopted in our study using Decision Tree models. Our approach has been tested on a large set of patients registered in the US National Trauma Data Bank and has outperformed the standard method in terms of prediction accuracy, thereby providing practitioners with accurate estimates of the predictive posterior densities of interest that are required for making risk-aware decisions. Copyright © 2017 Elsevier B.V. All rights reserved.

Tracking composite material damage evolution using Bayesian filtering and flash thermography data

NASA Astrophysics Data System (ADS)

Gregory, Elizabeth D.; Holland, Steve D.

2016-05-01

We propose a method for tracking the condition of a composite part using Bayesian filtering of ash thermography data over the lifetime of the part. In this demonstration, composite panels were fabricated; impacted to induce subsurface delaminations; and loaded in compression over multiple time steps, causing the delaminations to grow in size. Flash thermography data was collected between each damage event to serve as a time history of the part. The ash thermography indicated some areas of damage but provided little additional information as to the exact nature or depth of the damage. Computed tomography (CT) data was also collected after each damage event and provided a high resolution volume model of damage that acted as truth. After each cycle, the condition estimate, from the ash thermography data and the Bayesian filter, was compared to 'ground truth'. The Bayesian process builds on the lifetime history of ash thermography scans and can give better estimates of material condition as compared to the most recent scan alone, which is common practice in the aerospace industry. Bayesian inference provides probabilistic estimates of damage condition that are updated as each new set of data becomes available. The method was tested on simulated data and then on an experimental data set.

The Efficacy of Consensus Tree Methods for Summarizing Phylogenetic Relationships from a Posterior Sample of Trees Estimated from Morphological Data.

PubMed

O'Reilly, Joseph E; Donoghue, Philip C J

2018-03-01

Consensus trees are required to summarize trees obtained through MCMC sampling of a posterior distribution, providing an overview of the distribution of estimated parameters such as topology, branch lengths, and divergence times. Numerous consensus tree construction methods are available, each presenting a different interpretation of the tree sample. The rise of morphological clock and sampled-ancestor methods of divergence time estimation, in which times and topology are coestimated, has increased the popularity of the maximum clade credibility (MCC) consensus tree method. The MCC method assumes that the sampled, fully resolved topology with the highest clade credibility is an adequate summary of the most probable clades, with parameter estimates from compatible sampled trees used to obtain the marginal distributions of parameters such as clade ages and branch lengths. Using both simulated and empirical data, we demonstrate that MCC trees, and trees constructed using the similar maximum a posteriori (MAP) method, often include poorly supported and incorrect clades when summarizing diffuse posterior samples of trees. We demonstrate that the paucity of information in morphological data sets contributes to the inability of MCC and MAP trees to accurately summarise of the posterior distribution. Conversely, majority-rule consensus (MRC) trees represent a lower proportion of incorrect nodes when summarizing the same posterior samples of trees. Thus, we advocate the use of MRC trees, in place of MCC or MAP trees, in attempts to summarize the results of Bayesian phylogenetic analyses of morphological data.

The Efficacy of Consensus Tree Methods for Summarizing Phylogenetic Relationships from a Posterior Sample of Trees Estimated from Morphological Data

PubMed Central

O’Reilly, Joseph E; Donoghue, Philip C J

2018-01-01

Abstract Consensus trees are required to summarize trees obtained through MCMC sampling of a posterior distribution, providing an overview of the distribution of estimated parameters such as topology, branch lengths, and divergence times. Numerous consensus tree construction methods are available, each presenting a different interpretation of the tree sample. The rise of morphological clock and sampled-ancestor methods of divergence time estimation, in which times and topology are coestimated, has increased the popularity of the maximum clade credibility (MCC) consensus tree method. The MCC method assumes that the sampled, fully resolved topology with the highest clade credibility is an adequate summary of the most probable clades, with parameter estimates from compatible sampled trees used to obtain the marginal distributions of parameters such as clade ages and branch lengths. Using both simulated and empirical data, we demonstrate that MCC trees, and trees constructed using the similar maximum a posteriori (MAP) method, often include poorly supported and incorrect clades when summarizing diffuse posterior samples of trees. We demonstrate that the paucity of information in morphological data sets contributes to the inability of MCC and MAP trees to accurately summarise of the posterior distribution. Conversely, majority-rule consensus (MRC) trees represent a lower proportion of incorrect nodes when summarizing the same posterior samples of trees. Thus, we advocate the use of MRC trees, in place of MCC or MAP trees, in attempts to summarize the results of Bayesian phylogenetic analyses of morphological data. PMID:29106675

Bayesian Network Meta-Analysis for Unordered Categorical Outcomes with Incomplete Data

ERIC Educational Resources Information Center

Schmid, Christopher H.; Trikalinos, Thomas A.; Olkin, Ingram

2014-01-01

We develop a Bayesian multinomial network meta-analysis model for unordered (nominal) categorical outcomes that allows for partially observed data in which exact event counts may not be known for each category. This model properly accounts for correlations of counts in mutually exclusive categories and enables proper comparison and ranking of…

Impact of censoring on learning Bayesian networks in survival modelling.

PubMed

Stajduhar, Ivan; Dalbelo-Basić, Bojana; Bogunović, Nikola

2009-11-01

Bayesian networks are commonly used for presenting uncertainty and covariate interactions in an easily interpretable way. Because of their efficient inference and ability to represent causal relationships, they are an excellent choice for medical decision support systems in diagnosis, treatment, and prognosis. Although good procedures for learning Bayesian networks from data have been defined, their performance in learning from censored survival data has not been widely studied. In this paper, we explore how to use these procedures to learn about possible interactions between prognostic factors and their influence on the variate of interest. We study how censoring affects the probability of learning correct Bayesian network structures. Additionally, we analyse the potential usefulness of the learnt models for predicting the time-independent probability of an event of interest. We analysed the influence of censoring with a simulation on synthetic data sampled from randomly generated Bayesian networks. We used two well-known methods for learning Bayesian networks from data: a constraint-based method and a score-based method. We compared the performance of each method under different levels of censoring to those of the naive Bayes classifier and the proportional hazards model. We did additional experiments on several datasets from real-world medical domains. The machine-learning methods treated censored cases in the data as event-free. We report and compare results for several commonly used model evaluation metrics. On average, the proportional hazards method outperformed other methods in most censoring setups. As part of the simulation study, we also analysed structural similarities of the learnt networks. Heavy censoring, as opposed to no censoring, produces up to a 5% surplus and up to 10% missing total arcs. It also produces up to 50% missing arcs that should originally be connected to the variate of interest. Presented methods for learning Bayesian networks from data can be used to learn from censored survival data in the presence of light censoring (up to 20%) by treating censored cases as event-free. Given intermediate or heavy censoring, the learnt models become tuned to the majority class and would thus require a different approach.

Predicting coastal cliff erosion using a Bayesian probabilistic model

USGS Publications Warehouse

Hapke, Cheryl J.; Plant, Nathaniel G.

2010-01-01

Regional coastal cliff retreat is difficult to model due to the episodic nature of failures and the along-shore variability of retreat events. There is a growing demand, however, for predictive models that can be used to forecast areas vulnerable to coastal erosion hazards. Increasingly, probabilistic models are being employed that require data sets of high temporal density to define the joint probability density function that relates forcing variables (e.g. wave conditions) and initial conditions (e.g. cliff geometry) to erosion events. In this study we use a multi-parameter Bayesian network to investigate correlations between key variables that control and influence variations in cliff retreat processes. The network uses Bayesian statistical methods to estimate event probabilities using existing observations. Within this framework, we forecast the spatial distribution of cliff retreat along two stretches of cliffed coast in Southern California. The input parameters are the height and slope of the cliff, a descriptor of material strength based on the dominant cliff-forming lithology, and the long-term cliff erosion rate that represents prior behavior. The model is forced using predicted wave impact hours. Results demonstrate that the Bayesian approach is well-suited to the forward modeling of coastal cliff retreat, with the correct outcomes forecast in 70–90% of the modeled transects. The model also performs well in identifying specific locations of high cliff erosion, thus providing a foundation for hazard mapping. This approach can be employed to predict cliff erosion at time-scales ranging from storm events to the impacts of sea-level rise at the century-scale.

Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

PubMed Central

2010-01-01

Background All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. Results The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. Conclusions This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general. PMID:20144194

Bayesian Decision Tree for the Classification of the Mode of Motion in Single-Molecule Trajectories

PubMed Central

Türkcan, Silvan; Masson, Jean-Baptiste

2013-01-01

Membrane proteins move in heterogeneous environments with spatially (sometimes temporally) varying friction and with biochemical interactions with various partners. It is important to reliably distinguish different modes of motion to improve our knowledge of the membrane architecture and to understand the nature of interactions between membrane proteins and their environments. Here, we present an analysis technique for single molecule tracking (SMT) trajectories that can determine the preferred model of motion that best matches observed trajectories. The method is based on Bayesian inference to calculate the posteriori probability of an observed trajectory according to a certain model. Information theory criteria, such as the Bayesian information criterion (BIC), the Akaike information criterion (AIC), and modified AIC (AICc), are used to select the preferred model. The considered group of models includes free Brownian motion, and confined motion in 2nd or 4th order potentials. We determine the best information criteria for classifying trajectories. We tested its limits through simulations matching large sets of experimental conditions and we built a decision tree. This decision tree first uses the BIC to distinguish between free Brownian motion and confined motion. In a second step, it classifies the confining potential further using the AIC. We apply the method to experimental Clostridium Perfingens -toxin (CPT) receptor trajectories to show that these receptors are confined by a spring-like potential. An adaptation of this technique was applied on a sliding window in the temporal dimension along the trajectory. We applied this adaptation to experimental CPT trajectories that lose confinement due to disaggregation of confining domains. This new technique adds another dimension to the discussion of SMT data. The mode of motion of a receptor might hold more biologically relevant information than the diffusion coefficient or domain size and may be a better tool to classify and compare different SMT experiments. PMID:24376584

Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies.

PubMed

David, Maria Pamela C; Concepcion, Gisela P; Padlan, Eduardo A

2010-02-08

All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general.

Methods for estimating population density in data-limited areas: evaluating regression and tree-based models in Peru.

PubMed

Anderson, Weston; Guikema, Seth; Zaitchik, Ben; Pan, William

2014-01-01

Obtaining accurate small area estimates of population is essential for policy and health planning but is often difficult in countries with limited data. In lieu of available population data, small area estimate models draw information from previous time periods or from similar areas. This study focuses on model-based methods for estimating population when no direct samples are available in the area of interest. To explore the efficacy of tree-based models for estimating population density, we compare six different model structures including Random Forest and Bayesian Additive Regression Trees. Results demonstrate that without information from prior time periods, non-parametric tree-based models produced more accurate predictions than did conventional regression methods. Improving estimates of population density in non-sampled areas is important for regions with incomplete census data and has implications for economic, health and development policies.

Methods for Estimating Population Density in Data-Limited Areas: Evaluating Regression and Tree-Based Models in Peru

PubMed Central

Anderson, Weston; Guikema, Seth; Zaitchik, Ben; Pan, William

2014-01-01

Obtaining accurate small area estimates of population is essential for policy and health planning but is often difficult in countries with limited data. In lieu of available population data, small area estimate models draw information from previous time periods or from similar areas. This study focuses on model-based methods for estimating population when no direct samples are available in the area of interest. To explore the efficacy of tree-based models for estimating population density, we compare six different model structures including Random Forest and Bayesian Additive Regression Trees. Results demonstrate that without information from prior time periods, non-parametric tree-based models produced more accurate predictions than did conventional regression methods. Improving estimates of population density in non-sampled areas is important for regions with incomplete census data and has implications for economic, health and development policies. PMID:24992657

Looking for trees in the forest: summary tree from posterior samples

PubMed Central

2013-01-01

Background Bayesian phylogenetic analysis generates a set of trees which are often condensed into a single tree representing the whole set. Many methods exist for selecting a representative topology for a set of unrooted trees, few exist for assigning branch lengths to a fixed topology, and even fewer for simultaneously setting the topology and branch lengths. However, there is very little research into locating a good representative for a set of rooted time trees like the ones obtained from a BEAST analysis. Results We empirically compare new and known methods for generating a summary tree. Some new methods are motivated by mathematical constructions such as tree metrics, while the rest employ tree concepts which work well in practice. These use more of the posterior than existing methods, which discard information not directly mapped to the chosen topology. Using results from a large number of simulations we assess the quality of a summary tree, measuring (a) how well it explains the sequence data under the model and (b) how close it is to the “truth”, i.e to the tree used to generate the sequences. Conclusions Our simulations indicate that no single method is “best”. Methods producing good divergence time estimates have poor branch lengths and lower model fit, and vice versa. Using the results presented here, a user can choose the appropriate method based on the purpose of the summary tree. PMID:24093883

Looking for trees in the forest: summary tree from posterior samples.

PubMed

Heled, Joseph; Bouckaert, Remco R

2013-10-04

Bayesian phylogenetic analysis generates a set of trees which are often condensed into a single tree representing the whole set. Many methods exist for selecting a representative topology for a set of unrooted trees, few exist for assigning branch lengths to a fixed topology, and even fewer for simultaneously setting the topology and branch lengths. However, there is very little research into locating a good representative for a set of rooted time trees like the ones obtained from a BEAST analysis. We empirically compare new and known methods for generating a summary tree. Some new methods are motivated by mathematical constructions such as tree metrics, while the rest employ tree concepts which work well in practice. These use more of the posterior than existing methods, which discard information not directly mapped to the chosen topology. Using results from a large number of simulations we assess the quality of a summary tree, measuring (a) how well it explains the sequence data under the model and (b) how close it is to the "truth", i.e to the tree used to generate the sequences. Our simulations indicate that no single method is "best". Methods producing good divergence time estimates have poor branch lengths and lower model fit, and vice versa. Using the results presented here, a user can choose the appropriate method based on the purpose of the summary tree.

Anatomical modeling of the bronchial tree

NASA Astrophysics Data System (ADS)

Hentschel, Gerrit; Klinder, Tobias; Blaffert, Thomas; Bülow, Thomas; Wiemker, Rafael; Lorenz, Cristian

2010-02-01

The bronchial tree is of direct clinical importance in the context of respective diseases, such as chronic obstructive pulmonary disease (COPD). It furthermore constitutes a reference structure for object localization in the lungs and it finally provides access to lung tissue in, e.g., bronchoscope based procedures for diagnosis and therapy. This paper presents a comprehensive anatomical model for the bronchial tree, including statistics of position, relative and absolute orientation, length, and radius of 34 bronchial segments, going beyond previously published results. The model has been built from 16 manually annotated CT scans, covering several branching variants. The model is represented as a centerline/tree structure but can also be converted in a surface representation. Possible model applications are either to anatomically label extracted bronchial trees or to improve the tree extraction itself by identifying missing segments or sub-trees, e.g., if located beyond a bronchial stenosis. Bronchial tree labeling is achieved using a naïve Bayesian classifier based on the segment properties contained in the model in combination with tree matching. The tree matching step makes use of branching variations covered by the model. An evaluation of the model has been performed in a leaveone- out manner. In total, 87% of the branches resulting from preceding airway tree segmentation could be correctly labeled. The individualized model enables the detection of missing branches, allowing a targeted search, e.g., a local rerun of the tree-segmentation segmentation.

IND - THE IND DECISION TREE PACKAGE

NASA Technical Reports Server (NTRS)

Buntine, W.

1994-01-01

A common approach to supervised classification and prediction in artificial intelligence and statistical pattern recognition is the use of decision trees. A tree is "grown" from data using a recursive partitioning algorithm to create a tree which has good prediction of classes on new data. Standard algorithms are CART (by Breiman Friedman, Olshen and Stone) and ID3 and its successor C4 (by Quinlan). As well as reimplementing parts of these algorithms and offering experimental control suites, IND also introduces Bayesian and MML methods and more sophisticated search in growing trees. These produce more accurate class probability estimates that are important in applications like diagnosis. IND is applicable to most data sets consisting of independent instances, each described by a fixed length vector of attribute values. An attribute value may be a number, one of a set of attribute specific symbols, or it may be omitted. One of the attributes is delegated the "target" and IND grows trees to predict the target. Prediction can then be done on new data or the decision tree printed out for inspection. IND provides a range of features and styles with convenience for the casual user as well as fine-tuning for the advanced user or those interested in research. IND can be operated in a CART-like mode (but without regression trees, surrogate splits or multivariate splits), and in a mode like the early version of C4. Advanced features allow more extensive search, interactive control and display of tree growing, and Bayesian and MML algorithms for tree pruning and smoothing. These often produce more accurate class probability estimates at the leaves. IND also comes with a comprehensive experimental control suite. IND consists of four basic kinds of routines: data manipulation routines, tree generation routines, tree testing routines, and tree display routines. The data manipulation routines are used to partition a single large data set into smaller training and test sets. The generation routines are used to build classifiers. The test routines are used to evaluate classifiers and to classify data using a classifier. And the display routines are used to display classifiers in various formats. IND is written in C-language for Sun4 series computers. It consists of several programs with controlling shell scripts. Extensive UNIX man entries are included. IND is designed to be used on any UNIX system, although it has only been thoroughly tested on SUN platforms. The standard distribution medium for IND is a .25 inch streaming magnetic tape cartridge in UNIX tar format. An electronic copy of the documentation in PostScript format is included on the distribution medium. IND was developed in 1992.

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics.

PubMed

Itter, Malcolm S; Finley, Andrew O; D'Amato, Anthony W; Foster, Jane R; Bradford, John B

2017-06-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics-changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands. © 2017 by the Ecological Society of America.

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics

USGS Publications Warehouse

Itter, Malcolm S.; Finley, Andrew O.; D'Amato, Anthony W.; Foster, Jane R.; Bradford, John B.

2017-01-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands.

Kernel and divergence techniques in high energy physics separations

NASA Astrophysics Data System (ADS)

Bouř, Petr; Kůs, Václav; Franc, Jiří

2017-10-01

Binary decision trees under the Bayesian decision technique are used for supervised classification of high-dimensional data. We present a great potential of adaptive kernel density estimation as the nested separation method of the supervised binary divergence decision tree. Also, we provide a proof of alternative computing approach for kernel estimates utilizing Fourier transform. Further, we apply our method to Monte Carlo data set from the particle accelerator Tevatron at DØ experiment in Fermilab and provide final top-antitop signal separation results. We have achieved up to 82 % AUC while using the restricted feature selection entering the signal separation procedure.

Molecular phylogeny of Gymnocalycium (Cactaceae): assessment of alternative infrageneric systems, a new subgenus, and trends in the evolution of the genus.

PubMed

Demaio, Pablo H; Barfuss, Michael H J; Kiesling, Roberto; Till, Walter; Chiapella, Jorge O

2011-11-01

The South American genus Gymnocalycium (Cactoideae-Trichocereae) demonstrates how the sole use of morphological data in Cactaceae results in conflicts in assessing phylogeny, constructing a taxonomic system, and analyzing trends in the evolution of the genus. Molecular phylogenetic analysis was performed using parsimony and Bayesian methods on a 6195-bp data matrix of plastid DNA sequences (atpI-atpH, petL-psbE, trnK-matK, trnT-trnL-trnF) of 78 samples, including 52 species and infraspecific taxa representing all the subgenera of Gymnocalycium. We assessed morphological character evolution using likelihood methods to optimize characters on a Bayesian tree and to reconstruct possible ancestral states. The results of the phylogenetic study confirm the monophyly of the genus, while supporting overall the available infrageneric classification based on seed morphology. Analysis showed the subgenera Microsemineum and Macrosemineum to be polyphyletic and paraphyletic. Analysis of morphological characters showed a tendency toward reduction of stem size, reduction in quantity and hardiness of spines, increment of seed size, development of napiform roots, and change from juicy and colorful fruits to dry and green fruits. Gymnocalycium saglionis is the only species of Microsemineum and a new name is required to identify the clade including the remaining species of Microsemineum; we propose the name Scabrosemineum in agreement with seed morphology. Identifying morphological trends and environmental features allows for a better understanding of the events that might have influenced the diversification of the genus.

Computational statistics using the Bayesian Inference Engine

NASA Astrophysics Data System (ADS)

Weinberg, Martin D.

2013-09-01

This paper introduces the Bayesian Inference Engine (BIE), a general parallel, optimized software package for parameter inference and model selection. This package is motivated by the analysis needs of modern astronomical surveys and the need to organize and reuse expensive derived data. The BIE is the first platform for computational statistics designed explicitly to enable Bayesian update and model comparison for astronomical problems. Bayesian update is based on the representation of high-dimensional posterior distributions using metric-ball-tree based kernel density estimation. Among its algorithmic offerings, the BIE emphasizes hybrid tempered Markov chain Monte Carlo schemes that robustly sample multimodal posterior distributions in high-dimensional parameter spaces. Moreover, the BIE implements a full persistence or serialization system that stores the full byte-level image of the running inference and previously characterized posterior distributions for later use. Two new algorithms to compute the marginal likelihood from the posterior distribution, developed for and implemented in the BIE, enable model comparison for complex models and data sets. Finally, the BIE was designed to be a collaborative platform for applying Bayesian methodology to astronomy. It includes an extensible object-oriented and easily extended framework that implements every aspect of the Bayesian inference. By providing a variety of statistical algorithms for all phases of the inference problem, a scientist may explore a variety of approaches with a single model and data implementation. Additional technical details and download details are available from http://www.astro.umass.edu/bie. The BIE is distributed under the GNU General Public License.

treespace: Statistical exploration of landscapes of phylogenetic trees.

PubMed

Jombart, Thibaut; Kendall, Michelle; Almagro-Garcia, Jacob; Colijn, Caroline

2017-11-01

The increasing availability of large genomic data sets as well as the advent of Bayesian phylogenetics facilitates the investigation of phylogenetic incongruence, which can result in the impossibility of representing phylogenetic relationships using a single tree. While sometimes considered as a nuisance, phylogenetic incongruence can also reflect meaningful biological processes as well as relevant statistical uncertainty, both of which can yield valuable insights in evolutionary studies. We introduce a new tool for investigating phylogenetic incongruence through the exploration of phylogenetic tree landscapes. Our approach, implemented in the R package treespace, combines tree metrics and multivariate analysis to provide low-dimensional representations of the topological variability in a set of trees, which can be used for identifying clusters of similar trees and group-specific consensus phylogenies. treespace also provides a user-friendly web interface for interactive data analysis and is integrated alongside existing standards for phylogenetics. It fills a gap in the current phylogenetics toolbox in R and will facilitate the investigation of phylogenetic results. © 2017 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

2016-01-01

Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

Modeling of Water Flow Processes in the Soil-Plant-Atmosphere System: The Soil-Tree-Atmosphere Continuum Model

NASA Astrophysics Data System (ADS)

Massoud, E. C.; Vrugt, J. A.

2015-12-01

Trees and forests play a key role in controlling the water and energy balance at the land-air surface. This study reports on the calibration of an integrated soil-tree-atmosphere continuum (STAC) model using Bayesian inference with the DREAM algorithm and temporal observations of soil moisture content, matric head, sap flux, and leaf water potential from the King's River Experimental Watershed (KREW) in the southern Sierra Nevada mountain range in California. Water flow through the coupled system is described using the Richards' equation with both the soil and tree modeled as a porous medium with nonlinear soil and tree water relationships. Most of the model parameters appear to be reasonably well defined by calibration against the observed data. The posterior mean simulation reproduces the observed soil and tree data quite accurately, but a systematic mismatch is observed between early afternoon measured and simulated sap fluxes. We will show how this points to a structural error in the STAC-model and suggest and test an alternative hypothesis for root water uptake that alleviates this problem.

Presentation of the results of a Bayesian automatic event detection and localization program to human analysts

NASA Astrophysics Data System (ADS)

Kushida, N.; Kebede, F.; Feitio, P.; Le Bras, R.

2016-12-01

The Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) has been developing and testing NET-VISA (Arora et al., 2013), a Bayesian automatic event detection and localization program, and evaluating its performance in a realistic operational mode. In our preliminary testing at the CTBTO, NET-VISA shows better performance than its currently operating automatic localization program. However, given CTBTO's role and its international context, a new technology should be introduced cautiously when it replaces a key piece of the automatic processing. We integrated the results of NET-VISA into the Analyst Review Station, extensively used by the analysts so that they can check the accuracy and robustness of the Bayesian approach. We expect the workload of the analysts to be reduced because of the better performance of NET-VISA in finding missed events and getting a more complete set of stations than the current system which has been operating for nearly twenty years. The results of a series of tests indicate that the expectations born from the automatic tests, which show an overall overlap improvement of 11%, meaning that the missed events rate is cut by 42%, hold for the integrated interactive module as well. New events are found by analysts, which qualify for the CTBTO Reviewed Event Bulletin, beyond the ones analyzed through the standard procedures. Arora, N., Russell, S., and Sudderth, E., NET-VISA: Network Processing Vertically Integrated Seismic Analysis, 2013, Bull. Seismol. Soc. Am., 103, 709-729.

A combined Fuzzy and Naive Bayesian strategy can be used to assign event codes to injury narratives.

PubMed

Marucci-Wellman, H; Lehto, M; Corns, H

2011-12-01

Bayesian methods show promise for classifying injury narratives from large administrative datasets into cause groups. This study examined a combined approach where two Bayesian models (Fuzzy and Naïve) were used to either classify a narrative or select it for manual review. Injury narratives were extracted from claims filed with a worker's compensation insurance provider between January 2002 and December 2004. Narratives were separated into a training set (n=11,000) and prediction set (n=3,000). Expert coders assigned two-digit Bureau of Labor Statistics Occupational Injury and Illness Classification event codes to each narrative. Fuzzy and Naïve Bayesian models were developed using manually classified cases in the training set. Two semi-automatic machine coding strategies were evaluated. The first strategy assigned cases for manual review if the Fuzzy and Naïve models disagreed on the classification. The second strategy selected additional cases for manual review from the Agree dataset using prediction strength to reach a level of 50% computer coding and 50% manual coding. When agreement alone was used as the filtering strategy, the majority were coded by the computer (n=1,928, 64%) leaving 36% for manual review. The overall combined (human plus computer) sensitivity was 0.90 and positive predictive value (PPV) was >0.90 for 11 of 18 2-digit event categories. Implementing the 2nd strategy improved results with an overall sensitivity of 0.95 and PPV >0.90 for 17 of 18 categories. A combined Naïve-Fuzzy Bayesian approach can classify some narratives with high accuracy and identify others most beneficial for manual review, reducing the burden on human coders.

Phylogenetic congruence of armored scale insects (Hemiptera: Diaspididae) and their primary endosymbionts from the phylum Bacteroidetes.

PubMed

Gruwell, Matthew E; Morse, Geoffrey E; Normark, Benjamin B

2007-07-01

Insects in the sap-sucking hemipteran suborder Sternorrhyncha typically harbor maternally transmitted bacteria housed in a specialized organ, the bacteriome. In three of the four superfamilies of Sternorrhyncha (Aphidoidea, Aleyrodoidea, Psylloidea), the bacteriome-associated (primary) bacterial lineage is from the class Gammaproteobacteria (phylum Proteobacteria). The fourth superfamily, Coccoidea (scale insects), has a diverse array of bacterial endosymbionts whose affinities are largely unexplored. We have amplified fragments of two bacterial ribosomal genes from each of 68 species of armored scale insects (Diaspididae). In spite of initially using primers designed for Gammaproteobacteria, we consistently amplified sequences from a different bacterial phylum: Bacteroidetes. We use these sequences (16S and 23S, 2105 total base pairs), along with previously published sequences from the armored scale hosts (elongation factor 1alpha and 28S rDNA) to investigate phylogenetic congruence between the two clades. The Bayesian tree for the bacteria is roughly congruent with that of the hosts, with 67% of nodes identical. Partition homogeneity tests found no significant difference between the host and bacterial data sets. Of thirteen Shimodaira-Hasegawa tests, comparing the original Bayesian bacterial tree to bacterial trees with incongruent clades forced to match the host tree, 12 found no significant difference. A significant difference in topology was found only when the entire host tree was compared with the entire bacterial tree. For the bacterial data set, the treelengths of the most parsimonious host trees are only 1.8-2.4% longer than that of the most parsimonious bacterial trees. The high level of congruence between the topologies indicates that these Bacteroidetes are the primary endosymbionts of armored scale insects. To investigate the phylogenetic affinities of these endosymbionts, we aligned some of their 16S rDNA sequences with other known Bacteroidetes endosymbionts and with other similar sequences identified by BLAST searches. Although the endosymbionts of armored scales are only distantly related to the endosymbionts of the other sternorrhynchan insects, they are closely related to bacteria associated with eriococcid and margarodid scale insects, to cockroach and auchenorrynchan endosymbionts (Blattabacterium and Sulcia), and to male-killing endosymbionts of ladybird beetles. We propose the name "Candidatus Uzinura diaspidicola" for the primary endosymbionts of armored scale insects.

On incomplete sampling under birth-death models and connections to the sampling-based coalescent.

PubMed

Stadler, Tanja

2009-11-07

The constant rate birth-death process is used as a stochastic model for many biological systems, for example phylogenies or disease transmission. As the biological data are usually not fully available, it is crucial to understand the effect of incomplete sampling. In this paper, we analyze the constant rate birth-death process with incomplete sampling. We derive the density of the bifurcation events for trees on n leaves which evolved under this birth-death-sampling process. This density is used for calculating prior distributions in Bayesian inference programs and for efficiently simulating trees. We show that the birth-death-sampling process can be interpreted as a birth-death process with reduced rates and complete sampling. This shows that joint inference of birth rate, death rate and sampling probability is not possible. The birth-death-sampling process is compared to the sampling-based population genetics model, the coalescent. It is shown that despite many similarities between these two models, the distribution of bifurcation times remains different even in the case of very large population sizes. We illustrate these findings on an Hepatitis C virus dataset from Egypt. We show that the transmission times estimates are significantly different-the widely used Gamma statistic even changes its sign from negative to positive when switching from the coalescent to the birth-death process.

Genetic variation in scaly hair-fin anchovy Setipinna tenuifilis (Engraulididae) based on the mitochondrial DNA control region.

PubMed

Xu, Shengyong; Song, Na; Lu, Zhichuang; Wang, Jun; Cai, Shanshan; Gao, Tianxiang

2014-06-01

Scaly hair-fin anchovy (Setipinna tenuifilis) is a small, pelagic and economical species and widely distributed in Chinese coastal water. However, resources of S. tenuifilis have been reduced due to overfishing. For better fishery management, it is necessary to understand the pattern of S. tenuifilis's biogeography. Genetic analyses were taken place to detect their population genetic variation. A total of 153 individuals from 7 locations (Dongying, Yantai, Qingdao, Nantong, Wenzhou, Xiamen and Beibu Bay) were sequenced at the 5' end of mtDNA control region. A 39-bp tandem repeated sequence was found at the 5' end of the segment and a polymorphism of tandem repeated sequence was detected among 7 populations. Both mismatch distribution analysis and neutrality tests showed S. tenuifilis had experienced a recent population expansion. The topology of neighbor-joining tree and Bayesian evolutionary tree showed no significant genealogical branches or clusters of samples corresponding to sampling locality. Hierarchical analysis of molecular variance and conventional pairwise population Fst value at group hierarchical level implied that there might have genetic divergence between southern group (population WZ, XM and BB) and northern group (population DY, YT, QD and NT). We concluded that there might have three different fishery management groups of S. tenuifilis and the late Pleistocene glacial event might have a crucial effect on present-day demography of S. tenuifilis in this region.

Two C++ Libraries for Counting Trees on a Phylogenetic Terrace.

PubMed

Biczok, R; Bozsoky, P; Eisenmann, P; Ernst, J; Ribizel, T; Scholz, F; Trefzer, A; Weber, F; Hamann, M; Stamatakis, A

2018-05-08

The presence of terraces in phylogenetic tree space, that is, a potentially large number of distinct tree topologies that have exactly the same analytical likelihood score, was first described by Sanderson et al. (2011). However, popular software tools for maximum likelihood and Bayesian phylogenetic inference do not yet routinely report, if inferred phylogenies reside on a terrace, or not. We believe, this is due to the lack of an efficient library to (i) determine if a tree resides on a terrace, (ii) calculate how many trees reside on a terrace, and (iii) enumerate all trees on a terrace. In our bioinformatics practical that is set up as a programming contest we developed two efficient and independent C++ implementations of the SUPERB algorithm by Constantinescu and Sankoff (1995) for counting and enumerating trees on a terrace. Both implementations yield exactly the same results, are more than one order of magnitude faster, and require one order of magnitude less memory than a previous 3rd party python implementation. The source codes are available under GNU GPL at https://github.com/terraphast. Alexandros.Stamatakis@h-its.org. Supplementary data are available at Bioinformatics online.

Initial Evaluation of Signal-Based Bayesian Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Russell, S.

2016-12-01

We present SIGVISA (Signal-based Vertically Integrated Seismic Analysis), a next-generation system for global seismic monitoring through Bayesian inference on seismic signals. Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a network of stations. We report results from an evaluation of SIGVISA monitoring the western United States for a two-week period following the magnitude 6.0 event in Wells, NV in February 2008. During this period, SIGVISA detects more than twice as many events as NETVISA, and three times as many as SEL3, while operating at the same precision; at lower precisions it detects up to five times as many events as SEL3. At the same time, signal-based monitoring reduces mean location errors by a factor of four relative to detection-based systems. We provide evidence that, given only IMS data, SIGVISA detects events that are missed by regional monitoring networks, indicating that our evaluations may even underestimate its performance. Finally, SIGVISA matches or exceeds the detection rates of existing systems for de novo events - events with no nearby historical seismicity - and detects through automated processing a number of such events missed even by the human analysts generating the LEB.

Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting.

PubMed

Vock, David M; Wolfson, Julian; Bandyopadhyay, Sunayan; Adomavicius, Gediminas; Johnson, Paul E; Vazquez-Benitez, Gabriela; O'Connor, Patrick J

2016-06-01

Models for predicting the probability of experiencing various health outcomes or adverse events over a certain time frame (e.g., having a heart attack in the next 5years) based on individual patient characteristics are important tools for managing patient care. Electronic health data (EHD) are appealing sources of training data because they provide access to large amounts of rich individual-level data from present-day patient populations. However, because EHD are derived by extracting information from administrative and clinical databases, some fraction of subjects will not be under observation for the entire time frame over which one wants to make predictions; this loss to follow-up is often due to disenrollment from the health system. For subjects without complete follow-up, whether or not they experienced the adverse event is unknown, and in statistical terms the event time is said to be right-censored. Most machine learning approaches to the problem have been relatively ad hoc; for example, common approaches for handling observations in which the event status is unknown include (1) discarding those observations, (2) treating them as non-events, (3) splitting those observations into two observations: one where the event occurs and one where the event does not. In this paper, we present a general-purpose approach to account for right-censored outcomes using inverse probability of censoring weighting (IPCW). We illustrate how IPCW can easily be incorporated into a number of existing machine learning algorithms used to mine big health care data including Bayesian networks, k-nearest neighbors, decision trees, and generalized additive models. We then show that our approach leads to better calibrated predictions than the three ad hoc approaches when applied to predicting the 5-year risk of experiencing a cardiovascular adverse event, using EHD from a large U.S. Midwestern healthcare system. Copyright © 2016 Elsevier Inc. All rights reserved.

An Efficient Independence Sampler for Updating Branches in Bayesian Markov chain Monte Carlo Sampling of Phylogenetic Trees.

PubMed

Aberer, Andre J; Stamatakis, Alexandros; Ronquist, Fredrik

2016-01-01

Sampling tree space is the most challenging aspect of Bayesian phylogenetic inference. The sheer number of alternative topologies is problematic by itself. In addition, the complex dependency between branch lengths and topology increases the difficulty of moving efficiently among topologies. Current tree proposals are fast but sample new trees using primitive transformations or re-mappings of old branch lengths. This reduces acceptance rates and presumably slows down convergence and mixing. Here, we explore branch proposals that do not rely on old branch lengths but instead are based on approximations of the conditional posterior. Using a diverse set of empirical data sets, we show that most conditional branch posteriors can be accurately approximated via a [Formula: see text] distribution. We empirically determine the relationship between the logarithmic conditional posterior density, its derivatives, and the characteristics of the branch posterior. We use these relationships to derive an independence sampler for proposing branches with an acceptance ratio of ~90% on most data sets. This proposal samples branches between 2× and 3× more efficiently than traditional proposals with respect to the effective sample size per unit of runtime. We also compare the performance of standard topology proposals with hybrid proposals that use the new independence sampler to update those branches that are most affected by the topological change. Our results show that hybrid proposals can sometimes noticeably decrease the number of generations necessary for topological convergence. Inconsistent performance gains indicate that branch updates are not the limiting factor in improving topological convergence for the currently employed set of proposals. However, our independence sampler might be essential for the construction of novel tree proposals that apply more radical topology changes. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Efficient Probabilistic Diagnostics for Electrical Power Systems

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Chavira, Mark; Cascio, Keith; Poll, Scott; Darwiche, Adnan; Uckun, Serdar

2008-01-01

We consider in this work the probabilistic approach to model-based diagnosis when applied to electrical power systems (EPSs). Our probabilistic approach is formally well-founded, as it based on Bayesian networks and arithmetic circuits. We investigate the diagnostic task known as fault isolation, and pay special attention to meeting two of the main challenges . model development and real-time reasoning . often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-to-use speci.cation language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In essence, we introduce a high-level EPS speci.cation language from which Bayesian networks that can diagnose multiple simultaneous failures are auto-generated, and we illustrate the feasibility of using arithmetic circuits, compiled from Bayesian networks, for real-time diagnosis on real-world EPSs of interest to NASA. The experimental system is a real-world EPS, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. In experiments with the ADAPT Bayesian network, which currently contains 503 discrete nodes and 579 edges, we .nd high diagnostic accuracy in scenarios where one to three faults, both in components and sensors, were inserted. The time taken to compute the most probable explanation using arithmetic circuits has a small mean of 0.2625 milliseconds and standard deviation of 0.2028 milliseconds. In experiments with data from ADAPT we also show that arithmetic circuit evaluation substantially outperforms joint tree propagation and variable elimination, two alternative algorithms for diagnosis using Bayesian network inference.

The Tunguska event in 1908: evidence from tree-ring anatomy.

PubMed

Vaganov, Evgenii A; Hughes, Malcolm K; Silkin, Pavel P; Nesvetailo, Valery D

2004-01-01

We analyzed tree rings in wood samples collected from some of the few surviving trees found close to the epicenter (within 4-5 km) of the Tunguska event that occurred on the last day of June 1908. Tree-ring growth shows a depression starting in the year after the event and continuing during a 4-5-year period. The most remarkable traces of the event were found in the rings' anatomical structure: (1) formation of "light" rings and a reduction of maximum density in 1908; (2) non-thickened tracheids (the cells that make up most of the wood volume) in the transition and latewood zones (the middle and last-formed parts of the ring, respectively); and (3) deformed tracheids, which are located on the 1908 annual ring outer boundary. In the majority of samples, normal earlywood and latewood tracheids were formed in all annual rings after 1908. The observed anomalies in wood anatomy suggest two main impacts of the Tunguska event on surviving trees--(1) defoliation and (2) direct mechanical stress on active xylem tissue. The mechanical stress needed to fell trees is less than the stress needed to cause the deformation of differentiating tracheids observed in trees close to the epicenter. In order to resolve this apparent contradiction, work is suggested on possible topographic modification of the overpressure experienced by these trees, as is an experimental test of the effects of such stresses on precisely analogous growing trees.

Probabilistic inference using linear Gaussian importance sampling for hybrid Bayesian networks

NASA Astrophysics Data System (ADS)

Sun, Wei; Chang, K. C.

2005-05-01

Probabilistic inference for Bayesian networks is in general NP-hard using either exact algorithms or approximate methods. However, for very complex networks, only the approximate methods such as stochastic sampling could be used to provide a solution given any time constraint. There are several simulation methods currently available. They include logic sampling (the first proposed stochastic method for Bayesian networks, the likelihood weighting algorithm) the most commonly used simulation method because of its simplicity and efficiency, the Markov blanket scoring method, and the importance sampling algorithm. In this paper, we first briefly review and compare these available simulation methods, then we propose an improved importance sampling algorithm called linear Gaussian importance sampling algorithm for general hybrid model (LGIS). LGIS is aimed for hybrid Bayesian networks consisting of both discrete and continuous random variables with arbitrary distributions. It uses linear function and Gaussian additive noise to approximate the true conditional probability distribution for continuous variable given both its parents and evidence in a Bayesian network. One of the most important features of the newly developed method is that it can adaptively learn the optimal important function from the previous samples. We test the inference performance of LGIS using a 16-node linear Gaussian model and a 6-node general hybrid model. The performance comparison with other well-known methods such as Junction tree (JT) and likelihood weighting (LW) shows that LGIS-GHM is very promising.

New phiomorph rodents from the latest Eocene of Egypt, and the impact of Bayesian "clock"-based phylogenetic methods on estimates of basal hystricognath relationships and biochronology.

PubMed

Sallam, Hesham M; Seiffert, Erik R

2016-01-01

The Fayum Depression of Egypt has yielded fossils of hystricognathous rodents from multiple Eocene and Oligocene horizons that range in age from ∼37 to ∼30 Ma and document several phases in the early evolution of crown Hystricognathi and one of its major subclades, Phiomorpha. Here we describe two new genera and species of basal phiomorphs, Birkamys korai and Mubhammys vadumensis, based on rostra and maxillary and mandibular remains from the terminal Eocene (∼34 Ma) Fayum Locality 41 (L-41). Birkamys is the smallest known Paleogene hystricognath, has very simple molars, and, like derived Oligocene-to-Recent phiomorphs (but unlike contemporaneous and older taxa) apparently retained dP(4)∕4 late into life, with no evidence for P(4)∕4 eruption or formation. Mubhammys is very similar in dental morphology to Birkamys, and also shows no evidence for P(4)∕4 formation or eruption, but is considerably larger. Though parsimony analysis with all characters equally weighted places Birkamys and Mubhammys as sister taxa of extant Thryonomys to the exclusion of much younger relatives of that genus, all other methods (standard Bayesian inference, Bayesian "tip-dating," and parsimony analysis with scaled transitions between "fixed" and polymorphic states) place these species in more basal positions within Hystricognathi, as sister taxa of Oligocene-to-Recent phiomorphs. We also employ tip-dating as a means for estimating the ages of early hystricognath-bearing localities, many of which are not well-constrained by geological, geochronological, or biostratigraphic evidence. By simultaneously taking into account phylogeny, evolutionary rates, and uniform priors that appropriately encompass the range of possible ages for fossil localities, dating of tips in this Bayesian framework allows paleontologists to move beyond vague and assumption-laden "stage of evolution" arguments in biochronology to provide relatively rigorous age assessments of poorly-constrained faunas. This approach should become increasingly robust as estimates are combined from multiple independent analyses of distantly related clades, and is broadly applicable across the tree of life; as such it is deserving of paleontologists' close attention. Notably, in the example provided here, hystricognathous rodents from Libya and Namibia that are controversially considered to be of middle Eocene age are instead estimated to be of late Eocene and late Oligocene age, respectively. Finally, we reconstruct the evolution of first lower molar size among Paleogene African hystricognaths using a Bayesian approach; the results of this analysis reconstruct a rapid latest Eocene dwarfing event along the lineage leading to Birkamys.

The tempo and mode of New World monkey evolution and biogeography in the context of phylogenomic analysis.

PubMed

Jameson Kiesling, Natalie M; Yi, Soojin V; Xu, Ke; Gianluca Sperone, F; Wildman, Derek E

2015-01-01

The development and evolution of organisms is heavily influenced by their environment. Thus, understanding the historical biogeography of taxa can provide insights into their evolutionary history, adaptations and trade-offs realized throughout time. In the present study we have taken a phylogenomic approach to infer New World monkey phylogeny, upon which we have reconstructed the biogeographic history of extant platyrrhines. In order to generate sufficient phylogenetic signal within the New World monkey clade, we carried out a large-scale phylogenetic analysis of approximately 40 kb of non-genic genomic DNA sequence in a 36 species subset of extant New World monkeys. Maximum parsimony, maximum likelihood and Bayesian inference analysis all converged on a single optimal tree topology. Divergence dating and biogeographic analysis reconstruct the timing and geographic location of divergence events. The ancestral area reconstruction describes the geographic locations of the last common ancestor of extant platyrrhines and provides insight into key biogeographic events occurring during platyrrhine diversification. Through these analyses we conclude that the diversification of the platyrrhines took place concurrently with the establishment and diversification of the Amazon rainforest. This suggests that an expanding rainforest environment rather than geographic isolation drove platyrrhine diversification. Copyright © 2014 Elsevier Inc. All rights reserved.

Phylogeny of sipunculan worms: A combined analysis of four gene regions and morphology.

PubMed

Schulze, Anja; Cutler, Edward B; Giribet, Gonzalo

2007-01-01

The intra-phyletic relationships of sipunculan worms were analyzed based on DNA sequence data from four gene regions and 58 morphological characters. Initially we analyzed the data under direct optimization using parsimony as optimality criterion. An implied alignment resulting from the direct optimization analysis was subsequently utilized to perform a Bayesian analysis with mixed models for the different data partitions. For this we applied a doublet model for the stem regions of the 18S rRNA. Both analyses support monophyly of Sipuncula and most of the same clades within the phylum. The analyses differ with respect to the relationships among the major groups but whereas the deep nodes in the direct optimization analysis generally show low jackknife support, they are supported by 100% posterior probability in the Bayesian analysis. Direct optimization has been useful for handling sequences of unequal length and generating conservative phylogenetic hypotheses whereas the Bayesian analysis under mixed models provided high resolution in the basal nodes of the tree.

Molecular evolution of the ependymin protein family: a necessary update.

PubMed

Suárez-Castillo, Edna C; García-Arrarás, José E

2007-02-15

Ependymin (Epd), the predominant protein in the cerebrospinal fluid of teleost fishes, was originally associated with neuroplasticity and regeneration. Ependymin-related proteins (Epdrs) have been identified in other vertebrates, including amphibians and mammals. Recently, we reported the identification and characterization of an Epdr in echinoderms, showing that there are ependymin family members in non-vertebrate deuterostomes. We have now explored multiple databases to find Epdrs in different metazoan species. Using these sequences we have performed genome mapping, molecular phylogenetic analyses using Maximum Likelihood and Bayesian methods, and statistical tests of tree topologies, to ascertain the phylogenetic relationship among ependymin proteins. Our results demonstrate that ependymin genes are also present in protostomes. In addition, as a result of the putative fish-specific genome duplication event and posterior divergence, the ependymin family can be divided into four groups according to their amino acid composition and branching pattern in the gene tree: 1) a brain-specific group of ependymin sequences that is unique to teleost fishes and encompasses the originally described ependymin; 2) a group expressed in non-brain tissue in fishes; 3) a group expressed in several tissues that appears to be deuterostome-specific, and 4) a group found in invertebrate deuterostomes and protostomes, with a broad pattern of expression and that probably represents the evolutionary origin of the ependymins. Using codon-substitution models to statistically assess the selective pressures acting over the ependymin protein family, we found evidence of episodic positive Darwinian selection and relaxed selective constraints in each one of the postduplication branches of the gene tree. However, purifying selection (with among-site variability) appears to be the main influence on the evolution of each subgroup within the family. Functional divergence among the ependymin paralog groups is well supported and several amino acid positions are predicted to be critical for this divergence. Ependymin proteins are present in vertebrates, invertebrate deuterostomes, and protostomes. Overall, our analyses suggest that the ependymin protein family is a suitable target to experimentally test subfunctionalization in gene copies that originated after gene or genome duplication events.

Molecular evolution of the ependymin protein family: a necessary update

PubMed Central

Suárez-Castillo, Edna C; García-Arrarás, José E

2007-01-01

Background Ependymin (Epd), the predominant protein in the cerebrospinal fluid of teleost fishes, was originally associated with neuroplasticity and regeneration. Ependymin-related proteins (Epdrs) have been identified in other vertebrates, including amphibians and mammals. Recently, we reported the identification and characterization of an Epdr in echinoderms, showing that there are ependymin family members in non-vertebrate deuterostomes. We have now explored multiple databases to find Epdrs in different metazoan species. Using these sequences we have performed genome mapping, molecular phylogenetic analyses using Maximum Likelihood and Bayesian methods, and statistical tests of tree topologies, to ascertain the phylogenetic relationship among ependymin proteins. Results Our results demonstrate that ependymin genes are also present in protostomes. In addition, as a result of the putative fish-specific genome duplication event and posterior divergence, the ependymin family can be divided into four groups according to their amino acid composition and branching pattern in the gene tree: 1) a brain-specific group of ependymin sequences that is unique to teleost fishes and encompasses the originally described ependymin; 2) a group expressed in non-brain tissue in fishes; 3) a group expressed in several tissues that appears to be deuterostome-specific, and 4) a group found in invertebrate deuterostomes and protostomes, with a broad pattern of expression and that probably represents the evolutionary origin of the ependymins. Using codon-substitution models to statistically assess the selective pressures acting over the ependymin protein family, we found evidence of episodic positive Darwinian selection and relaxed selective constraints in each one of the postduplication branches of the gene tree. However, purifying selection (with among-site variability) appears to be the main influence on the evolution of each subgroup within the family. Functional divergence among the ependymin paralog groups is well supported and several amino acid positions are predicted to be critical for this divergence. Conclusion Ependymin proteins are present in vertebrates, invertebrate deuterostomes, and protostomes. Overall, our analyses suggest that the ependymin protein family is a suitable target to experimentally test subfunctionalization in gene copies that originated after gene or genome duplication events. PMID:17302986

Inferring phylogenetic trees from the knowledge of rare evolutionary events.

PubMed

Hellmuth, Marc; Hernandez-Rosales, Maribel; Long, Yangjing; Stadler, Peter F

2018-06-01

Rare events have played an increasing role in molecular phylogenetics as potentially homoplasy-poor characters. In this contribution we analyze the phylogenetic information content from a combinatorial point of view by considering the binary relation on the set of taxa defined by the existence of a single event separating two taxa. We show that the graph-representation of this relation must be a tree. Moreover, we characterize completely the relationship between the tree of such relations and the underlying phylogenetic tree. With directed operations such as tandem-duplication-random-loss events in mind we demonstrate how non-symmetric information constrains the position of the root in the partially reconstructed phylogeny.

Genetic connectivity of the moth pollinated tree Glionnetia sericea in a highly fragmented habitat.

PubMed

Finger, Aline; Kaiser-Bunbury, Christopher N; Kettle, Chris J; Valentin, Terence; Ghazoul, Jaboury

2014-01-01

Long-distance gene flow is thought to be one prerequisite for the persistence of plant species in fragmented environments. Human influences have led to severe fragmentation of native habitats in the Seychelles islands, with many species surviving only in small and isolated populations. The endangered Seychelles endemic tree Glionnetia sericea is restricted to altitudes between 450 m and 900 m where the native forest vegetation has been largely lost and replaced with exotic invasives over the last 200 years. This study explores the genetic and ecological consequences of population fragmentation in this species by analysing patterns of genetic diversity in a sample of adults, juveniles and seeds, and by using controlled pollination experiments. Our results show no decrease in genetic diversity and no increase in genetic structuring from adult to juvenile cohorts. Despite significant inbreeding in some populations, there is no evidence of higher inbreeding in juvenile cohorts relative to adults. A Bayesian structure analysis and a tentative paternity analysis indicate extensive historical and contemporary gene flow among remnant populations. Pollination experiments and a paternity analysis show that Glionnetia sericea is self-compatible. Nevertheless, outcrossing is present with 7% of mating events resulting from pollen transfer between populations. Artificial pollination provided no evidence for pollen limitation in isolated populations. The highly mobile and specialized hawkmoth pollinators (Agrius convolvuli and Cenophodes tamsi; Sphingidae) appear to promote extensive gene flow, thus mitigating the potential negative ecological and genetic effects of habitat fragmentation in this species. We conclude that contemporary gene flow is sufficient to maintain genetic connectivity in this rare and restricted Seychelles endemic, in contrast to other island endemic tree species with limited contemporary gene flow.

Genetic Connectivity of the Moth Pollinated Tree Glionnetia sericea in a Highly Fragmented Habitat

PubMed Central

Finger, Aline; Valentin, Terence; Ghazoul, Jaboury

2014-01-01

Long-distance gene flow is thought to be one prerequisite for the persistence of plant species in fragmented environments. Human influences have led to severe fragmentation of native habitats in the Seychelles islands, with many species surviving only in small and isolated populations. The endangered Seychelles endemic tree Glionnetia sericea is restricted to altitudes between 450 m and 900 m where the native forest vegetation has been largely lost and replaced with exotic invasives over the last 200 years. This study explores the genetic and ecological consequences of population fragmentation in this species by analysing patterns of genetic diversity in a sample of adults, juveniles and seeds, and by using controlled pollination experiments. Our results show no decrease in genetic diversity and no increase in genetic structuring from adult to juvenile cohorts. Despite significant inbreeding in some populations, there is no evidence of higher inbreeding in juvenile cohorts relative to adults. A Bayesian structure analysis and a tentative paternity analysis indicate extensive historical and contemporary gene flow among remnant populations. Pollination experiments and a paternity analysis show that Glionnetia sericea is self-compatible. Nevertheless, outcrossing is present with 7% of mating events resulting from pollen transfer between populations. Artificial pollination provided no evidence for pollen limitation in isolated populations. The highly mobile and specialized hawkmoth pollinators (Agrius convolvuli and Cenophodes tamsi; Sphingidae) appear to promote extensive gene flow, thus mitigating the potential negative ecological and genetic effects of habitat fragmentation in this species. We conclude that contemporary gene flow is sufficient to maintain genetic connectivity in this rare and restricted Seychelles endemic, in contrast to other island endemic tree species with limited contemporary gene flow. PMID:25347541

Fossils matter: improved estimates of divergence times in Pinus reveal older diversification.

PubMed

Saladin, Bianca; Leslie, Andrew B; Wüest, Rafael O; Litsios, Glenn; Conti, Elena; Salamin, Nicolas; Zimmermann, Niklaus E

2017-04-04

The taxonomy of pines (genus Pinus) is widely accepted and a robust gene tree based on entire plastome sequences exists. However, there is a large discrepancy in estimated divergence times of major pine clades among existing studies, mainly due to differences in fossil placement and dating methods used. We currently lack a dated molecular phylogeny that makes use of the rich pine fossil record, and this study is the first to estimate the divergence dates of pines based on a large number of fossils (21) evenly distributed across all major clades, in combination with applying both node and tip dating methods. We present a range of molecular phylogenetic trees of Pinus generated within a Bayesian framework. We find the origin of crown Pinus is likely up to 30 Myr older (Early Cretaceous) than inferred in most previous studies (Late Cretaceous) and propose generally older divergence times for major clades within Pinus than previously thought. Our age estimates vary significantly between the different dating approaches, but the results generally agree on older divergence times. We present a revised list of 21 fossils that are suitable to use in dating or comparative analyses of pines. Reliable estimates of divergence times in pines are essential if we are to link diversification processes and functional adaptation of this genus to geological events or to changing climates. In addition to older divergence times in Pinus, our results also indicate that node age estimates in pines depend on dating approaches and the specific fossil sets used, reflecting inherent differences in various dating approaches. The sets of dated phylogenetic trees of pines presented here provide a way to account for uncertainties in age estimations when applying comparative phylogenetic methods.

Differential soil water sourcing of managed Loblolly Pine and Sweet Gum revealed by stable isotopes in the Upper Coastal Plain, USA

NASA Astrophysics Data System (ADS)

Brockman, L. E.; Younger, S. E.; Jackson, C. R.; McDonnell, J.; Janzen, K. F.

2017-12-01

Stable isotope signatures of stem water can illuminate where in the soil profile different types of trees are accessing soil water and thereby contribute to our understanding of water movement through the soil plant atmosphere continuum. The objective of this study was to use 2H and 18O isotopes to characterize water sources of fourteen-year-old intensively managed Loblolly Pine and Sweet Gum stands in replicated (n=3) paired plots. In order to differentiate the isotopic signatures of tree and soil water, both species and five soil depths were sampled monthly for one year. Tree sap and soil water were extracted cryogenically and their isotopic signatures were determined. Although plant water uptake is generally considered a non-fractionating process, our dataset suggests a source of fractionation in 2H signatures in both species and during most of the thirteen sampling events. As a result, only the 18O isotopic data were used to determine the vertical distribution of soil water contributions to stem water. Statistically, we grouped the five soil sampling depths into three isotopic horizons. Shallow, intermediate and deep soil represent sampling depths of 0-10cm, 30-70cm and 100-125cm, respectively. These isotopic horizons were used in a direct inference approach and Bayesian mixing model analysis to determine the origin of stem water. In this study, Loblolly Pine used more water from intermediate and deep soil while Sweet Gum used more water from shallow and intermediate soil. In the winter months, January through March, Loblolly Pine transpired primarily deep soil where as Sweet Gum mainly utilized shallow soil for transpiration. These results indicate that both species have opportunistic water use patterns with seasonal variation.

Relating phylogenetic trees to transmission trees of infectious disease outbreaks.

PubMed

Ypma, Rolf J F; van Ballegooijen, W Marijn; Wallinga, Jacco

2013-11-01

Transmission events are the fundamental building blocks of the dynamics of any infectious disease. Much about the epidemiology of a disease can be learned when these individual transmission events are known or can be estimated. Such estimations are difficult and generally feasible only when detailed epidemiological data are available. The genealogy estimated from genetic sequences of sampled pathogens is another rich source of information on transmission history. Optimal inference of transmission events calls for the combination of genetic data and epidemiological data into one joint analysis. A key difficulty is that the transmission tree, which describes the transmission events between infected hosts, differs from the phylogenetic tree, which describes the ancestral relationships between pathogens sampled from these hosts. The trees differ both in timing of the internal nodes and in topology. These differences become more pronounced when a higher fraction of infected hosts is sampled. We show how the phylogenetic tree of sampled pathogens is related to the transmission tree of an outbreak of an infectious disease, by the within-host dynamics of pathogens. We provide a statistical framework to infer key epidemiological and mutational parameters by simultaneously estimating the phylogenetic tree and the transmission tree. We test the approach using simulations and illustrate its use on an outbreak of foot-and-mouth disease. The approach unifies existing methods in the emerging field of phylodynamics with transmission tree reconstruction methods that are used in infectious disease epidemiology.

Paleo-event data standards for dendrochronology

Treesearch

Elaine Kennedy Sutherland; P. Brewer; W. Gross

2017-01-01

Extreme environmental events, such as storm winds, landslides, insect infestations, and wildfire, cause loss of life, resources, and human infrastructure. Disaster riskreduction analysis can be improved with information about past frequency, intensity, and spatial patterns of extreme events. Tree-ring analyses can provide such information: tree rings reflect events as...

A Bayesian technique for improving the sensitivity of the atmospheric neutrino L/E analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blake, A. S. T.; Chapman, J. D.; Thomson, M. A.

Tmore » his paper outlines a method for improving the precision of atmospheric neutrino oscillation measurements. One experimental signature for these oscillations is an observed deficit in the rate of ν μ charged-current interactions with an oscillatory dependence on L ν / E ν , where L ν is the neutrino propagation distance and E mrow is="true"> ν is the neutrino energy. For contained-vertex atmospheric neutrino interactions, the L ν / E ν resolution varies significantly from event to event. he precision of the oscillation measurement can be improved by incorporating information on L ν / E ν resolution into the oscillation analysis. In the analysis presented here, a Bayesian technique is used to estimate the L ν / E ν resolution of observed atmospheric neutrinos on an event-by-event basis. By separating the events into bins of L ν / E ν resolution in the oscillation analysis, a significant improvement in oscillation sensitivity can be achieved.« less

Bayesian Analysis of Evolutionary Divergence with Genomic Data under Diverse Demographic Models.

PubMed

Chung, Yujin; Hey, Jody

2017-06-01

We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation-with-Migration framework. The new method implements a 2-step analysis, with an initial Markov chain Monte Carlo (MCMC) phase that samples simple coalescent trees, followed by the calculation of the joint posterior density for the parameters of a demographic model. In step 1, the MCMC sampling phase, the method uses a reduced state space, consisting of coalescent trees without migration paths, and a simple importance sampling distribution without the demography of interest. Once obtained, a single sample of trees can be used in step 2 to calculate the joint posterior density for model parameters under multiple diverse demographic models, without having to repeat MCMC runs. Because migration paths are not included in the state space of the MCMC phase, but rather are handled by analytic integration in step 2 of the analysis, the method is scalable to a large number of loci with excellent MCMC mixing properties. With an implementation of the new method in the computer program MIST, we demonstrate the method's accuracy, scalability, and other advantages using simulated data and DNA sequences of two common chimpanzee subspecies: Pan troglodytes (P. t.) troglodytes and P. t. verus. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Postglacial recolonization history of the European crabapple (Malus sylvestris Mill.), a wild contributor to the domesticated apple.

PubMed

Cornille, A; Giraud, T; Bellard, C; Tellier, A; Le Cam, B; Smulders, M J M; Kleinschmit, J; Roldan-Ruiz, I; Gladieux, P

2013-04-01

Understanding the way in which the climatic oscillations of the Quaternary Period have shaped the distribution and genetic structure of extant tree species provides insight into the processes driving species diversification, distribution and survival. Deciphering the genetic consequences of past climatic change is also critical for the conservation and sustainable management of forest and tree genetic resources, a timely endeavour as the Earth heads into a period of fast climate change. We used a combination of genetic data and ecological niche models to investigate the historical patterns of biogeographic range expansion of a wild fruit tree, the European crabapple (Malus sylvestris), a wild contributor to the domesticated apple. Both climatic predictions for the last glacial maximum and analyses of microsatellite variation indicated that M. sylvestris experienced range contraction and fragmentation. Bayesian clustering analyses revealed a clear pattern of genetic structure, with one genetic cluster spanning a large area in Western Europe and two other genetic clusters with a more limited distribution range in Eastern Europe, one around the Carpathian Mountains and the other restricted to the Balkan Peninsula. Approximate Bayesian computation appeared to be a powerful technique for inferring the history of these clusters, supporting a scenario of simultaneous differentiation of three separate glacial refugia. Admixture between these three populations was found in their suture zones. A weak isolation by distance pattern was detected within each population, indicating a high extent of historical gene flow for the European crabapple. © 2013 Blackwell Publishing Ltd.

Assessment of phylogenetic sensitivity for reconstructing HIV-1 epidemiological relationships.

PubMed

Beloukas, Apostolos; Magiorkinis, Emmanouil; Magiorkinis, Gkikas; Zavitsanou, Asimina; Karamitros, Timokratis; Hatzakis, Angelos; Paraskevis, Dimitrios

2012-06-01

Phylogenetic analysis has been extensively used as a tool for the reconstruction of epidemiological relations for research or for forensic purposes. It was our objective to assess the sensitivity of different phylogenetic methods and various phylogenetic programs to reconstruct epidemiological links among HIV-1 infected patients that is the probability to reveal a true transmission relationship. Multiple datasets (90) were prepared consisting of HIV-1 sequences in protease (PR) and partial reverse transcriptase (RT) sampled from patients with documented epidemiological relationship (target population), and from unrelated individuals (control population) belonging to the same HIV-1 subtype as the target population. Each dataset varied regarding the number, the geographic origin and the transmission risk groups of the sequences among the control population. Phylogenetic trees were inferred by neighbor-joining (NJ), maximum likelihood heuristics (hML) and Bayesian methods. All clusters of sequences belonging to the target population were correctly reconstructed by NJ and Bayesian methods receiving high bootstrap and posterior probability (PP) support, respectively. On the other hand, TreePuzzle failed to reconstruct or provide significant support for several clusters; high puzzling step support was associated with the inclusion of control sequences from the same geographic area as the target population. In contrary, all clusters were correctly reconstructed by hML as implemented in PhyML 3.0 receiving high bootstrap support. We report that under the conditions of our study, hML using PhyML, NJ and Bayesian methods were the most sensitive for the reconstruction of epidemiological links mostly from sexually infected individuals. Copyright © 2012 Elsevier B.V. All rights reserved.

Functional Multi-Locus QTL Mapping of Temporal Trends in Scots Pine Wood Traits

PubMed Central

Li, Zitong; Hallingbäck, Henrik R.; Abrahamsson, Sara; Fries, Anders; Gull, Bengt Andersson; Sillanpää, Mikko J.; García-Gil, M. Rosario

2014-01-01

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals. PMID:25305041

Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.

PubMed

Li, Zitong; Hallingbäck, Henrik R; Abrahamsson, Sara; Fries, Anders; Gull, Bengt Andersson; Sillanpää, Mikko J; García-Gil, M Rosario

2014-10-09

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals. Copyright © 2014 Li et al.

Bayesian reconstruction of the evolutionary history and cross-species transition of variola virus and orthopoxviruses.

PubMed

Zehender, Gianguglielmo; Lai, Alessia; Veo, Carla; Bergna, Annalisa; Ciccozzi, Massimo; Galli, Massimo

2018-06-01

Variola virus (VARV), the causative agent of smallpox, is an exclusively human virus belonging to the genus Orthopoxvirus, which includes many other viral species covering a wide range of mammal hosts, such as vaccinia, cowpox, camelpox, taterapox, ectromelia, and monkeypox virus. The tempo and mode of evolution of Orthopoxviruses were reconstructed using a Bayesian phylodynamic framework by analysing 80 hemagglutinin sequences retrieved from public databases. Bayesian phylogeography was used to estimate their putative ancestral hosts. In order to estimate the substitution rate, the tree including all of the available Orthopoxviruses was calibrated using historical references dating the South American variola minor clade (alastrim) to between the XVI and XIX century. The mean substitution rate determined by the analysis was 6.5 × 10 -6 substitutions/site/year. Based on this evolutionary estimate, the time of the most recent common ancestor of the genus Orthopoxvirus was placed at about 10 000 years before the present. Cowpox virus was the species closest to the root of the phylogenetic tree. The root of VARV circulating in the XX century was estimated to be about 700 years ago, corresponding to about 1300 AD. The divergence between West African and South American VARV went back about 500 years ago (falling approximately in the XVI century). A rodent species is the most probable ancestral host from which the ancestors of all the known Orthopoxviruses were transmitted to the other mammal host species, and each of these species represented a dead-end for each new poxvirus species, without any further inter-specific spread. © 2018 Wiley Periodicals, Inc.

Dynamic Event Tree advancements and control logic improvements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alfonsi, Andrea; Rabiti, Cristian; Mandelli, Diego

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN is currently equipped with three different sampling categories: Forward samplers (Monte Carlo, Latin Hyper Cube, Stratified, Grid Sampler, Factorials, etc.), Adaptive Samplers (Limit Surface search, Adaptive Polynomial Chaos, etc.) and Dynamic Event Tree (DET) samplers (Deterministic and Adaptive Dynamic Event Trees). The main subject of this document is to report the activities that have been donemore » in order to: start the migration of the RAVEN/RELAP-7 control logic system into MOOSE, and develop advanced dynamic sampling capabilities based on the Dynamic Event Tree approach. In order to provide to all MOOSE-based applications a control logic capability, in this Fiscal Year an initial migration activity has been initiated, moving the control logic system, designed for RELAP-7 by the RAVEN team, into the MOOSE framework. In this document, a brief explanation of what has been done is going to be reported. The second and most important subject of this report is about the development of a Dynamic Event Tree (DET) sampler named “Hybrid Dynamic Event Tree” (HDET) and its Adaptive variant “Adaptive Hybrid Dynamic Event Tree” (AHDET). As other authors have already reported, among the different types of uncertainties, it is possible to discern two principle types: aleatory and epistemic uncertainties. The classical Dynamic Event Tree is in charge of treating the first class (aleatory) uncertainties; the dependence of the probabilistic risk assessment and analysis on the epistemic uncertainties are treated by an initial Monte Carlo sampling (MCDET). From each Monte Carlo sample, a DET analysis is run (in total, N trees). The Monte Carlo employs a pre-sampling of the input space characterized by epistemic uncertainties. The consequent Dynamic Event Tree performs the exploration of the aleatory space. In the RAVEN code, a more general approach has been developed, not limiting the exploration of the epistemic space through a Monte Carlo method but using all the forward sampling strategies RAVEN currently employs. The user can combine a Latin Hyper Cube, Grid, Stratified and Monte Carlo sampling in order to explore the epistemic space, without any limitation. From this pre-sampling, the Dynamic Event Tree sampler starts its aleatory space exploration. As reported by the authors, the Dynamic Event Tree is a good fit to develop a goal-oriented sampling strategy. The DET is used to drive a Limit Surface search. The methodology that has been developed by the authors last year, performs a Limit Surface search in the aleatory space only. This report documents how this approach has been extended in order to consider the epistemic space interacting with the Hybrid Dynamic Event Tree methodology.« less

36 CFR 292.46 - Timber harvesting activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... hazard trees; or to respond to natural events such as wildfire, flood, earthquake, volcanic eruption, high winds, and disease or insect infestation. (2) Where authorized, trees may be harvested by... trees, or to respond to natural events provided that the activity is consistent with the Wild and Scenic...

Distributed Events in Sentinel: Design and Implementation of a Global Event Detector

DTIC Science & Technology

1999-01-01

local event detector and a global event detector to detect events. Global event detector in this case plays the role of a message sending/receiving than...significant in this case . The system performance will decrease with increase in the number of applications involved in global event detection. Yet from a...Figure 8: A Global event tree (2) 1. Global composite event is detected at the GED In this case , the whole global composite event tree is sent to the

Mapping pre-European settlement vegetation at fine resolutions using a hierarchical Bayesian model and GIS

Treesearch

Hong S. He; Daniel C. Dey; Xiuli Fan; Mevin B. Hooten; John M. Kabrick; Christopher K. Wikle; Zhaofei. Fan

2007-01-01

In the Midwestern United States, the GeneralLandOffice (GLO) survey records provide the only reasonably accurate data source of forest composition and tree species distribution at the time of pre-European settlement (circa late 1800 to early 1850). However, GLO data have two fundamental limitations: coarse spatial resolutions (the square mile section and half mile...

Reducing uncertainty in Climate Response Time Scale by Bayesian Analysis of the 8.2 ka event

NASA Astrophysics Data System (ADS)

Lorenz, A.; Held, H.; Bauer, E.; Schneider von Deimling, T.

2009-04-01

We analyze the possibility of uncertainty reduction in Climate Response Time Scale by utilizing Greenland ice-core data that contain the 8.2 ka event within a Bayesian model-data intercomparison with the Earth system model of intermediate complexity, CLIMBER-2.3. Within a stochastic version of the model it has been possible to mimic the 8.2 ka event within a plausible experimental setting and with relatively good accuracy considering the timing of the event in comparison to other modeling exercises [1]. The simulation of the centennial cold event is effectively determined by the oceanic cooling rate which depends largely on the ocean diffusivity described by diffusion coefficients of relatively wide uncertainty ranges. The idea now is to discriminate between the different values of diffusivities according to their likelihood to rightly represent the duration of the 8.2 ka event and thus to exploit the paleo data to constrain uncertainty in model parameters in analogue to [2]. Implementing this inverse Bayesian Analysis with this model the technical difficulty arises to establish the related likelihood numerically in addition to the uncertain model parameters: While mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study [3] the Bayesian Analysis showed a reduction of uncertainty in vertical ocean diffusivity parameters of factor 2 compared to prior knowledge. This learning effect on the model parameters is propagated to other model outputs of interest; e.g. the inverse ocean heat capacity, which is important for the dominant time scale of climate response to anthropogenic forcing which, in combination with climate sensitivity, strongly influences the climate systems reaction for the near- and medium-term future. 1 References [1] E. Bauer, A. Ganopolski, M. Montoya: Simulation of the cold climate event 8200 years ago by meltwater outburst from lake Agassiz. Paleoceanography 19:PA3014, (2004) [2] T. Schneider von Deimling, H. Held, A. Ganopolski, S. Rahmstorf, Climate sensitivity estimated from ensemble simulations of glacial climates, Climate Dynamics 27, 149-163, DOI 10.1007/s00382-006-0126-8 (2006). [3] A. Lorenz, Diploma Thesis, U Potsdam (2007).

The mitochondrial genome of Elodia flavipalpis Aldrich (Diptera: Tachinidae) and the evolutionary timescale of Tachinid flies.

PubMed

Zhao, Zhe; Su, Tian-Juan; Chesters, Douglas; Wang, Shi-di; Ho, Simon Y W; Zhu, Chao-Dong; Chen, Xiao-Lin; Zhang, Chun-Tian

2013-01-01

Tachinid flies are natural enemies of many lepidopteran and coleopteran pests of forests, crops, and fruit trees. In order to address the lack of genetic data in this economically important group, we sequenced the complete mitochondrial genome of the Palaearctic tachinid fly Elodia flavipalpis Aldrich, 1933. Usually found in Northern China and Japan, this species is one of the primary natural enemies of the leaf-roller moths (Tortricidae), which are major pests of various fruit trees. The 14,932-bp mitochondrial genome was typical of Diptera, with 13 protein-coding genes, 22 tRNA genes, and 2 rRNA genes. However, its control region is only 105 bp in length, which is the shortest found so far in flies. In order to estimate dipteran evolutionary relationships, we conducted a phylogenetic analysis of 58 mitochondrial genomes from 23 families. Maximum-likelihood and Bayesian methods supported the monophyly of both Tachinidae and superfamily Oestroidea. Within the subsection Calyptratae, Muscidae was inferred as the sister group to Oestroidea. Within Oestroidea, Calliphoridae and Sarcophagidae formed a sister clade to Oestridae and Tachinidae. Using a Bayesian relaxed clock calibrated with fossil data, we estimated that Tachinidae originated in the middle Eocene.

The Mitochondrial Genome of Elodia flavipalpis Aldrich (Diptera: Tachinidae) and the Evolutionary Timescale of Tachinid Flies

PubMed Central

Zhao, Zhe; Su, Tian-juan; Chesters, Douglas; Wang, Shi-di; Ho, Simon Y. W.; Zhu, Chao-dong; Chen, Xiao-lin; Zhang, Chun-tian

2013-01-01

Tachinid flies are natural enemies of many lepidopteran and coleopteran pests of forests, crops, and fruit trees. In order to address the lack of genetic data in this economically important group, we sequenced the complete mitochondrial genome of the Palaearctic tachinid fly Elodia flavipalpis Aldrich, 1933. Usually found in Northern China and Japan, this species is one of the primary natural enemies of the leaf-roller moths (Tortricidae), which are major pests of various fruit trees. The 14,932-bp mitochondrial genome was typical of Diptera, with 13 protein-coding genes, 22 tRNA genes, and 2 rRNA genes. However, its control region is only 105 bp in length, which is the shortest found so far in flies. In order to estimate dipteran evolutionary relationships, we conducted a phylogenetic analysis of 58 mitochondrial genomes from 23 families. Maximum-likelihood and Bayesian methods supported the monophyly of both Tachinidae and superfamily Oestroidea. Within the subsection Calyptratae, Muscidae was inferred as the sister group to Oestroidea. Within Oestroidea, Calliphoridae and Sarcophagidae formed a sister clade to Oestridae and Tachinidae. Using a Bayesian relaxed clock calibrated with fossil data, we estimated that Tachinidae originated in the middle Eocene. PMID:23626734

Constructing event trees for volcanic crises

USGS Publications Warehouse

Newhall, C.; Hoblitt, R.

2002-01-01

Event trees are useful frameworks for discussing probabilities of possible outcomes of volcanic unrest. Each branch of the tree leads from a necessary prior event to a more specific outcome, e.g., from an eruption to a pyroclastic flow. Where volcanic processes are poorly understood, probability estimates might be purely empirical - utilizing observations of past and current activity and an assumption that the future will mimic the past or follow a present trend. If processes are better understood, probabilities might be estimated from a theoritical model, either subjectively or by numerical simulations. Use of Bayes' theorem aids in the estimation of how fresh unrest raises (or lowers) the probabilities of eruptions. Use of event trees during volcanic crises can help volcanologists to critically review their analysis of hazard, and help officials and individuals to compare volcanic risks with more familiar risks. Trees also emphasize the inherently probabilistic nature of volcano forecasts, with multiple possible outcomes.

Data Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powell, Danny H; Elwood Jr, Robert H

2011-01-01

Analysis of the material protection, control, and accountability (MPC&A) system is necessary to understand the limits and vulnerabilities of the system to internal threats. A self-appraisal helps the facility be prepared to respond to internal threats and reduce the risk of theft or diversion of nuclear material. The material control and accountability (MC&A) system effectiveness tool (MSET) fault tree was developed to depict the failure of the MPC&A system as a result of poor practices and random failures in the MC&A system. It can also be employed as a basis for assessing deliberate threats against a facility. MSET uses faultmore » tree analysis, which is a top-down approach to examining system failure. The analysis starts with identifying a potential undesirable event called a 'top event' and then determining the ways it can occur (e.g., 'Fail To Maintain Nuclear Materials Under The Purview Of The MC&A System'). The analysis proceeds by determining how the top event can be caused by individual or combined lower level faults or failures. These faults, which are the causes of the top event, are 'connected' through logic gates. The MSET model uses AND-gates and OR-gates and propagates the effect of event failure using Boolean algebra. To enable the fault tree analysis calculations, the basic events in the fault tree are populated with probability risk values derived by conversion of questionnaire data to numeric values. The basic events are treated as independent variables. This assumption affects the Boolean algebraic calculations used to calculate results. All the necessary calculations are built into the fault tree codes, but it is often useful to estimate the probabilities manually as a check on code functioning. The probability of failure of a given basic event is the probability that the basic event primary question fails to meet the performance metric for that question. The failure probability is related to how well the facility performs the task identified in that basic event over time (not just one performance or exercise). Fault tree calculations provide a failure probability for the top event in the fault tree. The basic fault tree calculations establish a baseline relative risk value for the system. This probability depicts relative risk, not absolute risk. Subsequent calculations are made to evaluate the change in relative risk that would occur if system performance is improved or degraded. During the development effort of MSET, the fault tree analysis program used was SAPHIRE. SAPHIRE is an acronym for 'Systems Analysis Programs for Hands-on Integrated Reliability Evaluations.' Version 1 of the SAPHIRE code was sponsored by the Nuclear Regulatory Commission in 1987 as an innovative way to draw, edit, and analyze graphical fault trees primarily for safe operation of nuclear power reactors. When the fault tree calculations are performed, the fault tree analysis program will produce several reports that can be used to analyze the MPC&A system. SAPHIRE produces reports showing risk importance factors for all basic events in the operational MC&A system. The risk importance information is used to examine the potential impacts when performance of certain basic events increases or decreases. The initial results produced by the SAPHIRE program are considered relative risk values. None of the results can be interpreted as absolute risk values since the basic event probability values represent estimates of risk associated with the performance of MPC&A tasks throughout the material balance area (MBA). The RRR for a basic event represents the decrease in total system risk that would result from improvement of that one event to a perfect performance level. Improvement of the basic event with the greatest RRR value produces a greater decrease in total system risk than improvement of any other basic event. Basic events with the greatest potential for system risk reduction are assigned performance improvement values, and new fault tree calculations show the improvement in total system risk. The operational impact or cost-effectiveness from implementing the performance improvements can then be evaluated. The improvements being evaluated can be system performance improvements, or they can be potential, or actual, upgrades to the system. The RIR for a basic event represents the increase in total system risk that would result from failure of that one event. Failure of the basic event with the greatest RIR value produces a greater increase in total system risk than failure of any other basic event. Basic events with the greatest potential for system risk increase are assigned failure performance values, and new fault tree calculations show the increase in total system risk. This evaluation shows the importance of preventing performance degradation of the basic events. SAPHIRE identifies combinations of basic events where concurrent failure of the events results in failure of the top event.« less

Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees.

PubMed

Stolzer, Maureen; Lai, Han; Xu, Minli; Sathaye, Deepa; Vernot, Benjamin; Durand, Dannie

2012-09-15

Gene duplication (D), transfer (T), loss (L) and incomplete lineage sorting (I) are crucial to the evolution of gene families and the emergence of novel functions. The history of these events can be inferred via comparison of gene and species trees, a process called reconciliation, yet current reconciliation algorithms model only a subset of these evolutionary processes. We present an algorithm to reconcile a binary gene tree with a nonbinary species tree under a DTLI parsimony criterion. This is the first reconciliation algorithm to capture all four evolutionary processes driving tree incongruence and the first to reconcile non-binary species trees with a transfer model. Our algorithm infers all optimal solutions and reports complete, temporally feasible event histories, giving the gene and species lineages in which each event occurred. It is fixed-parameter tractable, with polytime complexity when the maximum species outdegree is fixed. Application of our algorithms to prokaryotic and eukaryotic data show that use of an incomplete event model has substantial impact on the events inferred and resulting biological conclusions. Our algorithms have been implemented in Notung, a freely available phylogenetic reconciliation software package, available at http://www.cs.cmu.edu/~durand/Notung. mstolzer@andrew.cmu.edu.

The FTA Method And A Possibility Of Its Application In The Area Of Road Freight Transport

NASA Astrophysics Data System (ADS)

Poliaková, Adela

2015-06-01

The Fault Tree process utilizes logic diagrams to portray and analyse potentially hazardous events. Three basic symbols (logic gates) are adequate for diagramming any fault tree. However, additional recently developed symbols can be used to reduce the time and effort required for analysis. A fault tree is a graphical representation of the relationship between certain specific events and the ultimate undesired event (2). This paper deals to method of Fault Tree Analysis basic description and provides a practical view on possibility of application by quality improvement in road freight transport company.

Development of a Bayesian Belief Network Runway Incursion and Excursion Model

NASA Technical Reports Server (NTRS)

Green, Lawrence L.

2014-01-01

In a previous work, a statistical analysis of runway incursion (RI) event data was conducted to ascertain the relevance of this data to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to several of the AvSP top ten TC and identified numerous primary causes and contributing factors of RI events. The statistical analysis served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events, also previously reported. Through literature searches and data analysis, this RI event network has now been extended to also model runway excursion (RE) events. These RI and RE event networks have been further modified and vetted by a Subject Matter Expert (SME) panel. The combined system-level BBN model will allow NASA to generically model the causes of RI and RE events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of runway safety incidents/accidents, and to improve runway safety in general. The development and structure of the BBN for both RI and RE events are documented in this paper.

Early changes in physical tree characteristics during an oak decline event in the Ozark highlands

Treesearch

Martin A. Spetich

2006-01-01

An oak decline event is severely affecting up to 120 000 ha in the Ozark National Forest of Arkansas. Results of early changes in physical tree characteristics during that event are presented. In the fall and winter of 1999 and 2000, we established research plots on a site that would become a center of severe oak decline. In August 2000, standing trees > 14 cm in...

Modeling decay rates of dead wood in a neotropical forest.

PubMed

Hérault, Bruno; Beauchêne, Jacques; Muller, Félix; Wagner, Fabien; Baraloto, Christopher; Blanc, Lilian; Martin, Jean-Michel

2010-09-01

Variation of dead wood decay rates among tropical trees remains one source of uncertainty in global models of the carbon cycle. Taking advantage of a broad forest plot network surveyed for tree mortality over a 23-year period, we measured the remaining fraction of boles from 367 dead trees from 26 neotropical species widely varying in wood density (0.23-1.24 g cm(-3)) and tree circumference at death time (31.5-272.0 cm). We modeled decay rates within a Bayesian framework assuming a first order differential equation to model the decomposition process and tested for the effects of forest management (selective logging vs. unexploited), of mode of death (standing vs. downed) and of topographical levels (bottomlands vs. hillsides vs. hilltops) on wood decay rates. The general decay model predicts the observed remaining fraction of dead wood (R2 = 60%) with only two biological predictors: tree circumference at death time and wood specific density. Neither selective logging nor local topography had a differential effect on wood decay rates. Including the mode of death into the model revealed that standing dead trees decomposed faster than downed dead trees, but the gain of model accuracy remains rather marginal. Overall, these results suggest that the release of carbon from tropical dead trees to the atmosphere can be simply estimated using tree circumference at death time and wood density.

Restricted Gene Flow among Hospital Subpopulations of Enterococcus faecium

PubMed Central

Willems, Rob J. L.; Top, Janetta; van Schaik, Willem; Leavis, Helen; Bonten, Marc; Sirén, Jukka; Hanage, William P.; Corander, Jukka

2012-01-01

ABSTRACT Enterococcus faecium has recently emerged as an important multiresistant nosocomial pathogen. Defining population structure in this species is required to provide insight into the existence, distribution, and dynamics of specific multiresistant or pathogenic lineages in particular environments, like the hospital. Here, we probe the population structure of E. faecium using Bayesian-based population genetic modeling implemented in Bayesian Analysis of Population Structure (BAPS) software. The analysis involved 1,720 isolates belonging to 519 sequence types (STs) (491 for E. faecium and 28 for Enterococcus faecalis). E. faecium isolates grouped into 13 BAPS (sub)groups, but the large majority (80%) of nosocomial isolates clustered in two subgroups (2-1 and 3-3). Phylogenetic and eBURST analysis of BAPS groups 2 and 3 confirmed the existence of three separate hospital lineages (17, 18, and 78), highlighting different evolutionary trajectories for BAPS 2-1 (lineage 78) and 3-3 (lineage 17 and lineage 18) isolates. Phylogenomic analysis of 29 E. faecium isolates showed agreement between BAPS assignment of STs and their relative positions in the phylogenetic tree. Odds ratio calculation confirmed the significant association between hospital isolates with BAPS 3-3 and lineages 17, 18, and 78. Admixture analysis showed a scarce number of recombination events between the different BAPS groups. For the E. faecium hospital population, we propose an evolutionary model in which strains with a high propensity to colonize and infect hospitalized patients arise through horizontal gene transfer. Once adapted to the distinct hospital niche, this subpopulation becomes isolated, and recombination with other populations declines. PMID:22807567

75 FR 66125 - Notice of Public Meeting and Request for Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-27

...--The National Christmas Tree Lighting and the subsequent 23 day event. SUMMARY: The National Park Service is seeking public comments and suggestions on the planning of the 2010 National Christmas Tree... Christmas Tree Lighting and the subsequent 23 day event, which opens on December 9, 2010, on the Ellipse...

The influence of tree traits and storm event characteristics on stemflow production from isolated deciduous trees in an urban park

NASA Astrophysics Data System (ADS)

Carlyle-Moses, D. E.; Schooling, J. T.

2014-12-01

Urban tree canopy processes affect the volume and biogeochemistry of inputs to the hydrological cycle in cities. We studied stemflow from 37 isolated deciduous trees in an urban park in Kamloops, British Columbia which has a semi-arid climate dominated by small precipitation events. Precipitation and stemflow were measured on an event basis from June 12, 2012 to November 3, 2013. To clarify the effect of canopy traits on stemflow thresholds, rates, yields, percent, and funneling ratios, we analyzed branch angles, bark roughness, tree size, cover, leaf size, and branch and leader counts. High branch angles promoted stemflow in all trees, while bark roughness influenced stemflow differently for single- and multi-leader trees. The association between stemflow and numerous leaders deserves further study. Columnar-form trees often partitioned a large percentage of precipitation into stemflow, with event-scale values as high as 27.9 % recorded for an Armstrong Freeman Maple (Acer x freemanii 'Armstrong'). Under growing-season conditions funneling ratios as high as 196.9 were derived for an American Beech (Fagus grandifolia) individual. Among meteorological variables, rain depth was strongly correlated with stemflow yields; intra-storm break duration, rainfall intensity, rainfall inclination, wind speed, and vapour pressure deficit also played roles. Greater stemflow was associated with leafless canopies and with rain or mixed events versus snow. Results can inform climate-sensitive selection and siting of urban trees towards integrated rainwater management. For example, previous studies suggest that the reduction in storm-water generation by urban trees is accomplished through canopy interception loss alone. However, trees that partition large quantities of precipitation canopy-drainage as stemflow to the base of their trunks, where it has the potential to infiltrate into the soil media rather than fall on impervious surfaces as throughfall, may assist in reducing stormwater flow.

Impacts of a water stress followed by an early frost event on beech (Fagus sylvatica L.) susceptibility to Scolytine ambrosia beetles - Research strategy and first results

NASA Astrophysics Data System (ADS)

La Spina, Sylvie; de Cannière, Charles; Molenberg, Jean-Marc; Vincke, Caroline; Deman, Déborah; Grégoire, Jean-Claude

2010-05-01

Climate change tends to induce more frequent abiotic and biotic extreme events, having large impacts on tree vitality. Weakened trees are then more susceptible to secondary insect outbreaks, as it happened in Belgium in the early 2000s: after an early frost event, secondary Scolytine ambrosia beetles attacks were observed on beech trees. In this study, we test if a combination of stress, i.e. a soil water deficit preceding an early frost, could render trees more attractive to beetles. An experimental study was set in autumn 2008. Two parcels of a beech forest were covered with plastic tents to induce a water stress by rain interception. The parcels were surrounded by 2-meters depth trenches to avoid water supply by streaming. Soil water content and different indicators of tree water use (sap flow, predawn leaf water potential, tree radial growth) were followed. In autumn 2010, artificial frost injuries will be inflicted to trees using dry ice. Trees attractivity for Scolytine insects, and the success of insect colonization will then be studied. The poster will focus on experiment setting and first results (impacts of soil water deficit on trees).

A Bayesian network model to assess the public health risk associated with wet weather sewer overflows discharging into waterways.

PubMed

Goulding, R; Jayasuriya, N; Horan, E

2012-10-15

Overflows from sanitary sewers during wet weather, which occur when the hydraulic capacity of the sewer system is exceeded, are considered a potential threat to the ecological and public health of the waterways which receive these overflows. As a result, water retailers in Australia and internationally commit significant resources to manage and abate sewer overflows. However, whilst some studies have contributed to an increased understanding of the impacts and risks associated with these events, they are relatively few in number and there still is a general lack of knowledge in this area. A Bayesian network model to assess the public health risk associated with wet weather sewer overflows is presented in this paper. The Bayesian network approach is shown to provide significant benefits in the assessment of public health risks associated with wet weather sewer overflows. In particular, the ability for the model to account for the uncertainty inherent in sewer overflow events and subsequent impacts through the use of probabilities is a valuable function. In addition, the paper highlights the benefits of the probabilistic inference function of the Bayesian network in prioritising management options to minimise public health risks associated with sewer overflows. Copyright © 2012. Published by Elsevier Ltd.

A Comparative Study of Data Mining Techniques on Football Match Prediction

NASA Astrophysics Data System (ADS)

Rosli, Che Mohamad Firdaus Che Mohd; Zainuri Saringat, Mohd; Razali, Nazim; Mustapha, Aida

2018-05-01

Data prediction have become a trend in today’s business or organization. This paper is set to predict match outcomes for association football from the perspective of football club managers and coaches. This paper explored different data mining techniques used for predicting the match outcomes where the target class is win, draw and lose. The main objective of this research is to find the most accurate data mining technique that fits the nature of football data. The techniques tested are Decision Trees, Neural Networks, Bayesian Network, and k-Nearest Neighbors. The results from the comparative experiments showed that Decision Trees produced the highest average prediction accuracy in the domain of football match prediction by 99.56%.

Impact assessment of extreme storm events using a Bayesian network

USGS Publications Warehouse

den Heijer, C.(Kees); Knipping, Dirk T.J.A.; Plant, Nathaniel G.; van Thiel de Vries, Jaap S. M.; Baart, Fedor; van Gelder, Pieter H. A. J. M.

2012-01-01

This paper describes an investigation on the usefulness of Bayesian Networks in the safety assessment of dune coasts. A network has been created that predicts the erosion volume based on hydraulic boundary conditions and a number of cross-shore profile indicators. Field measurement data along a large part of the Dutch coast has been used to train the network. Corresponding storm impact on the dunes was calculated with an empirical dune erosion model named duros+. Comparison between the Bayesian Network predictions and the original duros+ results, here considered as observations, results in a skill up to 0.88, provided that the training data covers the range of predictions. Hence, the predictions from a deterministic model (duros+) can be captured in a probabilistic model (Bayesian Network) such that both the process knowledge and uncertainties can be included in impact and vulnerability assessments.

Influence of gene flow on divergence dating - implications for the speciation history of Takydromus grass lizards.

PubMed

Tseng, Shu-Ping; Li, Shou-Hsien; Hsieh, Chia-Hung; Wang, Hurng-Yi; Lin, Si-Min

2014-10-01

Dating the time of divergence and understanding speciation processes are central to the study of the evolutionary history of organisms but are notoriously difficult. The difficulty is largely rooted in variations in the ancestral population size or in the genealogy variation across loci. To depict the speciation processes and divergence histories of three monophyletic Takydromus species endemic to Taiwan, we sequenced 20 nuclear loci and combined with one mitochondrial locus published in GenBank. They were analysed by a multispecies coalescent approach within a Bayesian framework. Divergence dating based on the gene tree approach showed high variation among loci, and the divergence was estimated at an earlier date than when derived by the species-tree approach. To test whether variations in the ancestral population size accounted for the majority of this variation, we conducted computer inferences using isolation-with-migration (IM) and approximate Bayesian computation (ABC) frameworks. The results revealed that gene flow during the early stage of speciation was strongly favoured over the isolation model, and the initiation of the speciation process was far earlier than the dates estimated by gene- and species-based divergence dating. Due to their limited dispersal ability, it is suggested that geographical isolation may have played a major role in the divergence of these Takydromus species. Nevertheless, this study reveals a more complex situation and demonstrates that gene flow during the speciation process cannot be overlooked and may have a great impact on divergence dating. By using multilocus data and incorporating Bayesian coalescence approaches, we provide a more biologically realistic framework for delineating the divergence history of Takydromus. © 2014 John Wiley & Sons Ltd.

Emerging Concepts of Data Integration in Pathogen Phylodynamics.

PubMed

Baele, Guy; Suchard, Marc A; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.

The genetic diversity of hepatitis A genotype I in Bulgaria

PubMed Central

Cella, Eleonora; Golkocheva-Markova, Elitsa N.; Trandeva-Bankova, Diljana; Gregori, Giulia; Bruni, Roberto; Taffon, Stefania; Equestre, Michele; Costantino, Angela; Spoto, Silvia; Curtis, Melissa; Ciccaglione, Anna Rita; Ciccozzi, Massimo; Angeletti, Silvia

2018-01-01

Abstract The purpose of this study was to analyze sequences of hepatitis A virus (HAV) Ia and Ib genotypes from Bulgarian patients to investigate the molecular epidemiology of HAV genotype I during the years 2012 to 2014. Around 105 serum samples were collected by the Department of Virology of the National Center of Infectious and Parasitic Diseases in Bulgaria. The sequenced region encompassed the VP1/2A region of HAV genome. The sequences obtained from the samples were 103. For the phylogenetic analyses, 5 datasets were built to investigate the viral gene in/out flow among distinct HAV subpopulations in different geographic areas and to build a Bayesian dated tree, Bayesian phylogenetic and migration pattern analyses were performed. HAV Ib Bulgarian sequences mostly grouped into a single clade. This indicates that the Bulgarian epidemic is partially compartmentalized. It originated from a limited number of viruses and then spread through fecal-oral local transmission. HAV Ia Bulgarian sequences were intermixed with European sequences, suggesting that an Ia epidemic is not restricted to Bulgaria but can affect other European countries. The time-scaled phylogeny reconstruction showed the root of the tree dating in 2008 for genotype Ib and in 1999 for genotype Ia with a second epidemic entrance in 2003. The Bayesian skyline plot for genotype Ib showed a slow but continuous growth, sustained by fecal-oral route transmission. For genotype Ia, there was an exponential growth followed by a plateau, which suggests better infection control. Bidirectional viral flow for Ib genotype, involving different Bulgarian areas, was observed, whereas a unidirectional flow from Sofia to Ihtiman for genotype Ia was highlighted, suggesting the fecal-oral transmission route for Ia. PMID:29504993

The genetic diversity of hepatitis A genotype I in Bulgaria.

PubMed

Cella, Eleonora; Golkocheva-Markova, Elitsa N; Trandeva-Bankova, Diljana; Gregori, Giulia; Bruni, Roberto; Taffon, Stefania; Equestre, Michele; Costantino, Angela; Spoto, Silvia; Curtis, Melissa; Ciccaglione, Anna Rita; Ciccozzi, Massimo; Angeletti, Silvia

2018-01-01

The purpose of this study was to analyze sequences of hepatitis A virus (HAV) Ia and Ib genotypes from Bulgarian patients to investigate the molecular epidemiology of HAV genotype I during the years 2012 to 2014. Around 105 serum samples were collected by the Department of Virology of the National Center of Infectious and Parasitic Diseases in Bulgaria. The sequenced region encompassed the VP1/2A region of HAV genome. The sequences obtained from the samples were 103. For the phylogenetic analyses, 5 datasets were built to investigate the viral gene in/out flow among distinct HAV subpopulations in different geographic areas and to build a Bayesian dated tree, Bayesian phylogenetic and migration pattern analyses were performed. HAV Ib Bulgarian sequences mostly grouped into a single clade. This indicates that the Bulgarian epidemic is partially compartmentalized. It originated from a limited number of viruses and then spread through fecal-oral local transmission. HAV Ia Bulgarian sequences were intermixed with European sequences, suggesting that an Ia epidemic is not restricted to Bulgaria but can affect other European countries. The time-scaled phylogeny reconstruction showed the root of the tree dating in 2008 for genotype Ib and in 1999 for genotype Ia with a second epidemic entrance in 2003. The Bayesian skyline plot for genotype Ib showed a slow but continuous growth, sustained by fecal-oral route transmission. For genotype Ia, there was an exponential growth followed by a plateau, which suggests better infection control. Bidirectional viral flow for Ib genotype, involving different Bulgarian areas, was observed, whereas a unidirectional flow from Sofia to Ihtiman for genotype Ia was highlighted, suggesting the fecal-oral transmission route for Ia. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

Using data mining techniques to predict the severity of bicycle crashes.

PubMed

Prati, Gabriele; Pietrantoni, Luca; Fraboni, Federico

2017-04-01

To investigate the factors predicting severity of bicycle crashes in Italy, we used an observational study of official statistics. We applied two of the most widely used data mining techniques, CHAID decision tree technique and Bayesian network analysis. We used data provided by the Italian National Institute of Statistics on road crashes that occurred on the Italian road network during the period ranging from 2011 to 2013. In the present study, the dataset contains information about road crashes occurred on the Italian road network during the period ranging from 2011 to 2013. We extracted 49,621 road accidents where at least one cyclist was injured or killed from the original database that comprised a total of 575,093 road accidents. CHAID decision tree technique was employed to establish the relationship between severity of bicycle crashes and factors related to crash characteristics (type of collision and opponent vehicle), infrastructure characteristics (type of carriageway, road type, road signage, pavement type, and type of road segment), cyclists (gender and age), and environmental factors (time of the day, day of the week, month, pavement condition, and weather). CHAID analysis revealed that the most important predictors were, in decreasing order of importance, road type (0.30), crash type (0.24), age of cyclist (0.19), road signage (0.08), gender of cyclist (0.07), type of opponent vehicle (0.05), month (0.04), and type of road segment (0.02). These eight most important predictors of the severity of bicycle crashes were included as predictors of the target (i.e., severity of bicycle crashes) in Bayesian network analysis. Bayesian network analysis identified crash type (0.31), road type (0.19), and type of opponent vehicle (0.18) as the most important predictors of severity of bicycle crashes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Emerging Concepts of Data Integration in Pathogen Phylodynamics

PubMed Central

Baele, Guy; Suchard, Marc A.; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics. PMID:28173504

Bayesian updating in a fault tree model for shipwreck risk assessment.

PubMed

Landquist, H; Rosén, L; Lindhe, A; Norberg, T; Hassellöv, I-M

2017-07-15

Shipwrecks containing oil and other hazardous substances have been deteriorating on the seabeds of the world for many years and are threatening to pollute the marine environment. The status of the wrecks and the potential volume of harmful substances present in the wrecks are affected by a multitude of uncertainties. Each shipwreck poses a unique threat, the nature of which is determined by the structural status of the wreck and possible damage resulting from hazardous activities that could potentially cause a discharge. Decision support is required to ensure the efficiency of the prioritisation process and the allocation of resources required to carry out risk mitigation measures. Whilst risk assessments can provide the requisite decision support, comprehensive methods that take into account key uncertainties related to shipwrecks are limited. The aim of this paper was to develop a method for estimating the probability of discharge of hazardous substances from shipwrecks. The method is based on Bayesian updating of generic information on the hazards posed by different activities in the surroundings of the wreck, with information on site-specific and wreck-specific conditions in a fault tree model. Bayesian updating is performed using Monte Carlo simulations for estimating the probability of a discharge of hazardous substances and formal handling of intrinsic uncertainties. An example application involving two wrecks located off the Swedish coast is presented. Results show the estimated probability of opening, discharge and volume of the discharge for the two wrecks and illustrate the capability of the model to provide decision support. Together with consequence estimations of a discharge of hazardous substances, the suggested model enables comprehensive and probabilistic risk assessments of shipwrecks to be made. Copyright © 2017 Elsevier B.V. All rights reserved.

Three times greater weight of daytime than of night-time temperature on leaf unfolding phenology in temperate trees.

PubMed

Fu, Yongshuo H; Liu, Yongjie; De Boeck, Hans J; Menzel, Annette; Nijs, Ivan; Peaucelle, Marc; Peñuelas, Josep; Piao, Shilong; Janssens, Ivan A

2016-11-01

The phenology of spring leaf unfolding plays a key role in the structure and functioning of ecosystems. The classical concept of heat requirement (growing degree days) for leaf unfolding was developed hundreds of years ago, but this model does not include the recently reported greater importance of daytime than night-time temperature. A manipulative experiment on daytime vs night-time warming with saplings of three species of temperate deciduous trees was conducted and a Bayesian method was applied to explore the different effects of daytime and night-time temperatures on spring phenology. We found that both daytime and night-time warming significantly advanced leaf unfolding, but the sensitivities to increased daytime and night-time temperatures differed significantly. Trees were most sensitive to daytime warming (7.4 ± 0.9, 4.8 ± 0.3 and 4.8 ± 0.2 d advancement per degree Celsius warming (d °C -1 ) for birch, oak and beech, respectively) and least sensitive to night-time warming (5.5 ± 0.9, 3.3 ± 0.3 and 2.1 ± 0.9 d °C -1 ). Interestingly, a Bayesian analysis found that the impact of daytime temperature on leaf unfolding was approximately three times higher than that of night-time temperatures. Night-time global temperature is increasing faster than daytime temperature, so model projections of future spring phenology should incorporate the effects of these different temperatures. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

DNA barcoding and the identification of tree frogs (Amphibia: Anura: Rhacophoridae).

PubMed

Dang, Ning-Xin; Sun, Feng-Hui; Lv, Yun-Yun; Zhao, Bo-Han; Wang, Ji-Chao; Murphy, Robert W; Wang, Wen-Zhi; Li, Jia-Tang

2016-07-01

The DNA barcoding gene COI (cytochrome c oxidase subunit I) effectively identifies many species. Herein, we barcoded 172 individuals from 37 species belonging to nine genera in Rhacophoridae to test if the gene serves equally well to identify species of tree frogs. Phenetic neighbor joining and phylogenetic Bayesian inference were used to construct phylogenetic trees, which resolved all nine genera as monophyletic taxa except for Rhacophorus, two new matrilines for Liuixalus, and Polypedates leucomystax species complex. Intraspecific genetic distances ranged from 0.000 to 0.119 and interspecific genetic distances ranged from 0.015 to 0.334. Within Rhacophorus and Kurixalus, the intra- and interspecific genetic distances did not reveal an obvious barcode gap. Notwithstanding, we found that COI sequences unambiguously identified rhacophorid species and helped to discover likely new cryptic species via the synthesis of genealogical relationships and divergence patterns. Our results supported that COI is an effective DNA barcoding marker for Rhacophoridae.

Divergence times and colonization of the Canary Islands by Gallotia lizards.

PubMed

Cox, Siobhan C; Carranza, Salvador; Brown, Richard P

2010-08-01

The Canary Islands have become a model region for evolutionary studies. We obtained 1.8 Kbp of mtDNA sequence from all known island forms of the endemic lizard genus Gallotia and from its sister taxon Psammodromus in order to reanalyze phylogenetic relationships within the archipelago, estimate lineage divergence times, and reconstruct the colonization history of this group. Well-supported phylogenies were obtained using maximum parsimony and Bayesian inference. Previous studies have been unable to establish the branching pattern at the base of the tree. We found evidence that G. stehlini (Gran Canaria) originated from the most basal Gallotia node and G. atlantica from the subsequent node. Divergence times were estimated under a global clock using Bayesian Markov Chain Monte Carlo methods implemented by three different programs: BEAST, MCMCTREE, MULTIDIVTIME. Node constraints were derived from subaerial island appearance data and were incorporated into the analyses as soft or hard maximal bounds. Posterior node ages differed slightly between programs, possibly due to different priors on divergence times. The most eastern Canary Islands first emerged just over 20 mya and their colonization appears to have taken place relatively quickly, around 17-20 mya. The subsequent node is consistent with cladogenesis due to colonization of Gran Canaria from the eastern islands about 11-13 mya. The western islands appear to have been colonized by a dispersal event from Lanzarote/Fuerteventura in the east to either La Gomera or one of the ancient edifices that subsequently formed Tenerife in the west, about 9-10 mya. Within the western islands, the most recent node that is ancestral to both the G. intermedia/G. gomerana/G. simonyi and the G.galloti/G. caesaris clades is dated at about 5-6 mya. Subsequent dispersal events between ancient Tenerife islands and La Gomera are dated at around 3 mya in both clades, although the direction of dispersal cannot be determined. Finally, we show that G. galloti is likely to have colonized La Palma more than 0.5 Ma after emergence of the island 1.77 mya, while G. caesaris from the same clade may have colonized El Hierro very soon after it emerged 1.12 mya. There are tentative indications that the large-bodied endangered G. simonyi colonized El Hierro around the same time or even later than the smaller-bodied G. caesaris. This study demonstrates the effectiveness of Bayesian dating of a phylogeny in helping reconstruct the historical pattern of dispersal across an oceanic archipelago. Copyright 2010 Elsevier Inc. All rights reserved.

CytoBayesJ: software tools for Bayesian analysis of cytogenetic radiation dosimetry data.

PubMed

Ainsbury, Elizabeth A; Vinnikov, Volodymyr; Puig, Pedro; Maznyk, Nataliya; Rothkamm, Kai; Lloyd, David C

2013-08-30

A number of authors have suggested that a Bayesian approach may be most appropriate for analysis of cytogenetic radiation dosimetry data. In the Bayesian framework, probability of an event is described in terms of previous expectations and uncertainty. Previously existing, or prior, information is used in combination with experimental results to infer probabilities or the likelihood that a hypothesis is true. It has been shown that the Bayesian approach increases both the accuracy and quality assurance of radiation dose estimates. New software entitled CytoBayesJ has been developed with the aim of bringing Bayesian analysis to cytogenetic biodosimetry laboratory practice. CytoBayesJ takes a number of Bayesian or 'Bayesian like' methods that have been proposed in the literature and presents them to the user in the form of simple user-friendly tools, including testing for the most appropriate model for distribution of chromosome aberrations and calculations of posterior probability distributions. The individual tools are described in detail and relevant examples of the use of the methods and the corresponding CytoBayesJ software tools are given. In this way, the suitability of the Bayesian approach to biological radiation dosimetry is highlighted and its wider application encouraged by providing a user-friendly software interface and manual in English and Russian. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterization of phylogenetically diverse astroviruses of marine mammals.

PubMed

Rivera, Rebecca; Nollens, Hendrik H; Venn-Watson, Stephanie; Gulland, Frances M D; Wellehan, James F X

2010-01-01

Astroviruses are small, non-enveloped, positive-stranded RNA viruses. Previously studied mammalian astroviruses have been associated with diarrhoeal disease. Knowledge of astrovirus diversity is very limited, with only six officially recognized astrovirus species from mammalian hosts and, in addition, one human and some bat astroviruses were recently described. We used consensus PCR techniques for initial identification of five astroviruses of marine mammals: three from California sea lions (Zalophus californianus), one from a Steller sea lion (Eumetopias jubatus) and one from a bottlenose dolphin (Tursiops truncatus). Bayesian and maximum-likelihood phylogenetic analysis found that these viruses showed significant diversity at a level consistent with novel species. Astroviruses that we identified from marine mammals were found across the mamastrovirus tree and did not form a monophyletic group. Recombination analysis found that a recombination event may have occurred between a human and a California sea lion astrovirus, suggesting that both lineages may have been capable of infecting the same host at one point. The diversity found amongst marine mammal astroviruses and their similarity to terrestrial astroviruses suggests that the marine environment plays an important role in astrovirus ecology.

Condition Monitoring for Helicopter Data. Appendix A

NASA Technical Reports Server (NTRS)

Wen, Fang; Willett, Peter; Deb, Somnath

2000-01-01

In this paper the classical "Westland" set of empirical accelerometer helicopter data is analyzed with the aim of condition monitoring for diagnostic purposes. The goal is to determine features for failure events from these data, via a proprietary signal processing toolbox, and to weigh these according to a variety of classification algorithms. As regards signal processing, it appears that the autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; it has also been found that augmentation of these by harmonic and other parameters can improve classification significantly. As regards classification, several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior on training data and is thus able to quantify probability of error in an exact manner, such that features may be discarded or coarsened appropriately.

Supervised Time Series Event Detector for Building Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-04-13

A machine learning based approach is developed to detect events that have rarely been seen in the historical data. The data can include building energy consumption, sensor data, environmental data and any data that may affect the building's energy consumption. The algorithm is a modified nonlinear Bayesian support vector machine, which examines daily energy consumption profile, detect the days with abnormal events, and diagnose the cause of the events.

MIRAP, microcomputer reliability analysis program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jehee, J.N.T.

1989-01-01

A program for a microcomputer is outlined that can determine minimal cut sets from a specified fault tree logic. The speed and memory limitations of the microcomputers on which the program is implemented (Atari ST and IBM) are addressed by reducing the fault tree's size and by storing the cut set data on disk. Extensive well proven fault tree restructuring techniques, such as the identification of sibling events and of independent gate events, reduces the fault tree's size but does not alter its logic. New methods are used for the Boolean reduction of the fault tree logic. Special criteria formore » combining events in the 'AND' and 'OR' logic avoid the creation of many subsuming cut sets which all would cancel out due to existing cut sets. Figures and tables illustrates these methods. 4 refs., 5 tabs.« less

Using Bayesian Adaptive Trial Designs for Comparative Effectiveness Research: A Virtual Trial Execution.

PubMed

Luce, Bryan R; Connor, Jason T; Broglio, Kristine R; Mullins, C Daniel; Ishak, K Jack; Saunders, Elijah; Davis, Barry R

2016-09-20

Bayesian and adaptive clinical trial designs offer the potential for more efficient processes that result in lower sample sizes and shorter trial durations than traditional designs. To explore the use and potential benefits of Bayesian adaptive clinical trial designs in comparative effectiveness research. Virtual execution of ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) as if it had been done according to a Bayesian adaptive trial design. Comparative effectiveness trial of antihypertensive medications. Patient data sampled from the more than 42 000 patients enrolled in ALLHAT with publicly available data. Number of patients randomly assigned between groups, trial duration, observed numbers of events, and overall trial results and conclusions. The Bayesian adaptive approach and original design yielded similar overall trial conclusions. The Bayesian adaptive trial randomly assigned more patients to the better-performing group and would probably have ended slightly earlier. This virtual trial execution required limited resampling of ALLHAT patients for inclusion in RE-ADAPT (REsearch in ADAptive methods for Pragmatic Trials). Involvement of a data monitoring committee and other trial logistics were not considered. In a comparative effectiveness research trial, Bayesian adaptive trial designs are a feasible approach and potentially generate earlier results and allocate more patients to better-performing groups. National Heart, Lung, and Blood Institute.

Missing rings in Pinus halepensis – the missing link to relate the tree-ring record to extreme climatic events

Treesearch

Klemen Novak; Martin de Luis; Miguel A. Saz; Luis A. Longares; Roberto Serrano-Notivoli; Josep Raventos; Katarina Cufar; Jozica Gricar; Alfredo Di Filippo; Gianluca Piovesan; Cyrille B.K. Rathgeber; Andreas Papadopoulos; Kevin T. Smith

2016-01-01

Climate predictions for the Mediterranean Basin include increased temperatures, decreased precipitation, and increased frequency of extreme climatic events (ECE). These conditions are associated with decreased tree growth and increased vulnerability to pests and diseases. The anatomy of tree rings responds to these environmental conditions. Quantitatively, the width of...

Evidential Networks for Fault Tree Analysis with Imprecise Knowledge

NASA Astrophysics Data System (ADS)

Yang, Jianping; Huang, Hong-Zhong; Liu, Yu; Li, Yan-Feng

2012-06-01

Fault tree analysis (FTA), as one of the powerful tools in reliability engineering, has been widely used to enhance system quality attributes. In most fault tree analyses, precise values are adopted to represent the probabilities of occurrence of those events. Due to the lack of sufficient data or imprecision of existing data at the early stage of product design, it is often difficult to accurately estimate the failure rates of individual events or the probabilities of occurrence of the events. Therefore, such imprecision and uncertainty need to be taken into account in reliability analysis. In this paper, the evidential networks (EN) are employed to quantify and propagate the aforementioned uncertainty and imprecision in fault tree analysis. The detailed conversion processes of some logic gates to EN are described in fault tree (FT). The figures of the logic gates and the converted equivalent EN, together with the associated truth tables and the conditional belief mass tables, are also presented in this work. The new epistemic importance is proposed to describe the effect of ignorance degree of event. The fault tree of an aircraft engine damaged by oil filter plugs is presented to demonstrate the proposed method.

Physics-based, Bayesian sequential detection method and system for radioactive contraband

DOEpatents

Candy, James V; Axelrod, Michael C; Breitfeller, Eric F; Chambers, David H; Guidry, Brian L; Manatt, Douglas R; Meyer, Alan W; Sale, Kenneth E

2014-03-18

A distributed sequential method and system for detecting and identifying radioactive contraband from highly uncertain (noisy) low-count, radionuclide measurements, i.e. an event mode sequence (EMS), using a statistical approach based on Bayesian inference and physics-model-based signal processing based on the representation of a radionuclide as a monoenergetic decomposition of monoenergetic sources. For a given photon event of the EMS, the appropriate monoenergy processing channel is determined using a confidence interval condition-based discriminator for the energy amplitude and interarrival time and parameter estimates are used to update a measured probability density function estimate for a target radionuclide. A sequential likelihood ratio test is then used to determine one of two threshold conditions signifying that the EMS is either identified as the target radionuclide or not, and if not, then repeating the process for the next sequential photon event of the EMS until one of the two threshold conditions is satisfied.

A diagnosis system using object-oriented fault tree models

NASA Technical Reports Server (NTRS)

Iverson, David L.; Patterson-Hine, F. A.

1990-01-01

Spaceborne computing systems must provide reliable, continuous operation for extended periods. Due to weight, power, and volume constraints, these systems must manage resources very effectively. A fault diagnosis algorithm is described which enables fast and flexible diagnoses in the dynamic distributed computing environments planned for future space missions. The algorithm uses a knowledge base that is easily changed and updated to reflect current system status. Augmented fault trees represented in an object-oriented form provide deep system knowledge that is easy to access and revise as a system changes. Given such a fault tree, a set of failure events that have occurred, and a set of failure events that have not occurred, this diagnosis system uses forward and backward chaining to propagate causal and temporal information about other failure events in the system being diagnosed. Once the system has established temporal and causal constraints, it reasons backward from heuristically selected failure events to find a set of basic failure events which are a likely cause of the occurrence of the top failure event in the fault tree. The diagnosis system has been implemented in common LISP using Flavors.

Empirical and Bayesian approaches to fossil-only divergence times: A study across three reptile clades.

PubMed

Turner, Alan H; Pritchard, Adam C; Matzke, Nicholas J

2017-01-01

Estimating divergence times on phylogenies is critical in paleontological and neontological studies. Chronostratigraphically-constrained fossils are the only direct evidence of absolute timing of species divergence. Strict temporal calibration of fossil-only phylogenies provides minimum divergence estimates, and various methods have been proposed to estimate divergences beyond these minimum values. We explore the utility of simultaneous estimation of tree topology and divergence times using BEAST tip-dating on datasets consisting only of fossils by using relaxed morphological clocks and birth-death tree priors that include serial sampling (BDSS) at a constant rate through time. We compare BEAST results to those from the traditional maximum parsimony (MP) and undated Bayesian inference (BI) methods. Three overlapping datasets were used that span 250 million years of archosauromorph evolution leading to crocodylians. The first dataset focuses on early Sauria (31 taxa, 240 chars.), the second on early Archosauria (76 taxa, 400 chars.) and the third on Crocodyliformes (101 taxa, 340 chars.). For each dataset three time-calibrated trees (timetrees) were calculated: a minimum-age timetree with node ages based on earliest occurrences in the fossil record; a 'smoothed' timetree using a range of time added to the root that is then averaged over zero-length internodes; and a tip-dated timetree. Comparisons within datasets show that the smoothed and tip-dated timetrees provide similar estimates. Only near the root node do BEAST estimates fall outside the smoothed timetree range. The BEAST model is not able to overcome limited sampling to correctly estimate divergences considerably older than sampled fossil occurrence dates. Conversely, the smoothed timetrees consistently provide node-ages far older than the strict dates or BEAST estimates for morphologically conservative sister-taxa when they sit on long ghost lineages. In this latter case, the relaxed-clock model appears to be correctly moderating the node-age estimate based on the limited morphological divergence. Topologies are generally similar across analyses, but BEAST trees for crocodyliforms differ when clades are deeply nested but contain very old taxa. It appears that the constant-rate sampling assumption of the BDSS tree prior influences topology inference by disfavoring long, unsampled branches.

Empirical and Bayesian approaches to fossil-only divergence times: A study across three reptile clades

PubMed Central

Turner, Alan H.; Pritchard, Adam C.; Matzke, Nicholas J.

2017-01-01

Estimating divergence times on phylogenies is critical in paleontological and neontological studies. Chronostratigraphically-constrained fossils are the only direct evidence of absolute timing of species divergence. Strict temporal calibration of fossil-only phylogenies provides minimum divergence estimates, and various methods have been proposed to estimate divergences beyond these minimum values. We explore the utility of simultaneous estimation of tree topology and divergence times using BEAST tip-dating on datasets consisting only of fossils by using relaxed morphological clocks and birth-death tree priors that include serial sampling (BDSS) at a constant rate through time. We compare BEAST results to those from the traditional maximum parsimony (MP) and undated Bayesian inference (BI) methods. Three overlapping datasets were used that span 250 million years of archosauromorph evolution leading to crocodylians. The first dataset focuses on early Sauria (31 taxa, 240 chars.), the second on early Archosauria (76 taxa, 400 chars.) and the third on Crocodyliformes (101 taxa, 340 chars.). For each dataset three time-calibrated trees (timetrees) were calculated: a minimum-age timetree with node ages based on earliest occurrences in the fossil record; a ‘smoothed’ timetree using a range of time added to the root that is then averaged over zero-length internodes; and a tip-dated timetree. Comparisons within datasets show that the smoothed and tip-dated timetrees provide similar estimates. Only near the root node do BEAST estimates fall outside the smoothed timetree range. The BEAST model is not able to overcome limited sampling to correctly estimate divergences considerably older than sampled fossil occurrence dates. Conversely, the smoothed timetrees consistently provide node-ages far older than the strict dates or BEAST estimates for morphologically conservative sister-taxa when they sit on long ghost lineages. In this latter case, the relaxed-clock model appears to be correctly moderating the node-age estimate based on the limited morphological divergence. Topologies are generally similar across analyses, but BEAST trees for crocodyliforms differ when clades are deeply nested but contain very old taxa. It appears that the constant-rate sampling assumption of the BDSS tree prior influences topology inference by disfavoring long, unsampled branches. PMID:28187191

Phylogenetics of Anthyllis (Leguminosae: Papilionoideae: Loteae): Partial incongruence between nuclear and plastid markers, a long branch problem and implications for morphological evolution.

PubMed

Degtjareva, Galina V; Valiejo-Roman, Carmen M; Samigullin, Tahir H; Guara-Requena, Miguel; Sokoloff, Dmitry D

2012-02-01

Phylogenetic relationships in the genus Anthyllis (Leguminosae: Papilionoideae: Loteae) were investigated using data from the nuclear ribosomal internal transcribed spacer regions (ITS) and three plastid regions (psbA-trnH intergenic spacer, petB-petD region and rps16 intron). Bayesian and maximum parsimony (MP) analysis of a concatenated plastid dataset recovered well-resolved trees that are topologically similar, with many clades supported by unique indels. MP and Bayesian analyses of the ITS sequence data recovered trees that have several well-supported topological differences, both among analyses, and to trees inferred from the plastid data. The most substantial of these concerns A. vulneraria and A. lemanniana, whose placement in the parsimony analysis of the ITS data appears to be due to a strong long-branch effect. Analysis of the secondary structure of the ITS1 spacer showed a strong bias towards transitions in A. vulneraria and A. lemanniana, many of which were also characteristic of certain outgroup taxa. This may contribute to the conflicting placement of this clade in the MP tree for the ITS data. Additional conflicts between the plastid and ITS trees were more taxonomically focused. These differences may reflect the occurrence of reticulate evolution between closely related species, including a possible hybrid origin for A. hystrix. The patterns of incongruence between the plastid and the ITS data seem to correlate with taxon ranks. All of our phylogenetic analyses supported the monophyly of Anthyllis (incl. Hymenocarpos). Although they are often taxonomically associated with Anthyllis, the genera Dorycnopsis and Tripodion are shown here to be more closely related to other genera of Loteae. We infer up to six major clades in Anthyllis that are morphologically well-characterized, and which could be recognized as sections. Four of these agree with various morphology-based classifications, while the other two are novel. We reconstruct the evolution of several morphological characteristics found only in Anthyllis or tribe Loteae. Some of these characters support major clades, while others show evidence of homoplasy within Anthyllis. Copyright © 2011 Elsevier Inc. All rights reserved.

A supermatrix analysis of genomic, morphological, and paleontological data from crown Cetacea

PubMed Central

2011-01-01

Background Cetacea (dolphins, porpoises, and whales) is a clade of aquatic species that includes the most massive, deepest diving, and largest brained mammals. Understanding the temporal pattern of diversification in the group as well as the evolution of cetacean anatomy and behavior requires a robust and well-resolved phylogenetic hypothesis. Although a large body of molecular data has accumulated over the past 20 years, DNA sequences of cetaceans have not been directly integrated with the rich, cetacean fossil record to reconcile discrepancies among molecular and morphological characters. Results We combined new nuclear DNA sequences, including segments of six genes (~2800 basepairs) from the functionally extinct Yangtze River dolphin, with an expanded morphological matrix and published genomic data. Diverse analyses of these data resolved the relationships of 74 taxa that represent all extant families and 11 extinct families of Cetacea. The resulting supermatrix (61,155 characters) and its sub-partitions were analyzed using parsimony methods. Bayesian and maximum likelihood (ML) searches were conducted on the molecular partition, and a molecular scaffold obtained from these searches was used to constrain a parsimony search of the morphological partition. Based on analysis of the supermatrix and model-based analyses of the molecular partition, we found overwhelming support for 15 extant clades. When extinct taxa are included, we recovered trees that are significantly correlated with the fossil record. These trees were used to reconstruct the timing of cetacean diversification and the evolution of characters shared by "river dolphins," a non-monophyletic set of species according to all of our phylogenetic analyses. Conclusions The parsimony analysis of the supermatrix and the analysis of morphology constrained to fit the ML/Bayesian molecular tree yielded broadly congruent phylogenetic hypotheses. In trees from both analyses, all Oligocene taxa included in our study fell outside crown Mysticeti and crown Odontoceti, suggesting that these two clades radiated in the late Oligocene or later, contra some recent molecular clock studies. Our trees also imply that many character states shared by river dolphins evolved in their oceanic ancestors, contradicting the hypothesis that these characters are convergent adaptations to fluvial habitats. PMID:21518443

A supermatrix analysis of genomic, morphological, and paleontological data from crown Cetacea.

PubMed

Geisler, Jonathan H; McGowen, Michael R; Yang, Guang; Gatesy, John

2011-04-25

Cetacea (dolphins, porpoises, and whales) is a clade of aquatic species that includes the most massive, deepest diving, and largest brained mammals. Understanding the temporal pattern of diversification in the group as well as the evolution of cetacean anatomy and behavior requires a robust and well-resolved phylogenetic hypothesis. Although a large body of molecular data has accumulated over the past 20 years, DNA sequences of cetaceans have not been directly integrated with the rich, cetacean fossil record to reconcile discrepancies among molecular and morphological characters. We combined new nuclear DNA sequences, including segments of six genes (~2800 basepairs) from the functionally extinct Yangtze River dolphin, with an expanded morphological matrix and published genomic data. Diverse analyses of these data resolved the relationships of 74 taxa that represent all extant families and 11 extinct families of Cetacea. The resulting supermatrix (61,155 characters) and its sub-partitions were analyzed using parsimony methods. Bayesian and maximum likelihood (ML) searches were conducted on the molecular partition, and a molecular scaffold obtained from these searches was used to constrain a parsimony search of the morphological partition. Based on analysis of the supermatrix and model-based analyses of the molecular partition, we found overwhelming support for 15 extant clades. When extinct taxa are included, we recovered trees that are significantly correlated with the fossil record. These trees were used to reconstruct the timing of cetacean diversification and the evolution of characters shared by "river dolphins," a non-monophyletic set of species according to all of our phylogenetic analyses. The parsimony analysis of the supermatrix and the analysis of morphology constrained to fit the ML/Bayesian molecular tree yielded broadly congruent phylogenetic hypotheses. In trees from both analyses, all Oligocene taxa included in our study fell outside crown Mysticeti and crown Odontoceti, suggesting that these two clades radiated in the late Oligocene or later, contra some recent molecular clock studies. Our trees also imply that many character states shared by river dolphins evolved in their oceanic ancestors, contradicting the hypothesis that these characters are convergent adaptations to fluvial habitats.

Dating the Cryptococcus gattii Dispersal to the North American Pacific Northwest

PubMed Central

Roe, Chandler C.; Bowers, Jolene; Oltean, Hanna; DeBess, Emilio; Dufresne, Philippe J.; McBurney, Scott; Overy, David P.; Wanke, Bodo; Lysen, Colleen; Chiller, Tom; Meyer, Wieland; Thompson, George R.; Lockhart, Shawn R.; Hepp, Crystal M.

2018-01-01

ABSTRACT The emergence of Cryptococcus gattii, previously regarded as a predominantly tropical pathogen, in the temperate climate of the North American Pacific Northwest (PNW) in 1999 prompted several questions. The most prevalent among these was the timing of the introduction of this pathogen to this novel environment. Here, we infer tip-dated timing estimates for the three clonal C. gattii populations observed in the PNW, VGIIa, VGIIb, and VGIIc, based on whole-genome sequencing of 134 C. gattii isolates and using Bayesian evolutionary analysis by sampling trees (BEAST). We estimated the nucleotide substitution rate for each lineage (1.59 × 10−8, 1.59 × 10−8, and 2.70 × 10−8, respectively) to be an order of magnitude higher than common neutral fungal mutation rates (2.0 × 10−9), indicating a microevolutionary rate (e.g., successive clonal generations in a laboratory) in comparison to a species’ slower, macroevolutionary rate (e.g., when using fossil records). The clonal nature of the PNW C. gattii emergence over a narrow number of years would therefore possibly explain our higher mutation rates. Our results suggest that the mean time to most recent common ancestor for all three sublineages occurred within the last 60 to 100 years. While the cause of C. gattii dispersal to the PNW is still unclear, our research estimates that the arrival is neither ancient nor very recent (i.e., <25 years ago), making a strong case for an anthropogenic introduction. IMPORTANCE The recent emergence of the pathogenic fungus Cryptococcus gattii in the Pacific Northwest (PNW) resulted in numerous investigations into the epidemiological and enzootic impacts, as well as multiple genomic explorations of the three primary molecular subtypes of the fungus that were discovered. These studies lead to the general conclusion that the subtypes identified likely emerged out of Brazil. Here, we conducted genomic dating analyses to determine the ages of the various lineages seen in the PNW and propose hypothetical causes for the dispersal events. Bayesian evolutionary analysis strongly suggests that these independent fungal populations in the PNW are all 60 to 100 years old, providing a timing that is subsequent to the opening of the Panama Canal, which allowed for more direct shipping between Brazil and the western North American coastline, a possible driving event for these fungal translocation events. PMID:29359190

Dating the Cryptococcus gattii Dispersal to the North American Pacific Northwest.

PubMed

Roe, Chandler C; Bowers, Jolene; Oltean, Hanna; DeBess, Emilio; Dufresne, Philippe J; McBurney, Scott; Overy, David P; Wanke, Bodo; Lysen, Colleen; Chiller, Tom; Meyer, Wieland; Thompson, George R; Lockhart, Shawn R; Hepp, Crystal M; Engelthaler, David M

2018-01-01

The emergence of Cryptococcus gattii , previously regarded as a predominantly tropical pathogen, in the temperate climate of the North American Pacific Northwest (PNW) in 1999 prompted several questions. The most prevalent among these was the timing of the introduction of this pathogen to this novel environment. Here, we infer tip-dated timing estimates for the three clonal C. gattii populations observed in the PNW, VGIIa, VGIIb, and VGIIc, based on whole-genome sequencing of 134 C. gattii isolates and using Bayesian evolutionary analysis by sampling trees (BEAST). We estimated the nucleotide substitution rate for each lineage (1.59 × 10 -8 , 1.59 × 10 -8 , and 2.70 × 10 -8 , respectively) to be an order of magnitude higher than common neutral fungal mutation rates (2.0 × 10 -9 ), indicating a microevolutionary rate (e.g., successive clonal generations in a laboratory) in comparison to a species' slower, macroevolutionary rate (e.g., when using fossil records). The clonal nature of the PNW C. gattii emergence over a narrow number of years would therefore possibly explain our higher mutation rates. Our results suggest that the mean time to most recent common ancestor for all three sublineages occurred within the last 60 to 100 years. While the cause of C. gattii dispersal to the PNW is still unclear, our research estimates that the arrival is neither ancient nor very recent (i.e., <25 years ago), making a strong case for an anthropogenic introduction. IMPORTANCE The recent emergence of the pathogenic fungus Cryptococcus gattii in the Pacific Northwest (PNW) resulted in numerous investigations into the epidemiological and enzootic impacts, as well as multiple genomic explorations of the three primary molecular subtypes of the fungus that were discovered. These studies lead to the general conclusion that the subtypes identified likely emerged out of Brazil. Here, we conducted genomic dating analyses to determine the ages of the various lineages seen in the PNW and propose hypothetical causes for the dispersal events. Bayesian evolutionary analysis strongly suggests that these independent fungal populations in the PNW are all 60 to 100 years old, providing a timing that is subsequent to the opening of the Panama Canal, which allowed for more direct shipping between Brazil and the western North American coastline, a possible driving event for these fungal translocation events.

Simple street tree sampling

Treesearch

David J. Nowak; Jeffrey T. Walton; James Baldwin; Jerry Bond

2015-01-01

Information on street trees is critical for management of this important resource. Sampling of street tree populations provides an efficient means to obtain street tree population information. Long-term repeat measures of street tree samples supply additional information on street tree changes and can be used to report damages from catastrophic events. Analyses of...

Event Classification and Identification Based on the Characteristic Ellipsoid of Phasor Measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Jian; Diao, Ruisheng; Makarov, Yuri V.

2011-09-23

In this paper, a method to classify and identify power system events based on the characteristic ellipsoid of phasor measurement is presented. The decision tree technique is used to perform the event classification and identification. Event types, event locations and clearance times are identified by decision trees based on the indices of the characteristic ellipsoid. A sufficiently large number of transient events were simulated on the New England 10-machine 39-bus system based on different system configurations. Transient simulations taking into account different event types, clearance times and various locations are conducted to simulate phasor measurement. Bus voltage magnitudes and recordedmore » reactive and active power flows are used to build the characteristic ellipsoid. The volume, eccentricity, center and projection of the longest axis in the parameter space coordinates of the characteristic ellipsoids are used to classify and identify events. Results demonstrate that the characteristic ellipsoid and the decision tree are capable to detect the event type, location, and clearance time with very high accuracy.« less

Forest pests and home values: The importance of accuracy in damage assessment and geocoding of properties

Treesearch

Klaus Moeltner; Christine E. Blinn; Thomas P. Holmes

2017-01-01

We examine the impact of measurement errors in geocoding of property locations and in the assessment of Mountain Pine Beetle-induced tree damage within the proximity of a given residence on estimated losses in home values. For our sample of homes in the wildland-urban interface of the Colorado front range and using a novel matching estimator with Bayesian regression...

Nonparametric analysis of Minnesota spruce and aspen tree data and LANDSAT data

NASA Technical Reports Server (NTRS)

Scott, D. W.; Jee, R.

1984-01-01

The application of nonparametric methods in data-intensive problems faced by NASA is described. The theoretical development of efficient multivariate density estimators and the novel use of color graphics workstations are reviewed. The use of nonparametric density estimates for data representation and for Bayesian classification are described and illustrated. Progress in building a data analysis system in a workstation environment is reviewed and preliminary runs presented.

Host shifts enhance diversification of ectomycorrhizal fungi: diversification rate analysis of the ectomycorrhizal fungal genera Strobilomyces and Afroboletus with an 80-gene phylogeny.

PubMed

Sato, Hirotoshi; Tanabe, Akifumi S; Toju, Hirokazu

2017-04-01

Mutualisms with new host lineages can provide symbionts with novel ecological opportunities to expand their geographical distribution, thereby leading to evolutionary diversification. Because ectomycorrhizal (ECM) fungi provide ideal opportunities to test the relationship between host shifts and diversification, we tested whether mutualism with new host lineages could increase the diversification rates of ECM fungi. Using a Bayesian tree inferred from 23 027-base nucleotide sequences of 80 single-copy genes, we tested whether the diversification rate had changed through host-shift events in the monophyletic clade containing the ECM fungal genera Strobilomyces and Afroboletus. The results indicated that these fungi were initially associated with Caesalpinioideae/Monotoideae in Africa, acquired associations with Dipterocarpoideae in tropical Asia, and then switched to Fagaceae/Pinaceae and Nothofagaceae/Eucalyptus. Fungal lineages associated with Fagaceae/Pinaceae were inferred to have approximately four-fold and two-fold greater diversification rates than those associated with Caesalpinioideae/Monotoideae and Dipterocarpoideae or Nothofagaceae/Eucalyptus, respectively. Moreover, the diversification rate shift was inferred to follow the host shift to Fagaceae/Pinaceae. Our study suggests that host-shift events, particularly those occurring with respect to Fagaceae/Pinaceae, can provide ecological opportunities for the rapid diversification of Strobilomyces-Afroboletus. Although further studies are needed for generalization, we propose a possible diversification scenario of ECM fungi. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Does the choice of nucleotide substitution models matter topologically?

PubMed

Hoff, Michael; Orf, Stefan; Riehm, Benedikt; Darriba, Diego; Stamatakis, Alexandros

2016-03-24

In the context of a master level programming practical at the computer science department of the Karlsruhe Institute of Technology, we developed and make available an open-source code for testing all 203 possible nucleotide substitution models in the Maximum Likelihood (ML) setting under the common Akaike, corrected Akaike, and Bayesian information criteria. We address the question if model selection matters topologically, that is, if conducting ML inferences under the optimal, instead of a standard General Time Reversible model, yields different tree topologies. We also assess, to which degree models selected and trees inferred under the three standard criteria (AIC, AICc, BIC) differ. Finally, we assess if the definition of the sample size (#sites versus #sites × #taxa) yields different models and, as a consequence, different tree topologies. We find that, all three factors (by order of impact: nucleotide model selection, information criterion used, sample size definition) can yield topologically substantially different final tree topologies (topological difference exceeding 10 %) for approximately 5 % of the tree inferences conducted on the 39 empirical datasets used in our study. We find that, using the best-fit nucleotide substitution model may change the final ML tree topology compared to an inference under a default GTR model. The effect is less pronounced when comparing distinct information criteria. Nonetheless, in some cases we did obtain substantial topological differences.

Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Wilkins, David C.; Roth, Dan

2010-01-01

For hard computational problems, stochastic local search has proven to be a competitive approach to finding optimal or approximately optimal problem solutions. Two key research questions for stochastic local search algorithms are: Which algorithms are effective for initialization? When should the search process be restarted? In the present work we investigate these research questions in the context of approximate computation of most probable explanations (MPEs) in Bayesian networks (BNs). We introduce a novel approach, based on the Viterbi algorithm, to explanation initialization in BNs. While the Viterbi algorithm works on sequences and trees, our approach works on BNs with arbitrary topologies. We also give a novel formalization of stochastic local search, with focus on initialization and restart, using probability theory and mixture models. Experimentally, we apply our methods to the problem of MPE computation, using a stochastic local search algorithm known as Stochastic Greedy Search. By carefully optimizing both initialization and restart, we reduce the MPE search time for application BNs by several orders of magnitude compared to using uniform at random initialization without restart. On several BNs from applications, the performance of Stochastic Greedy Search is competitive with clique tree clustering, a state-of-the-art exact algorithm used for MPE computation in BNs.

Bayesian-network-based safety risk assessment for steel construction projects.

PubMed

Leu, Sou-Sen; Chang, Ching-Miao

2013-05-01

There are four primary accident types at steel building construction (SC) projects: falls (tumbles), object falls, object collapse, and electrocution. Several systematic safety risk assessment approaches, such as fault tree analysis (FTA) and failure mode and effect criticality analysis (FMECA), have been used to evaluate safety risks at SC projects. However, these traditional methods ineffectively address dependencies among safety factors at various levels that fail to provide early warnings to prevent occupational accidents. To overcome the limitations of traditional approaches, this study addresses the development of a safety risk-assessment model for SC projects by establishing the Bayesian networks (BN) based on fault tree (FT) transformation. The BN-based safety risk-assessment model was validated against the safety inspection records of six SC building projects and nine projects in which site accidents occurred. The ranks of posterior probabilities from the BN model were highly consistent with the accidents that occurred at each project site. The model accurately provides site safety-management abilities by calculating the probabilities of safety risks and further analyzing the causes of accidents based on their relationships in BNs. In practice, based on the analysis of accident risks and significant safety factors, proper preventive safety management strategies can be established to reduce the occurrence of accidents on SC sites. Copyright © 2013 Elsevier Ltd. All rights reserved.

New phiomorph rodents from the latest Eocene of Egypt, and the impact of Bayesian “clock”-based phylogenetic methods on estimates of basal hystricognath relationships and biochronology

PubMed Central

2016-01-01

The Fayum Depression of Egypt has yielded fossils of hystricognathous rodents from multiple Eocene and Oligocene horizons that range in age from ∼37 to ∼30 Ma and document several phases in the early evolution of crown Hystricognathi and one of its major subclades, Phiomorpha. Here we describe two new genera and species of basal phiomorphs, Birkamys korai and Mubhammys vadumensis, based on rostra and maxillary and mandibular remains from the terminal Eocene (∼34 Ma) Fayum Locality 41 (L-41). Birkamys is the smallest known Paleogene hystricognath, has very simple molars, and, like derived Oligocene-to-Recent phiomorphs (but unlike contemporaneous and older taxa) apparently retained dP4∕4 late into life, with no evidence for P4∕4 eruption or formation. Mubhammys is very similar in dental morphology to Birkamys, and also shows no evidence for P4∕4 formation or eruption, but is considerably larger. Though parsimony analysis with all characters equally weighted places Birkamys and Mubhammys as sister taxa of extant Thryonomys to the exclusion of much younger relatives of that genus, all other methods (standard Bayesian inference, Bayesian “tip-dating,” and parsimony analysis with scaled transitions between “fixed” and polymorphic states) place these species in more basal positions within Hystricognathi, as sister taxa of Oligocene-to-Recent phiomorphs. We also employ tip-dating as a means for estimating the ages of early hystricognath-bearing localities, many of which are not well-constrained by geological, geochronological, or biostratigraphic evidence. By simultaneously taking into account phylogeny, evolutionary rates, and uniform priors that appropriately encompass the range of possible ages for fossil localities, dating of tips in this Bayesian framework allows paleontologists to move beyond vague and assumption-laden “stage of evolution” arguments in biochronology to provide relatively rigorous age assessments of poorly-constrained faunas. This approach should become increasingly robust as estimates are combined from multiple independent analyses of distantly related clades, and is broadly applicable across the tree of life; as such it is deserving of paleontologists’ close attention. Notably, in the example provided here, hystricognathous rodents from Libya and Namibia that are controversially considered to be of middle Eocene age are instead estimated to be of late Eocene and late Oligocene age, respectively. Finally, we reconstruct the evolution of first lower molar size among Paleogene African hystricognaths using a Bayesian approach; the results of this analysis reconstruct a rapid latest Eocene dwarfing event along the lineage leading to Birkamys. PMID:26966657

A Black Swan and Sub-continental Scale Dynamics in Humid, Late-Holocene Broadleaf Forests

NASA Astrophysics Data System (ADS)

Pederson, N.; Dyer, J.; McEwan, R.; Hessl, A. E.; Mock, C. J.; Orwig, D.; Rieder, H. E.; Cook, B. I.

2012-12-01

In humid regions with dense broadleaf-dominated forests where gap-dynamics is the prevailing disturbance regime, paleoecological evidence shows regional-scale changes in forest composition associated with climatic change. To investigate the potential for regional events in late-Holocene forests, we use tree-ring data from 76 populations covering 840,000 km2 and 5.3k tree recruitment dates spanning 1.4 million km2 in the eastern US to investigate the occurrence of simultaneous forest dynamics across a humid region. We compare regional forest dynamics with an independent set of annually-resolved tree ring record of hydroclimate to examine whether climate dynamics might drive forest dynamics in this humid region. In forests where light availability is an important limitation for tree recruitment, we document a pulse of tree recruitment during the mid- to late-1600s across the eastern US. This pulse, which can be inferred as large-scale canopy opening, occurred during an era that multiple proxies indicate as extended drought between two intense pluvial. Principal component analysis of the 76 populations indicates a step-change increase in average ring width during the late-1770s resembling a potential canopy accession event over 42,800 km2 of the southeastern US. Growth-release analysis of populations loading strongly on this eigenvector indicates severe canopy disturbance from 1775-1779 that peaked in 1776. The 1776 event follows a period with extended droughts and severe large-scale frost event. We hypothesize these climatic events lead to elevated tree mortality in the late-1770s and canopy accession for understory trees. Superposed epoch analysis reveals that spikes of elevated canopy disturbance from 1685-1850 CE are significantly associated with drought. Extreme value theory statistics indicates the 1776 event lies beyond the 99.9 quantile and nearly 7 sigmas above the 1685-1850 mean rate of disturbance. The time-series of canopy disturbance from 1685-1850 is so poorly described by a Gaussian distribution that it can be considered 'heavy tailed'. Preliminary results show that disturbance events that affect >3-5% of the trees in our dataset occur approximately every 200 years. The most extreme rates (>5%) occur approximately every 500-1000 years. These statistics indicate that the 1775-1779 heavy-tail event can also be considered a 'Black Swan', the rare event that has the potential to alter a system's trajectory further than common events. Our results challenge traditional views regarding characteristic disturbance regime in humid temperate forests, and speak to the importance of punctuated climatic events in shaping forest structure for centuries. Such an understanding is critical given the potential of more frequent extreme climatic events in the future.

Diversity Dynamics in Nymphalidae Butterflies: Effect of Phylogenetic Uncertainty on Diversification Rate Shift Estimates

PubMed Central

Peña, Carlos; Espeland, Marianne

2015-01-01

The species rich butterfly family Nymphalidae has been used to study evolutionary interactions between plants and insects. Theories of insect-hostplant dynamics predict accelerated diversification due to key innovations. In evolutionary biology, analysis of maximum credibility trees in the software MEDUSA (modelling evolutionary diversity using stepwise AIC) is a popular method for estimation of shifts in diversification rates. We investigated whether phylogenetic uncertainty can produce different results by extending the method across a random sample of trees from the posterior distribution of a Bayesian run. Using the MultiMEDUSA approach, we found that phylogenetic uncertainty greatly affects diversification rate estimates. Different trees produced diversification rates ranging from high values to almost zero for the same clade, and both significant rate increase and decrease in some clades. Only four out of 18 significant shifts found on the maximum clade credibility tree were consistent across most of the sampled trees. Among these, we found accelerated diversification for Ithomiini butterflies. We used the binary speciation and extinction model (BiSSE) and found that a hostplant shift to Solanaceae is correlated with increased net diversification rates in Ithomiini, congruent with the diffuse cospeciation hypothesis. Our results show that taking phylogenetic uncertainty into account when estimating net diversification rate shifts is of great importance, as very different results can be obtained when using the maximum clade credibility tree and other trees from the posterior distribution. PMID:25830910

Diversity dynamics in Nymphalidae butterflies: effect of phylogenetic uncertainty on diversification rate shift estimates.

PubMed

Peña, Carlos; Espeland, Marianne

2015-01-01

The species rich butterfly family Nymphalidae has been used to study evolutionary interactions between plants and insects. Theories of insect-hostplant dynamics predict accelerated diversification due to key innovations. In evolutionary biology, analysis of maximum credibility trees in the software MEDUSA (modelling evolutionary diversity using stepwise AIC) is a popular method for estimation of shifts in diversification rates. We investigated whether phylogenetic uncertainty can produce different results by extending the method across a random sample of trees from the posterior distribution of a Bayesian run. Using the MultiMEDUSA approach, we found that phylogenetic uncertainty greatly affects diversification rate estimates. Different trees produced diversification rates ranging from high values to almost zero for the same clade, and both significant rate increase and decrease in some clades. Only four out of 18 significant shifts found on the maximum clade credibility tree were consistent across most of the sampled trees. Among these, we found accelerated diversification for Ithomiini butterflies. We used the binary speciation and extinction model (BiSSE) and found that a hostplant shift to Solanaceae is correlated with increased net diversification rates in Ithomiini, congruent with the diffuse cospeciation hypothesis. Our results show that taking phylogenetic uncertainty into account when estimating net diversification rate shifts is of great importance, as very different results can be obtained when using the maximum clade credibility tree and other trees from the posterior distribution.

Non-Bayesian Inference: Causal Structure Trumps Correlation

ERIC Educational Resources Information Center

Bes, Benedicte; Sloman, Steven; Lucas, Christopher G.; Raufaste, Eric

2012-01-01

The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more…

Simulation-Based Evaluation of Hybridization Network Reconstruction Methods in the Presence of Incomplete Lineage Sorting

PubMed Central

Kamneva, Olga K; Rosenberg, Noah A

2017-01-01

Hybridization events generate reticulate species relationships, giving rise to species networks rather than species trees. We report a comparative study of consensus, maximum parsimony, and maximum likelihood methods of species network reconstruction using gene trees simulated assuming a known species history. We evaluate the role of the divergence time between species involved in a hybridization event, the relative contributions of the hybridizing species, and the error in gene tree estimation. When gene tree discordance is mostly due to hybridization and not due to incomplete lineage sorting (ILS), most of the methods can detect even highly skewed hybridization events between highly divergent species. For recent divergences between hybridizing species, when the influence of ILS is sufficiently high, likelihood methods outperform parsimony and consensus methods, which erroneously identify extra hybridizations. The more sophisticated likelihood methods, however, are affected by gene tree errors to a greater extent than are consensus and parsimony. PMID:28469378

Efficient Exploration of the Space of Reconciled Gene Trees

PubMed Central

Szöllősi, Gergely J.; Rosikiewicz, Wojciech; Boussau, Bastien; Tannier, Eric; Daubin, Vincent

2013-01-01

Gene trees record the combination of gene-level events, such as duplication, transfer and loss (DTL), and species-level events, such as speciation and extinction. Gene tree–species tree reconciliation methods model these processes by drawing gene trees into the species tree using a series of gene and species-level events. The reconstruction of gene trees based on sequence alone almost always involves choosing between statistically equivalent or weakly distinguishable relationships that could be much better resolved based on a putative species tree. To exploit this potential for accurate reconstruction of gene trees, the space of reconciled gene trees must be explored according to a joint model of sequence evolution and gene tree–species tree reconciliation. Here we present amalgamated likelihood estimation (ALE), a probabilistic approach to exhaustively explore all reconciled gene trees that can be amalgamated as a combination of clades observed in a sample of gene trees. We implement the ALE approach in the context of a reconciliation model (Szöllősi et al. 2013), which allows for the DTL of genes. We use ALE to efficiently approximate the sum of the joint likelihood over amalgamations and to find the reconciled gene tree that maximizes the joint likelihood among all such trees. We demonstrate using simulations that gene trees reconstructed using the joint likelihood are substantially more accurate than those reconstructed using sequence alone. Using realistic gene tree topologies, branch lengths, and alignment sizes, we demonstrate that ALE produces more accurate gene trees even if the model of sequence evolution is greatly simplified. Finally, examining 1099 gene families from 36 cyanobacterial genomes we find that joint likelihood-based inference results in a striking reduction in apparent phylogenetic discord, with respectively. 24%, 59%, and 46% reductions in the mean numbers of duplications, transfers, and losses per gene family. The open source implementation of ALE is available from https://github.com/ssolo/ALE.git. [amalgamation; gene tree reconciliation; gene tree reconstruction; lateral gene transfer; phylogeny.] PMID:23925510

A Bayesian additive model for understanding public transport usage in special events.

PubMed

Rodrigues, Filipe; Borysov, Stanislav; Ribeiro, Bernardete; Pereira, Francisco

2016-12-02

Public special events, like sports games, concerts and festivals are well known to create disruptions in transportation systems, often catching the operators by surprise. Although these are usually planned well in advance, their impact is difficult to predict, even when organisers and transportation operators coordinate. The problem highly increases when several events happen concurrently. To solve these problems, costly processes, heavily reliant on manual search and personal experience, are usual practice in large cities like Singapore, London or Tokyo. This paper presents a Bayesian additive model with Gaussian process components that combines smart card records from public transport with context information about events that is continuously mined from the Web. We develop an efficient approximate inference algorithm using expectation propagation, which allows us to predict the total number of public transportation trips to the special event areas, thereby contributing to a more adaptive transportation system. Furthermore, for multiple concurrent event scenarios, the proposed algorithm is able to disaggregate gross trip counts into their most likely components related to specific events and routine behavior. Using real data from Singapore, we show that the presented model outperforms the best baseline model by up to 26% in R2 and also has explanatory power for its individual components.

Extreme Drought Event and Shrub Invasion Reduce Oak Trees Functioning and Resilience on Water-Limited Ecosystems

NASA Astrophysics Data System (ADS)

Caldeira, M. C.; Lobo-do-Vale, R.; Lecomte, X.; David, T. S.; Pinto, J. G.; Bugalho, M. N.; Werner, C.

2016-12-01

Extreme droughts and plant invasions are major drivers of global change that can critically affect ecosystem functioning. Shrub encroachment is increasing in many regions worldwide and extreme events are projected to increase in frequency and intensity, namely in the Mediterranean region. Nevertheless, little is known about how these drivers may interact and affect ecosystem functioning and resilience Using a manipulative shrub removal experiment and the co-occurrence of an extreme drought event in a Mediterranean oak woodland, we show that the combination of native shrub invasion and extreme drought reduced ecosystem transpiration and the resilience of the key-stone oak tree species. We established six 25 x 25 m paired plots in a shrub (Cistus ladanifer L.) encroached Mediterranean cork-oak (Quercus suber L.) woodland. We measured sapflow and pre-dawn leaf water potential of trees and shrubs and soil water content in all plots during four years. We determined the resilience of tree transpiration to evaluate to what extent trees recovered from the extreme drought event. From February to November 2011 we conducted baseline measurements for plot comparison. In November 2011 all the shrubs from one of all the paired plots were cut and removed. Ecosystem transpiration was dominated by the water use of the invasive shrub, which further increased after the extreme drought. Simultaneously, tree transpiration in invaded plots declined more sharply (67 ± 13 %) than in plots cleared from shrubs (31 ± 11%) relative to the pre-drought year (2011). Trees in invaded plots were not able to recover in the following wetter year showing lower resilience to the extreme drought event. Our results imply that in Mediterranean-type of climates invasion by water spending species coupled with the projected recurrent extreme droughts will cause critical drought tolerance thresholds of trees to be overcome, thus increasing the probability of tree mortality.

Lognormal Approximations of Fault Tree Uncertainty Distributions.

PubMed

El-Shanawany, Ashraf Ben; Ardron, Keith H; Walker, Simon P

2018-01-26

Fault trees are used in reliability modeling to create logical models of fault combinations that can lead to undesirable events. The output of a fault tree analysis (the top event probability) is expressed in terms of the failure probabilities of basic events that are input to the model. Typically, the basic event probabilities are not known exactly, but are modeled as probability distributions: therefore, the top event probability is also represented as an uncertainty distribution. Monte Carlo methods are generally used for evaluating the uncertainty distribution, but such calculations are computationally intensive and do not readily reveal the dominant contributors to the uncertainty. In this article, a closed-form approximation for the fault tree top event uncertainty distribution is developed, which is applicable when the uncertainties in the basic events of the model are lognormally distributed. The results of the approximate method are compared with results from two sampling-based methods: namely, the Monte Carlo method and the Wilks method based on order statistics. It is shown that the closed-form expression can provide a reasonable approximation to results obtained by Monte Carlo sampling, without incurring the computational expense. The Wilks method is found to be a useful means of providing an upper bound for the percentiles of the uncertainty distribution while being computationally inexpensive compared with full Monte Carlo sampling. The lognormal approximation method and Wilks's method appear attractive, practical alternatives for the evaluation of uncertainty in the output of fault trees and similar multilinear models. © 2018 Society for Risk Analysis.

Quantifying probabilities of eruptions at Mount Etna (Sicily, Italy).

NASA Astrophysics Data System (ADS)

Brancato, Alfonso

2010-05-01

One of the major goals of modern volcanology is to set up sound risk-based decision-making in land-use planning and emergency management. Volcanic hazard must be managed with reliable estimates of quantitative long- and short-term eruption forecasting, but the large number of observables involved in a volcanic process suggests that a probabilistic approach could be a suitable tool in forecasting. The aim of this work is to quantify probabilistic estimate of the vent location for a suitable lava flow hazard assessment at Mt. Etna volcano, through the application of the code named BET (Marzocchi et al., 2004, 2008). The BET_EF model is based on the event tree philosophy assessed by Newhall and Hoblitt (2002), further developing the concept of vent location, epistemic uncertainties, and a fuzzy approach for monitoring measurements. A Bayesian event tree is a specialized branching graphical representation of events in which individual branches are alternative steps from a general prior event, and evolving into increasingly specific subsequent states. Then, the event tree attempts to graphically display all relevant possible outcomes of volcanic unrest in progressively higher levels of detail. The procedure is set to estimate an a priori probability distribution based upon theoretical knowledge, to accommodate it by using past data, and to modify it further by using current monitoring data. For the long-term forecasting, an a priori model, dealing with the present tectonic and volcanic structure of the Mt. Etna, is considered. The model is mainly based on past vent locations and fracture location datasets (XX century of eruptive history of the volcano). Considering the variation of the information through time, and their relationship with the structural setting of the volcano, datasets we are also able to define an a posteriori probability map for next vent opening. For short-term forecasting vent opening hazard assessment, the monitoring has a leading role, primarily based on seismological and volcanological data, integrated with strain, geochemical, gravimetric and magnetic parameters. In the code, is necessary to fix an appropriate forecasting time window. On open-conduit volcanoes as Mt. Etna, a forecast time window of a month (as fixed in other applications worldwide) seems unduly long, because variations of the state of the volcano (significant variation of a specific monitoring parameter could occur in time scale shorter than the forecasting time window) are expected with shorter time scale (hour, day or week). This leads to set a week as forecasting time window, coherently with the number of weeks in which an unrest has been experienced. The short-term vent opening hazard assessment will be estimated during an unrest phase; the testing case (2001 July eruption) will include all the monitoring parameters collected at Mt. Etna during the six months preceding the eruption. The monitoring role has been assessed eliciting more than 50 parameters, including seismic activity, ground deformation, geochemistry, gravity, magnetism, and distributed inside the first three nodes of the procedure. Parameter values describe the Mt. Etna volcano activity, being more detailed through the code, particularly in time units. The methodology allows all assumptions and thresholds to be clearly identified and provides a rational means for their revision if new data or information are incoming. References Newhall C.G. and Hoblitt R.P.; 2002: Constructing event trees for volcanic crises, Bull. Volcanol., 64, 3-20, doi: 10.1007/s0044500100173. Marzocchi W., Sandri L., Gasparini P., Newhall C. and Boschi E.; 2004: Quantifying probabilities of volcanic events: The example of volcanic hazard at Mount Vesuvius, J. Geophys. Res., 109, B11201, doi:10.1029/2004JB00315U. Marzocchi W., Sandri, L. and Selva, J.; 2008: BET_EF: a probabilistic tool for long- and short-term eruption forecasting, Bull. Volcanol., 70, 623 - 632, doi: 10.1007/s00445-007-0157-y.

Bayesian Techniques for Comparing Time-dependent GRMHD Simulations to Variable Event Horizon Telescope Observations

NASA Astrophysics Data System (ADS)

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

BAYESIAN TECHNIQUES FOR COMPARING TIME-DEPENDENT GRMHD SIMULATIONS TO VARIABLE EVENT HORIZON TELESCOPE OBSERVATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore themore » robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.« less

Quantifying MCMC exploration of phylogenetic tree space.

PubMed

Whidden, Chris; Matsen, Frederick A

2015-05-01

In order to gain an understanding of the effectiveness of phylogenetic Markov chain Monte Carlo (MCMC), it is important to understand how quickly the empirical distribution of the MCMC converges to the posterior distribution. In this article, we investigate this problem on phylogenetic tree topologies with a metric that is especially well suited to the task: the subtree prune-and-regraft (SPR) metric. This metric directly corresponds to the minimum number of MCMC rearrangements required to move between trees in common phylogenetic MCMC implementations. We develop a novel graph-based approach to analyze tree posteriors and find that the SPR metric is much more informative than simpler metrics that are unrelated to MCMC moves. In doing so, we show conclusively that topological peaks do occur in Bayesian phylogenetic posteriors from real data sets as sampled with standard MCMC approaches, investigate the efficiency of Metropolis-coupled MCMC (MCMCMC) in traversing the valleys between peaks, and show that conditional clade distribution (CCD) can have systematic problems when there are multiple peaks. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Application Bayesian Model Averaging method for ensemble system for Poland

NASA Astrophysics Data System (ADS)

Guzikowski, Jakub; Czerwinska, Agnieszka

2014-05-01

The aim of the project is to evaluate methods for generating numerical ensemble weather prediction using a meteorological data from The Weather Research & Forecasting Model and calibrating this data by means of Bayesian Model Averaging (WRF BMA) approach. We are constructing height resolution short range ensemble forecasts using meteorological data (temperature) generated by nine WRF's models. WRF models have 35 vertical levels and 2.5 km x 2.5 km horizontal resolution. The main emphasis is that the used ensemble members has a different parameterization of the physical phenomena occurring in the boundary layer. To calibrate an ensemble forecast we use Bayesian Model Averaging (BMA) approach. The BMA predictive Probability Density Function (PDF) is a weighted average of predictive PDFs associated with each individual ensemble member, with weights that reflect the member's relative skill. For test we chose a case with heat wave and convective weather conditions in Poland area from 23th July to 1st August 2013. From 23th July to 29th July 2013 temperature oscillated below or above 30 Celsius degree in many meteorology stations and new temperature records were added. During this time the growth of the hospitalized patients with cardiovascular system problems was registered. On 29th July 2013 an advection of moist tropical air masses was recorded in the area of Poland causes strong convection event with mesoscale convection system (MCS). MCS caused local flooding, damage to the transport infrastructure, destroyed buildings, trees and injuries and direct threat of life. Comparison of the meteorological data from ensemble system with the data recorded on 74 weather stations localized in Poland is made. We prepare a set of the model - observations pairs. Then, the obtained data from single ensemble members and median from WRF BMA system are evaluated on the basis of the deterministic statistical error Root Mean Square Error (RMSE), Mean Absolute Error (MAE). To evaluation probabilistic data The Brier Score (BS) and Continuous Ranked Probability Score (CRPS) were used. Finally comparison between BMA calibrated data and data from ensemble members will be displayed.

A Multilocus Molecular Phylogeny of the Parrots (Psittaciformes): Support for a Gondwanan Origin during the Cretaceous

PubMed Central

Schirtzinger, Erin E.; Matsumoto, Tania; Eberhard, Jessica R.; Graves, Gary R.; Sanchez, Juan J.; Capelli, Sara; Müller, Heinrich; Scharpegge, Julia; Chambers, Geoffrey K.; Fleischer, Robert C.

2008-01-01

The question of when modern birds (Neornithes) first diversified has generated much debate among avian systematists. Fossil evidence generally supports a Tertiary diversification, whereas estimates based on molecular dating favor an earlier diversification in the Cretaceous period. In this study, we used an alternate approach, the inference of historical biogeographic patterns, to test the hypothesis that the initial radiation of the Order Psittaciformes (the parrots and cockatoos) originated on the Gondwana supercontinent during the Cretaceous. We utilized broad taxonomic sampling (representatives of 69 of the 82 extant genera and 8 outgroup taxa) and multilocus molecular character sampling (3,941 bp from mitochondrial DNA (mtDNA) genes cytochrome oxidase I and NADH dehydrogenase 2 and nuclear introns of rhodopsin intron 1, tropomyosin alpha-subunit intron 5, and transforming growth factor ß-2) to generate phylogenetic hypotheses for the Psittaciformes. Analyses of the combined character partitions using maximum parsimony, maximum likelihood, and Bayesian criteria produced well-resolved and topologically similar trees in which the New Zealand taxa Strigops and Nestor (Psittacidae) were sister to all other psittaciforms and the cockatoo clade (Cacatuidae) was sister to a clade containing all remaining parrots (Psittacidae). Within this large clade of Psittacidae, some traditionally recognized tribes and subfamilies were monophyletic (e.g., Arini, Psittacini, and Loriinae), whereas several others were polyphyletic (e.g., Cyclopsittacini, Platycercini, Psittaculini, and Psittacinae). Ancestral area reconstructions using our Bayesian phylogenetic hypothesis and current distributions of genera supported the hypothesis of an Australasian origin for the Psittaciformes. Separate analyses of the timing of parrot diversification constructed with both Bayesian relaxed-clock and penalized likelihood approaches showed better agreement between geologic and diversification events in the chronograms based on a Cretaceous dating of the basal split within parrots than the chronograms based on a Tertiary dating of this split, although these data are more equivocal. Taken together, our results support a Cretaceous origin of Psittaciformes in Gondwana after the separation of Africa and the India/Madagascar block with subsequent diversification through both vicariance and dispersal. These well-resolved molecular phylogenies will be of value for comparative studies of behavior, ecology, and life history in parrots. PMID:18653733

Nonbinary Tree-Based Phylogenetic Networks.

PubMed

Jetten, Laura; van Iersel, Leo

2018-01-01

Rooted phylogenetic networks are used to describe evolutionary histories that contain non-treelike evolutionary events such as hybridization and horizontal gene transfer. In some cases, such histories can be described by a phylogenetic base-tree with additional linking arcs, which can, for example, represent gene transfer events. Such phylogenetic networks are called tree-based. Here, we consider two possible generalizations of this concept to nonbinary networks, which we call tree-based and strictly-tree-based nonbinary phylogenetic networks. We give simple graph-theoretic characterizations of tree-based and strictly-tree-based nonbinary phylogenetic networks. Moreover, we show for each of these two classes that it can be decided in polynomial time whether a given network is contained in the class. Our approach also provides a new view on tree-based binary phylogenetic networks. Finally, we discuss two examples of nonbinary phylogenetic networks in biology and show how our results can be applied to them.

Stand-structural effects on Heterobasidion abietinum-related mortality following drought events in Abies pinsapo.

PubMed

Linares, Juan Carlos; Camarero, Jesús Julio; Bowker, Matthew A; Ochoa, Victoria; Carreira, José Antonio

2010-12-01

Climate change may affect tree-pathogen interactions. This possibility has important implications for drought-prone forests, where stand dynamics and disease pathogenicity are especially sensitive to climatic stress. In addition, stand structural attributes including density-dependent tree-to-tree competition may modulate the stands' resistance to drought events and pathogen outbreaks. To assess the effects of stand structure on root-rot-related mortality after severe droughts, we focused on Heterobasidion abietinum mortality in relict Spanish stands of Abies pinsapo, a drought-sensitive fir. We compared stand attributes and tree spatial patterns in three plots with H. abietinum root-rot disease and three plots without root-rot. Point-pattern analyses were used to investigate the scale and extent of mortality patterns and to test hypotheses related to the spread of the disease. Dendrochronology was used to date the year of death and to assess the association between droughts and growth decline. We applied a structural equation modelling approach to test if tree mortality occurs more rapidly than predicted by a simple distance model when trees are subjected to high tree-to-tree competition and following drought events. Contrary to expectations of drought mortality, the effect of precipitation on the year of death was strong and negative, indicating that a period of high precipitation induced an earlier tree death. Competition intensity, related to the size and density of neighbour trees, also induced an earlier tree death. The effect of distance to the disease focus was negligible except in combination with intensive competition. Our results indicate that infected trees have decreased ability to withstand drought stress, and demonstrate that tree-to-tree competition and fungal infection act as predisposing factors of forest decline and mortality.

CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data

PubMed Central

Weiss, Scott T.

2014-01-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com. PMID:24922310

CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.

PubMed

McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T

2014-06-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

Multi-gene phylogeny of jacks and pompanos (Carangidae), including placement of monotypic vadigo Campogramma glaycos.

PubMed

Damerau, M; Freese, M; Hanel, R

2018-01-01

In this study, the phylogenetic trees of jacks and pompanos (Carangidae), an ecologically and morphologically diverse, globally distributed fish family, are inferred from a complete, concatenated data set of two mitochondrial (cytochrome c oxidase I, cytochrome b) loci and one nuclear (myosin heavy chain 6) locus. Maximum likelihood and Bayesian inferences are largely congruent and show a clear separation of Carangidae into the four subfamilies: Scomberoidinae, Trachinotinae, Naucratinae and Caranginae. The inclusion of the carangid sister lineages Coryphaenidae (dolphinfishes) and Rachycentridae (cobia), however, render Carangidae paraphyletic. The phylogenetic trees also show with high statistical support that the monotypic vadigo Campogramma glaycos is the sister to all other species within the Naucratinae. © 2017 The Fisheries Society of the British Isles.

Trans-dimensional and hierarchical Bayesian approaches toward rigorous estimation of seismic sources and structures in the Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, Seongryong; Tkalčić, Hrvoje; Mustać, Marija; Rhie, Junkee; Ford, Sean

2016-04-01

A framework is presented within which we provide rigorous estimations for seismic sources and structures in the Northeast Asia. We use Bayesian inversion methods, which enable statistical estimations of models and their uncertainties based on data information. Ambiguities in error statistics and model parameterizations are addressed by hierarchical and trans-dimensional (trans-D) techniques, which can be inherently implemented in the Bayesian inversions. Hence reliable estimation of model parameters and their uncertainties is possible, thus avoiding arbitrary regularizations and parameterizations. Hierarchical and trans-D inversions are performed to develop a three-dimensional velocity model using ambient noise data. To further improve the model, we perform joint inversions with receiver function data using a newly developed Bayesian method. For the source estimation, a novel moment tensor inversion method is presented and applied to regional waveform data of the North Korean nuclear explosion tests. By the combination of new Bayesian techniques and the structural model, coupled with meaningful uncertainties related to each of the processes, more quantitative monitoring and discrimination of seismic events is possible.

Understanding the recent colonization history of a plant pathogenic fungus using population genetic tools and Approximate Bayesian Computation

PubMed Central

Barrès, B; Carlier, J; Seguin, M; Fenouillet, C; Cilas, C; Ravigné, V

2012-01-01

Understanding the processes by which new diseases are introduced in previously healthy areas is of major interest in elaborating prevention and management policies, as well as in understanding the dynamics of pathogen diversity at large spatial scale. In this study, we aimed to decipher the dispersal processes that have led to the emergence of the plant pathogenic fungus Microcyclus ulei, which is responsible for the South American Leaf Blight (SALB). This fungus has devastated rubber tree plantations across Latin America since the beginning of the twentieth century. As only imprecise historical information is available, the study of population evolutionary history based on population genetics appeared most appropriate. The distribution of genetic diversity in a continental sampling of four countries (Brazil, Ecuador, Guatemala and French Guiana) was studied using a set of 16 microsatellite markers developed specifically for this purpose. A very strong genetic structure was found (Fst=0.70), demonstrating that there has been no regular gene flow between Latin American M. ulei populations. Strong bottlenecks probably occurred at the foundation of each population. The most likely scenario of colonization identified by the Approximate Bayesian Computation (ABC) method implemented in 𝒟ℐ𝒴𝒜ℬ𝒞 suggested two independent sources from the Amazonian endemic area. The Brazilian, Ecuadorian and Guatemalan populations might stem from serial introductions through human-mediated movement of infected plant material from an unsampled source population, whereas the French Guiana population seems to have arisen from an independent colonization event through spore dispersal. PMID:22828899

Nuclear introns outperform mitochondrial DNA in inter-specific phylogenetic reconstruction: Lessons from horseshoe bats (Rhinolophidae: Chiroptera).

PubMed

Dool, Serena E; Puechmaille, Sebastien J; Foley, Nicole M; Allegrini, Benjamin; Bastian, Anna; Mutumi, Gregory L; Maluleke, Tinyiko G; Odendaal, Lizelle J; Teeling, Emma C; Jacobs, David S

2016-04-01

Despite many studies illustrating the perils of utilising mitochondrial DNA in phylogenetic studies, it remains one of the most widely used genetic markers for this purpose. Over the last decade, nuclear introns have been proposed as alternative markers for phylogenetic reconstruction. However, the resolution capabilities of mtDNA and nuclear introns have rarely been quantified and compared. In the current study we generated a novel ∼5kb dataset comprising six nuclear introns and a mtDNA fragment. We assessed the relative resolution capabilities of the six intronic fragments with respect to each other, when used in various combinations together, and when compared to the traditionally used mtDNA. We focused on a major clade in the horseshoe bat family (Afro-Palaearctic clade; Rhinolophidae) as our case study. This old, widely distributed and speciose group contains a high level of conserved morphology. This morphological stasis renders the reconstruction of the phylogeny of this group with traditional morphological characters complex. We sampled multiple individuals per species to represent their geographic distributions as best as possible (122 individuals, 24 species, 68 localities). We reconstructed the species phylogeny using several complementary methods (partitioned Maximum Likelihood and Bayesian and Bayesian multispecies-coalescent) and made inferences based on consensus across these methods. We computed pairwise comparisons based on Robinson-Foulds tree distance metric between all Bayesian topologies generated (27,000) for every gene(s) and visualised the tree space using multidimensional scaling (MDS) plots. Using our supported species phylogeny we estimated the ancestral state of key traits of interest within this group, e.g. echolocation peak frequency which has been implicated in speciation. Our results revealed many potential cryptic species within this group, even in taxa where this was not suspected a priori and also found evidence for mtDNA introgression. We demonstrated that by using just two introns one can recover a better supported species tree than when using the mtDNA alone, despite the shorter overall length of the combined introns. Additionally, when combining any single intron with mtDNA, we showed that the result is highly similar to the mtDNA gene tree and far from the true species tree and therefore this approach should be avoided. We caution against the indiscriminate use of mtDNA in phylogenetic studies and advocate for pilot studies to select nuclear introns. The selection of marker type and number is a crucial step that is best based on critical examination of preliminary or previously published data. Based on our findings and previous publications, we recommend the following markers to recover phylogenetic relationships between recently diverged taxa (<20 My) in bats and other mammals: ACOX2, COPS7A, BGN, ROGDI and STAT5A. Copyright © 2016 Elsevier Inc. All rights reserved.

Are trees long-lived?

Treesearch

Kevin T. Smith

2009-01-01

Trees and tree care can capture the best of people's motivations and intentions. Trees are living memorials that help communities heal at sites of national tragedy, such as Oklahoma City and the World Trade Center. We mark the places of important historical events by the trees that grew nearby even if the original tree, such as the Charter Oak in Connecticut or...

Application of IATA - A case study in evaluating the global and local performance of a Bayesian Network model for Skin Sensitization

EPA Science Inventory

Since the publication of the Adverse Outcome Pathway (AOP) for skin sensitization, there have been many efforts to develop systematic approaches to integrate the information generated from different key events for decision making. The types of information characterizing key event...

Plastid phylogenomics of the cool-season grass subfamily: clarification of relationships among early-diverging tribes

PubMed Central

Saarela, Jeffery M.; Wysocki, William P.; Barrett, Craig F.; Soreng, Robert J.; Davis, Jerrold I.; Clark, Lynn G.; Kelchner, Scot A.; Pires, J. Chris; Edger, Patrick P.; Mayfield, Dustin R.; Duvall, Melvin R.

2015-01-01

Whole plastid genomes are being sequenced rapidly from across the green plant tree of life, and phylogenetic analyses of these are increasing resolution and support for relationships that have varied among or been unresolved in earlier single- and multi-gene studies. Pooideae, the cool-season grass lineage, is the largest of the 12 grass subfamilies and includes important temperate cereals, turf grasses and forage species. Although numerous studies of the phylogeny of the subfamily have been undertaken, relationships among some ‘early-diverging’ tribes conflict among studies, and some relationships among subtribes of Poeae have not yet been resolved. To address these issues, we newly sequenced 25 whole plastomes, which showed rearrangements typical of Poaceae. These plastomes represent 9 tribes and 11 subtribes of Pooideae, and were analysed with 20 existing plastomes for the subfamily. Maximum likelihood (ML), maximum parsimony (MP) and Bayesian inference (BI) robustly resolve most deep relationships in the subfamily. Complete plastome data provide increased nodal support compared with protein-coding data alone at nodes that are not maximally supported. Following the divergence of Brachyelytrum, Phaenospermateae, Brylkinieae–Meliceae and Ampelodesmeae–Stipeae are the successive sister groups of the rest of the subfamily. Ampelodesmeae are nested within Stipeae in the plastome trees, consistent with its hybrid origin between a phaenospermatoid and a stipoid grass (the maternal parent). The core Pooideae are strongly supported and include Brachypodieae, a Bromeae–Triticeae clade and Poeae. Within Poeae, a novel sister group relationship between Phalaridinae and Torreyochloinae is found, and the relative branching order of this clade and Aveninae, with respect to an Agrostidinae–Brizinae clade, are discordant between MP and ML/BI trees. Maximum likelihood and Bayesian analyses strongly support Airinae and Holcinae as the successive sister groups of a Dactylidinae–Loliinae clade. PMID:25940204

Bayesian Models for Streamflow and River Network Reconstruction using Tree Rings

NASA Astrophysics Data System (ADS)

Ravindranath, A.; Devineni, N.

2016-12-01

Water systems face non-stationary, dynamically shifting risks due to shifting societal conditions and systematic long-term variations in climate manifesting as quasi-periodic behavior on multi-decadal time scales. Water systems are thus vulnerable to long periods of wet or dry hydroclimatic conditions. Streamflow is a major component of water systems and a primary means by which water is transported to serve ecosystems' and human needs. Thus, our concern is in understanding streamflow variability. Climate variability and impacts on water resources are crucial factors affecting streamflow, and multi-scale variability increases risk to water sustainability and systems. Dam operations are necessary for collecting water brought by streamflow while maintaining downstream ecological health. Rules governing dam operations are based on streamflow records that are woefully short compared to periods of systematic variation present in the climatic factors driving streamflow variability and non-stationarity. We use hierarchical Bayesian regression methods in order to reconstruct paleo-streamflow records for dams within a basin using paleoclimate proxies (e.g. tree rings) to guide the reconstructions. The riverine flow network for the entire basin is subsequently modeled hierarchically using feeder stream and tributary flows. This is a starting point in analyzing streamflow variability and risks to water systems, and developing a scientifically-informed dynamic risk management framework for formulating dam operations and water policies to best hedge such risks. We will apply this work to the Missouri and Delaware River Basins (DRB). Preliminary results of streamflow reconstructions for eight dams in the upper DRB using standard Gaussian regression with regional tree ring chronologies give streamflow records that now span two to two and a half centuries, and modestly smoothed versions of these reconstructed flows indicate physically-justifiable trends in the time series.

Overcoming deep roots, fast rates, and short internodes to resolve the ancient rapid radiation of eupolypod II ferns.

PubMed

Rothfels, Carl J; Larsson, Anders; Kuo, Li-Yaung; Korall, Petra; Chiou, Wen-Liang; Pryer, Kathleen M

2012-05-01

Backbone relationships within the large eupolypod II clade, which includes nearly a third of extant fern species, have resisted elucidation by both molecular and morphological data. Earlier studies suggest that much of the phylogenetic intractability of this group is due to three factors: (i) a long root that reduces apparent levels of support in the ingroup; (ii) long ingroup branches subtended by a series of very short backbone internodes (the "ancient rapid radiation" model); and (iii) significantly heterogeneous lineage-specific rates of substitution. To resolve the eupolypod II phylogeny, with a particular emphasis on the backbone internodes, we assembled a data set of five plastid loci (atpA, atpB, matK, rbcL, and trnG-R) from a sample of 81 accessions selected to capture the deepest divergences in the clade. We then evaluated our phylogenetic hypothesis against potential confounding factors, including those induced by rooting, ancient rapid radiation, rate heterogeneity, and the Bayesian star-tree paradox artifact. While the strong support we inferred for the backbone relationships proved robust to these potential problems, their investigation revealed unexpected model-mediated impacts of outgroup composition, divergent effects of methods for countering the star-tree paradox artifact, and gave no support to concerns about the applicability of the unrooted model to data sets with heterogeneous lineage-specific rates of substitution. This study is among few to investigate these factors with empirical data, and the first to compare the performance of the two primary methods for overcoming the Bayesian star-tree paradox artifact. Among the significant phylogenetic results is the near-complete support along the eupolypod II backbone, the demonstrated paraphyly of Woodsiaceae as currently circumscribed, and the well-supported placement of the enigmatic genera Homalosorus, Diplaziopsis, and Woodsia.

The role of hybridization in facilitating tree invasion

USDA-ARS?s Scientific Manuscript database

Hybridization events can generate additional genetic diversity on which natural selection can act and at times enhance invasiveness of the species. Invasive tree species are a growing ecological concern worldwide, and some of these invasions involve hybridization events pre- or post-introduction. Th...

Valence-Dependent Belief Updating: Computational Validation

PubMed Central

Kuzmanovic, Bojana; Rigoux, Lionel

2017-01-01

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments. PMID:28706499

Valence-Dependent Belief Updating: Computational Validation.

PubMed

Kuzmanovic, Bojana; Rigoux, Lionel

2017-01-01

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments.

A review for identification of initiating events in event tree development process on nuclear power plants

NASA Astrophysics Data System (ADS)

Riyadi, Eko H.

2014-09-01

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logic model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.

Enhancements of Bayesian Blocks; Application to Large Light Curve Databases

NASA Technical Reports Server (NTRS)

Scargle, Jeff

2015-01-01

Bayesian Blocks are optimal piecewise linear representations (step function fits) of light-curves. The simple algorithm implementing this idea, using dynamic programming, has been extended to include more data modes and fitness metrics, multivariate analysis, and data on the circle (Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations, Scargle, Norris, Jackson and Chiang 2013, ApJ, 764, 167), as well as new results on background subtraction and refinement of the procedure for precise timing of transient events in sparse data. Example demonstrations will include exploratory analysis of the Kepler light curve archive in a search for "star-tickling" signals from extraterrestrial civilizations. (The Cepheid Galactic Internet, Learned, Kudritzki, Pakvasa1, and Zee, 2008, arXiv: 0809.0339; Walkowicz et al., in progress).

Bayesian theories of conditioning in a changing world.

PubMed

Courville, Aaron C; Daw, Nathaniel D; Touretzky, David S

2006-07-01

The recent flowering of Bayesian approaches invites the re-examination of classic issues in behavior, even in areas as venerable as Pavlovian conditioning. A statistical account can offer a new, principled interpretation of behavior, and previous experiments and theories can inform many unexplored aspects of the Bayesian enterprise. Here we consider one such issue: the finding that surprising events provoke animals to learn faster. We suggest that, in a statistical account of conditioning, surprise signals change and therefore uncertainty and the need for new learning. We discuss inference in a world that changes and show how experimental results involving surprise can be interpreted from this perspective, and also how, thus understood, these phenomena help constrain statistical theories of animal and human learning.

Dendritic tree extraction from noisy maximum intensity projection images in C. elegans.

PubMed

Greenblum, Ayala; Sznitman, Raphael; Fua, Pascal; Arratia, Paulo E; Oren, Meital; Podbilewicz, Benjamin; Sznitman, Josué

2014-06-12

Maximum Intensity Projections (MIP) of neuronal dendritic trees obtained from confocal microscopy are frequently used to study the relationship between tree morphology and mechanosensory function in the model organism C. elegans. Extracting dendritic trees from noisy images remains however a strenuous process that has traditionally relied on manual approaches. Here, we focus on automated and reliable 2D segmentations of dendritic trees following a statistical learning framework. Our dendritic tree extraction (DTE) method uses small amounts of labelled training data on MIPs to learn noise models of texture-based features from the responses of tree structures and image background. Our strategy lies in evaluating statistical models of noise that account for both the variability generated from the imaging process and from the aggregation of information in the MIP images. These noisy models are then used within a probabilistic, or Bayesian framework to provide a coarse 2D dendritic tree segmentation. Finally, some post-processing is applied to refine the segmentations and provide skeletonized trees using a morphological thinning process. Following a Leave-One-Out Cross Validation (LOOCV) method for an MIP databse with available "ground truth" images, we demonstrate that our approach provides significant improvements in tree-structure segmentations over traditional intensity-based methods. Improvements for MIPs under various imaging conditions are both qualitative and quantitative, as measured from Receiver Operator Characteristic (ROC) curves and the yield and error rates in the final segmentations. In a final step, we demonstrate our DTE approach on previously unseen MIP samples including the extraction of skeletonized structures, and compare our method to a state-of-the art dendritic tree tracing software. Overall, our DTE method allows for robust dendritic tree segmentations in noisy MIPs, outperforming traditional intensity-based methods. Such approach provides a useable segmentation framework, ultimately delivering a speed-up for dendritic tree identification on the user end and a reliable first step towards further morphological characterizations of tree arborization.

RecPhyloXML - a format for reconciled gene trees.

PubMed

Duchemin, Wandrille; Gence, Guillaume; Arigon Chifolleau, Anne-Muriel; Arvestad, Lars; Bansal, Mukul S; Berry, Vincent; Boussau, Bastien; Chevenet, François; Comte, Nicolas; Davín, Adrián A; Dessimoz, Christophe; Dylus, David; Hasic, Damir; Mallo, Diego; Planel, Rémi; Posada, David; Scornavacca, Celine; Szöllosi, Gergely; Zhang, Louxin; Tannier, Éric; Daubin, Vincent

2018-05-14

A reconciliation is an annotation of the nodes of a gene tree with evolutionary events-for example, speciation, gene duplication, transfer, loss, etc-along with a mapping onto a species tree. Many algorithms and software produce or use reconciliations but often using different reconciliation formats, regarding the type of events considered or whether the species tree is dated or not. This complicates the comparison and communication between different programs. Here, we gather a consortium of software developers in gene tree species tree reconciliation to propose and endorse a format that aims to promote an integrative-albeit flexible-specification of phylogenetic reconciliations. This format, named recPhyloXML, is accompanied by several tools such as a reconciled tree visualizer and conversion utilities. http://phylariane.univ-lyon1.fr/recphyloxml/. wandrille.duchemin@univ-lyon1.fr. There is no supplementary data associated with this publication.

A semiparametric Bayesian proportional hazards model for interval censored data with frailty effects.

PubMed

Henschel, Volkmar; Engel, Jutta; Hölzel, Dieter; Mansmann, Ulrich

2009-02-10

Multivariate analysis of interval censored event data based on classical likelihood methods is notoriously cumbersome. Likelihood inference for models which additionally include random effects are not available at all. Developed algorithms bear problems for practical users like: matrix inversion, slow convergence, no assessment of statistical uncertainty. MCMC procedures combined with imputation are used to implement hierarchical models for interval censored data within a Bayesian framework. Two examples from clinical practice demonstrate the handling of clustered interval censored event times as well as multilayer random effects for inter-institutional quality assessment. The software developed is called survBayes and is freely available at CRAN. The proposed software supports the solution of complex analyses in many fields of clinical epidemiology as well as health services research.

Trending in Probability of Collision Measurements via a Bayesian Zero-Inflated Beta Mixed Model

NASA Technical Reports Server (NTRS)

Vallejo, Jonathon; Hejduk, Matt; Stamey, James

2015-01-01

We investigate the performance of a generalized linear mixed model in predicting the Probabilities of Collision (Pc) for conjunction events. Specifically, we apply this model to the log(sub 10) transformation of these probabilities and argue that this transformation yields values that can be considered bounded in practice. Additionally, this bounded random variable, after scaling, is zero-inflated. Consequently, we model these values using the zero-inflated Beta distribution, and utilize the Bayesian paradigm and the mixed model framework to borrow information from past and current events. This provides a natural way to model the data and provides a basis for answering questions of interest, such as what is the likelihood of observing a probability of collision equal to the effective value of zero on a subsequent observation.

Analytical simulation and PROFAT II: a new methodology and a computer automated tool for fault tree analysis in chemical process industries.

PubMed

Khan, F I; Abbasi, S A

2000-07-10

Fault tree analysis (FTA) is based on constructing a hypothetical tree of base events (initiating events) branching into numerous other sub-events, propagating the fault and eventually leading to the top event (accident). It has been a powerful technique used traditionally in identifying hazards in nuclear installations and power industries. As the systematic articulation of the fault tree is associated with assigning probabilities to each fault, the exercise is also sometimes called probabilistic risk assessment. But powerful as this technique is, it is also very cumbersome and costly, limiting its area of application. We have developed a new algorithm based on analytical simulation (named as AS-II), which makes the application of FTA simpler, quicker, and cheaper; thus opening up the possibility of its wider use in risk assessment in chemical process industries. Based on the methodology we have developed a computer-automated tool. The details are presented in this paper.

Large-scale wind disturbances promote tree diversity in a Central Amazon forest.

PubMed

Marra, Daniel Magnabosco; Chambers, Jeffrey Q; Higuchi, Niro; Trumbore, Susan E; Ribeiro, Gabriel H P M; Dos Santos, Joaquim; Negrón-Juárez, Robinson I; Reu, Björn; Wirth, Christian

2014-01-01

Canopy gaps created by wind-throw events, or blowdowns, create a complex mosaic of forest patches varying in disturbance intensity and recovery in the Central Amazon. Using field and remote sensing data, we investigated the short-term (four-year) effects of large (>2000 m(2)) blowdown gaps created during a single storm event in January 2005 near Manaus, Brazil, to study (i) how forest structure and composition vary with disturbance gradients and (ii) whether tree diversity is promoted by niche differentiation related to wind-throw events at the landscape scale. In the forest area affected by the blowdown, tree mortality ranged from 0 to 70%, and was highest on plateaus and slopes. Less impacted areas in the region affected by the blowdown had overlapping characteristics with a nearby unaffected forest in tree density (583 ± 46 trees ha(-1)) (mean ± 99% Confidence Interval) and basal area (26.7 ± 2.4 m(2) ha(-1)). Highly impacted areas had tree density and basal area as low as 120 trees ha(-1) and 14.9 m(2) ha(-1), respectively. In general, these structural measures correlated negatively with an index of tree mortality intensity derived from satellite imagery. Four years after the blowdown event, differences in size-distribution, fraction of resprouters, floristic composition and species diversity still correlated with disturbance measures such as tree mortality and gap size. Our results suggest that the gradients of wind disturbance intensity encompassed in large blowdown gaps (>2000 m(2)) promote tree diversity. Specialists for particular disturbance intensities existed along the entire gradient. The existence of species or genera taking an intermediate position between undisturbed and gap specialists led to a peak of rarefied richness and diversity at intermediate disturbance levels. A diverse set of species differing widely in requirements and recruitment strategies forms the initial post-disturbance cohort, thus lending a high resilience towards wind disturbances at the community level.

Large-Scale Wind Disturbances Promote Tree Diversity in a Central Amazon Forest

PubMed Central

Marra, Daniel Magnabosco; Chambers, Jeffrey Q.; Higuchi, Niro; Trumbore, Susan E.; Ribeiro, Gabriel H. P. M.; dos Santos, Joaquim; Negrón-Juárez, Robinson I.; Reu, Björn; Wirth, Christian

2014-01-01

Canopy gaps created by wind-throw events, or blowdowns, create a complex mosaic of forest patches varying in disturbance intensity and recovery in the Central Amazon. Using field and remote sensing data, we investigated the short-term (four-year) effects of large (>2000 m2) blowdown gaps created during a single storm event in January 2005 near Manaus, Brazil, to study (i) how forest structure and composition vary with disturbance gradients and (ii) whether tree diversity is promoted by niche differentiation related to wind-throw events at the landscape scale. In the forest area affected by the blowdown, tree mortality ranged from 0 to 70%, and was highest on plateaus and slopes. Less impacted areas in the region affected by the blowdown had overlapping characteristics with a nearby unaffected forest in tree density (583±46 trees ha−1) (mean±99% Confidence Interval) and basal area (26.7±2.4 m2 ha−1). Highly impacted areas had tree density and basal area as low as 120 trees ha−1 and 14.9 m2 ha−1, respectively. In general, these structural measures correlated negatively with an index of tree mortality intensity derived from satellite imagery. Four years after the blowdown event, differences in size-distribution, fraction of resprouters, floristic composition and species diversity still correlated with disturbance measures such as tree mortality and gap size. Our results suggest that the gradients of wind disturbance intensity encompassed in large blowdown gaps (>2000 m2) promote tree diversity. Specialists for particular disturbance intensities existed along the entire gradient. The existence of species or genera taking an intermediate position between undisturbed and gap specialists led to a peak of rarefied richness and diversity at intermediate disturbance levels. A diverse set of species differing widely in requirements and recruitment strategies forms the initial post-disturbance cohort, thus lending a high resilience towards wind disturbances at the community level. PMID:25099118

Large-Scale Wind Disturbances Promote Tree Diversity in a Central Amazon Forest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marra, Daniel Magnabosco; Chambers, Jeffrey Q.; Higuchi, Niro

Canopy gaps created by wind-throw events, or blowdowns, create a complex mosaic of forest patches varying in disturbance intensity and recovery in the Central Amazon. Using field and remote sensing data, we investigated the short-term (four-year) effects of large (>2000 m 2) blowdown gaps created during a single storm event in January 2005 near Manaus, Brazil, to study (i) how forest structure and composition vary with disturbance gradients and (ii) whether tree diversity is promoted by niche differentiation related to wind-throw events at the landscape scale. In the forest area affected by the blowdown, tree mortality ranged from 0 tomore » 70%, and was highest on plateaus and slopes. Less impacted areas in the region affected by the blowdown had overlapping characteristics with a nearby unaffected forest in tree density (583±46 trees ha -1) (mean±99% Confidence Interval) and basal area (26.7±2.4 m 2 ha -1). Highly impacted areas had tree density and basal area as low as 120 trees ha -1 and 14.9 m 2 ha -1, respectively. In general, these structural measures correlated negatively with an index of tree mortality intensity derived from satellite imagery. Four years after the blowdown event, differences in size-distribution, fraction of resprouters, floristic composition and species diversity still correlated with disturbance measures such as tree mortality and gap size. Our results suggest that the gradients of wind disturbance intensity encompassed in large blowdown gaps (>2000 m 2) promote tree diversity. Specialists for particular disturbance intensities existed along the entire gradient. The existence of species or genera taking an intermediate position between undisturbed and gap specialists led to a peak of rarefied richness and diversity at intermediate disturbance levels. A diverse set of species differing widely in requirements and recruitment strategies forms the initial post-disturbance cohort, thus lending a high resilience towards wind disturbances at the community level.« less

Large-Scale Wind Disturbances Promote Tree Diversity in a Central Amazon Forest

DOE PAGES

Marra, Daniel Magnabosco; Chambers, Jeffrey Q.; Higuchi, Niro; ...

2014-08-06

Canopy gaps created by wind-throw events, or blowdowns, create a complex mosaic of forest patches varying in disturbance intensity and recovery in the Central Amazon. Using field and remote sensing data, we investigated the short-term (four-year) effects of large (>2000 m 2) blowdown gaps created during a single storm event in January 2005 near Manaus, Brazil, to study (i) how forest structure and composition vary with disturbance gradients and (ii) whether tree diversity is promoted by niche differentiation related to wind-throw events at the landscape scale. In the forest area affected by the blowdown, tree mortality ranged from 0 tomore » 70%, and was highest on plateaus and slopes. Less impacted areas in the region affected by the blowdown had overlapping characteristics with a nearby unaffected forest in tree density (583±46 trees ha -1) (mean±99% Confidence Interval) and basal area (26.7±2.4 m 2 ha -1). Highly impacted areas had tree density and basal area as low as 120 trees ha -1 and 14.9 m 2 ha -1, respectively. In general, these structural measures correlated negatively with an index of tree mortality intensity derived from satellite imagery. Four years after the blowdown event, differences in size-distribution, fraction of resprouters, floristic composition and species diversity still correlated with disturbance measures such as tree mortality and gap size. Our results suggest that the gradients of wind disturbance intensity encompassed in large blowdown gaps (>2000 m 2) promote tree diversity. Specialists for particular disturbance intensities existed along the entire gradient. The existence of species or genera taking an intermediate position between undisturbed and gap specialists led to a peak of rarefied richness and diversity at intermediate disturbance levels. A diverse set of species differing widely in requirements and recruitment strategies forms the initial post-disturbance cohort, thus lending a high resilience towards wind disturbances at the community level.« less

A Bayesian framework to estimate diversification rates and their variation through time and space

PubMed Central

2011-01-01

Background Patterns of species diversity are the result of speciation and extinction processes, and molecular phylogenetic data can provide valuable information to derive their variability through time and across clades. Bayesian Markov chain Monte Carlo methods offer a promising framework to incorporate phylogenetic uncertainty when estimating rates of diversification. Results We introduce a new approach to estimate diversification rates in a Bayesian framework over a distribution of trees under various constant and variable rate birth-death and pure-birth models, and test it on simulated phylogenies. Furthermore, speciation and extinction rates and their posterior credibility intervals can be estimated while accounting for non-random taxon sampling. The framework is particularly suitable for hypothesis testing using Bayes factors, as we demonstrate analyzing dated phylogenies of Chondrostoma (Cyprinidae) and Lupinus (Fabaceae). In addition, we develop a model that extends the rate estimation to a meta-analysis framework in which different data sets are combined in a single analysis to detect general temporal and spatial trends in diversification. Conclusions Our approach provides a flexible framework for the estimation of diversification parameters and hypothesis testing while simultaneously accounting for uncertainties in the divergence times and incomplete taxon sampling. PMID:22013891

Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network

NASA Astrophysics Data System (ADS)

Li, Zhiqiang; Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu

2018-04-01

This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit.

Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping.

PubMed

Durand, Jean-Baptiste; Allard, Alix; Guitton, Baptiste; van de Weg, Eric; Bink, Marco C A M; Costes, Evelyne

2017-01-01

Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS) were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI) with an autoregressive coefficient (γ g ) efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γ g and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.

Good fences make for good neighbors but bad science: a review of what improves Bayesian reasoning and why

PubMed Central

Brase, Gary L.; Hill, W. Trey

2015-01-01

Bayesian reasoning, defined here as the updating of a posterior probability following new information, has historically been problematic for humans. Classic psychology experiments have tested human Bayesian reasoning through the use of word problems and have evaluated each participant’s performance against the normatively correct answer provided by Bayes’ theorem. The standard finding is of generally poor performance. Over the past two decades, though, progress has been made on how to improve Bayesian reasoning. Most notably, research has demonstrated that the use of frequencies in a natural sampling framework—as opposed to single-event probabilities—can improve participants’ Bayesian estimates. Furthermore, pictorial aids and certain individual difference factors also can play significant roles in Bayesian reasoning success. The mechanics of how to build tasks which show these improvements is not under much debate. The explanations for why naturally sampled frequencies and pictures help Bayesian reasoning remain hotly contested, however, with many researchers falling into ingrained “camps” organized around two dominant theoretical perspectives. The present paper evaluates the merits of these theoretical perspectives, including the weight of empirical evidence, theoretical coherence, and predictive power. By these criteria, the ecological rationality approach is clearly better than the heuristics and biases view. Progress in the study of Bayesian reasoning will depend on continued research that honestly, vigorously, and consistently engages across these different theoretical accounts rather than staying “siloed” within one particular perspective. The process of science requires an understanding of competing points of view, with the ultimate goal being integration. PMID:25873904

Good fences make for good neighbors but bad science: a review of what improves Bayesian reasoning and why.

PubMed

Brase, Gary L; Hill, W Trey

2015-01-01

Bayesian reasoning, defined here as the updating of a posterior probability following new information, has historically been problematic for humans. Classic psychology experiments have tested human Bayesian reasoning through the use of word problems and have evaluated each participant's performance against the normatively correct answer provided by Bayes' theorem. The standard finding is of generally poor performance. Over the past two decades, though, progress has been made on how to improve Bayesian reasoning. Most notably, research has demonstrated that the use of frequencies in a natural sampling framework-as opposed to single-event probabilities-can improve participants' Bayesian estimates. Furthermore, pictorial aids and certain individual difference factors also can play significant roles in Bayesian reasoning success. The mechanics of how to build tasks which show these improvements is not under much debate. The explanations for why naturally sampled frequencies and pictures help Bayesian reasoning remain hotly contested, however, with many researchers falling into ingrained "camps" organized around two dominant theoretical perspectives. The present paper evaluates the merits of these theoretical perspectives, including the weight of empirical evidence, theoretical coherence, and predictive power. By these criteria, the ecological rationality approach is clearly better than the heuristics and biases view. Progress in the study of Bayesian reasoning will depend on continued research that honestly, vigorously, and consistently engages across these different theoretical accounts rather than staying "siloed" within one particular perspective. The process of science requires an understanding of competing points of view, with the ultimate goal being integration.

Adult mortality in a low-density tree population using high-resolution remote sensing.

PubMed

Kellner, James R; Hubbell, Stephen P

2017-06-01

We developed a statistical framework to quantify mortality rates in canopy trees observed using time series from high-resolution remote sensing. By timing the acquisition of remote sensing data with synchronous annual flowering in the canopy tree species Handroanthus guayacan, we made 2,596 unique detections of 1,006 individual adult trees within 18,883 observation attempts on Barro Colorado Island, Panama (BCI) during an 11-yr period. There were 1,057 observation attempts that resulted in missing data due to cloud cover or incomplete spatial coverage. Using the fraction of 123 individuals from an independent field sample that were detected by satellite data (109 individuals, 88.6%), we estimate that the adult population for this species on BCI was 1,135 individuals. We used a Bayesian state-space model that explicitly accounted for the probability of tree detection and missing observations to compute an annual adult mortality rate of 0.2%·yr -1 (SE = 0.1, 95% CI = 0.06-0.45). An independent estimate of the adult mortality rate from 260 field-checked trees closely matched the landscape-scale estimate (0.33%·yr -1 , SE = 0.16, 95% CI = 0.12-0.74). Our proof-of-concept study shows that one can remotely estimate adult mortality rates for canopy tree species precisely in the presence of variable detection and missing observations. © 2017 by the Ecological Society of America.

When Absence of Evidence Is Evidence of Absence: Rational Inferences From Absent Data.

PubMed

Hsu, Anne S; Horng, Andy; Griffiths, Thomas L; Chater, Nick

2017-05-01

Identifying patterns in the world requires noticing not only unusual occurrences, but also unusual absences. We examined how people learn from absences, manipulating the extent to which an absence is expected. People can make two types of inferences from the absence of an event: either the event is possible but has not yet occurred, or the event never occurs. A rational analysis using Bayesian inference predicts that inferences from absent data should depend on how much the absence is expected to occur, with less probable absences being more salient. We tested this prediction in two experiments in which we elicited people's judgments about patterns in the data as a function of absence salience. We found that people were able to decide that absences either were mere coincidences or were indicative of a significant pattern in the data in a manner that was consistent with predictions of a simple Bayesian model. Copyright © 2016 Cognitive Science Society, Inc.

Exposure of trees to drought-induced die-off is defined by a common climatic threshold across different vegetation types

PubMed Central

Mitchell, Patrick J; O'Grady, Anthony P; Hayes, Keith R; Pinkard, Elizabeth A

2014-01-01

Increases in drought and temperature stress in forest and woodland ecosystems are thought to be responsible for the rise in episodic mortality events observed globally. However, key climatic drivers common to mortality events and the impacts of future extreme droughts on tree survival have not been evaluated. Here, we characterize climatic drivers associated with documented tree die-off events across Australia using standardized climatic indices to represent the key dimensions of drought stress for a range of vegetation types. We identify a common probabilistic threshold associated with an increased risk of die-off across all the sites that we examined. We show that observed die-off events occur when water deficits and maximum temperatures are high and exist outside 98% of the observed range in drought intensity; this threshold was evident at all sites regardless of vegetation type and climate. The observed die-off events also coincided with at least one heat wave (three consecutive days above the 90th percentile for maximum temperature), emphasizing a pivotal role of heat stress in amplifying tree die-off and mortality processes. The joint drought intensity and maximum temperature distributions were modeled for each site to describe the co-occurrence of both hot and dry conditions and evaluate future shifts in climatic thresholds associated with the die-off events. Under a relatively dry and moderate warming scenario, the frequency of droughts capable of inducing significant tree die-off across Australia could increase from 1 in 24 years to 1 in 15 years by 2050, accompanied by a doubling in the occurrence of associated heat waves. By defining commonalities in drought conditions capable of inducing tree die-off, we show a strong interactive effect of water and high temperature stress and provide a consistent approach for assessing changes in the exposure of ecosystems to extreme drought events. PMID:24772285

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

PubMed

Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

2010-12-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies conservation planning. Journal compilation © 2010 Society for Conservation Biology. No claim to original US government works.

Preventing medical errors by designing benign failures.

PubMed

Grout, John R

2003-07-01

One way to successfully reduce medical errors is to design health care systems that are more resistant to the tendencies of human beings to err. One interdisciplinary approach entails creating design changes, mitigating human errors, and making human error irrelevant to outcomes. This approach is intended to facilitate the creation of benign failures, which have been called mistake-proofing devices and forcing functions elsewhere. USING FAULT TREES TO DESIGN FORCING FUNCTIONS: A fault tree is a graphical tool used to understand the relationships that either directly cause or contribute to the cause of a particular failure. A careful analysis of a fault tree enables the analyst to anticipate how the process will behave after the change. EXAMPLE OF AN APPLICATION: A scenario in which a patient is scalded while bathing can serve as an example of how multiple fault trees can be used to design forcing functions. The first fault tree shows the undesirable event--patient scalded while bathing. The second fault tree has a benign event--no water. Adding a scald valve changes the outcome from the undesirable event ("patient scalded while bathing") to the benign event ("no water") Analysis of fault trees does not ensure or guarantee that changes necessary to eliminate error actually occur. Most mistake-proofing is used to prevent simple errors and to create well-defended processes, but complex errors can also result. The utilization of mistake-proofing or forcing functions can be thought of as changing the logic of a process. Errors that formerly caused undesirable failures can be converted into the causes of benign failures. The use of fault trees can provide a variety of insights into the design of forcing functions that will improve patient safety.

Boolean logic tree of graphene-based chemical system for molecular computation and intelligent molecular search query.

PubMed

Huang, Wei Tao; Luo, Hong Qun; Li, Nian Bing

2014-05-06

The most serious, and yet unsolved, problem of constructing molecular computing devices consists in connecting all of these molecular events into a usable device. This report demonstrates the use of Boolean logic tree for analyzing the chemical event network based on graphene, organic dye, thrombin aptamer, and Fenton reaction, organizing and connecting these basic chemical events. And this chemical event network can be utilized to implement fluorescent combinatorial logic (including basic logic gates and complex integrated logic circuits) and fuzzy logic computing. On the basis of the Boolean logic tree analysis and logic computing, these basic chemical events can be considered as programmable "words" and chemical interactions as "syntax" logic rules to construct molecular search engine for performing intelligent molecular search query. Our approach is helpful in developing the advanced logic program based on molecules for application in biosensing, nanotechnology, and drug delivery.

Widespread Amazon forest tree mortality from a single cross-basin squall line event

NASA Astrophysics Data System (ADS)

Negrón-Juárez, Robinson I.; Chambers, Jeffrey Q.; Guimaraes, Giuliano; Zeng, Hongcheng; Raupp, Carlos F. M.; Marra, Daniel M.; Ribeiro, Gabriel H. P. M.; Saatchi, Sassan S.; Nelson, Bruce W.; Higuchi, Niro

2010-08-01

Climate change is expected to increase the intensity of extreme precipitation events in Amazonia that in turn might produce more forest blowdowns associated with convective storms. Yet quantitative tree mortality associated with convective storms has never been reported across Amazonia, representing an important additional source of carbon to the atmosphere. Here we demonstrate that a single squall line (aligned cluster of convective storm cells) propagating across Amazonia in January, 2005, caused widespread forest tree mortality and may have contributed to the elevated mortality observed that year. Forest plot data demonstrated that the same year represented the second highest mortality rate over a 15-year annual monitoring interval. Over the Manaus region, disturbed forest patches generated by the squall followed a power-law distribution (scaling exponent α = 1.48) and produced a mortality of 0.3-0.5 million trees, equivalent to 30% of the observed annual deforestation reported in 2005 over the same area. Basin-wide, potential tree mortality from this one event was estimated at 542 ± 121 million trees, equivalent to 23% of the mean annual biomass accumulation estimated for these forests. Our results highlight the vulnerability of Amazon trees to wind-driven mortality associated with convective storms. Storm intensity is expected to increase with a warming climate, which would result in additional tree mortality and carbon release to the atmosphere, with the potential to further warm the climate system.

The effect of using genealogy-based haplotypes for genomic prediction

PubMed Central

2013-01-01

Background Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Conclusions Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy. PMID:23496971

The effect of using genealogy-based haplotypes for genomic prediction.

PubMed

Edriss, Vahid; Fernando, Rohan L; Su, Guosheng; Lund, Mogens S; Guldbrandtsen, Bernt

2013-03-06

Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy.

Implementing Bayesian networks with embedded stochastic MRAM

NASA Astrophysics Data System (ADS)

Faria, Rafatul; Camsari, Kerem Y.; Datta, Supriyo

2018-04-01

Magnetic tunnel junctions (MTJ's) with low barrier magnets have been used to implement random number generators (RNG's) and it has recently been shown that such an MTJ connected to the drain of a conventional transistor provides a three-terminal tunable RNG or a p-bit. In this letter we show how this p-bit can be used to build a p-circuit that emulates a Bayesian network (BN), such that the correlations in real world variables can be obtained from electrical measurements on the corresponding circuit nodes. The p-circuit design proceeds in two steps: the BN is first translated into a behavioral model, called Probabilistic Spin Logic (PSL), defined by dimensionless biasing (h) and interconnection (J) coefficients, which are then translated into electronic circuit elements. As a benchmark example, we mimic a family tree of three generations and show that the genetic relatedness calculated from a SPICE-compatible circuit simulator matches well-known results.

Assessing electronic health record systems in emergency departments: Using a decision analytic Bayesian model.

PubMed

Ben-Assuli, Ofir; Leshno, Moshe

2016-09-01

In the last decade, health providers have implemented information systems to improve accuracy in medical diagnosis and decision-making. This article evaluates the impact of an electronic health record on emergency department physicians' diagnosis and admission decisions. A decision analytic approach using a decision tree was constructed to model the admission decision process to assess the added value of medical information retrieved from the electronic health record. Using a Bayesian statistical model, this method was evaluated on two coronary artery disease scenarios. The results show that the cases of coronary artery disease were better diagnosed when the electronic health record was consulted and led to more informed admission decisions. Furthermore, the value of medical information required for a specific admission decision in emergency departments could be quantified. The findings support the notion that physicians and patient healthcare can benefit from implementing electronic health record systems in emergency departments. © The Author(s) 2015.

Synergy of extreme drought and shrub invasion reduce ecosystem functioning and resilience in water-limited climates

PubMed Central

Caldeira, Maria C.; Lecomte, Xavier; David, Teresa S.; Pinto, Joaquim G.; Bugalho, Miguel N.; Werner, Christiane

2015-01-01

Extreme drought events and plant invasions are major drivers of global change that can critically affect ecosystem functioning and alter ecosystem-atmosphere exchange. Invaders are expanding worldwide and extreme drought events are projected to increase in frequency and intensity. However, very little is known on how these drivers may interact to affect the functioning and resilience of ecosystems to extreme events. Using a manipulative shrub removal experiment and the co-occurrence of an extreme drought event (2011/2012) in a Mediterranean woodland, we show that native shrub invasion and extreme drought synergistically reduced ecosystem transpiration and the resilience of key-stone oak tree species. Ecosystem transpiration was dominated by the water use of the invasive shrub Cistus ladanifer, which further increased after the extreme drought event. Meanwhile, the transpiration of key-stone tree species decreased, indicating a competitive advantage in favour of the invader. Our results suggest that in Mediterranean-type climates the invasion of water spending species and projected recurrent extreme drought events may synergistically cause critical drought tolerance thresholds of key-stone tree species to be surpassed, corroborating observed higher tree mortality in the invaded ecosystems. Ultimately, this may shift seasonally water limited ecosystems into less desirable alternative states dominated by water spending invasive shrubs. PMID:26461978

Synergy of extreme drought and shrub invasion reduce ecosystem functioning and resilience in water-limited climates.

PubMed

Caldeira, Maria C; Lecomte, Xavier; David, Teresa S; Pinto, Joaquim G; Bugalho, Miguel N; Werner, Christiane

2015-10-13

Extreme drought events and plant invasions are major drivers of global change that can critically affect ecosystem functioning and alter ecosystem-atmosphere exchange. Invaders are expanding worldwide and extreme drought events are projected to increase in frequency and intensity. However, very little is known on how these drivers may interact to affect the functioning and resilience of ecosystems to extreme events. Using a manipulative shrub removal experiment and the co-occurrence of an extreme drought event (2011/2012) in a Mediterranean woodland, we show that native shrub invasion and extreme drought synergistically reduced ecosystem transpiration and the resilience of key-stone oak tree species. Ecosystem transpiration was dominated by the water use of the invasive shrub Cistus ladanifer, which further increased after the extreme drought event. Meanwhile, the transpiration of key-stone tree species decreased, indicating a competitive advantage in favour of the invader. Our results suggest that in Mediterranean-type climates the invasion of water spending species and projected recurrent extreme drought events may synergistically cause critical drought tolerance thresholds of key-stone tree species to be surpassed, corroborating observed higher tree mortality in the invaded ecosystems. Ultimately, this may shift seasonally water limited ecosystems into less desirable alternative states dominated by water spending invasive shrubs.

Synergy of extreme drought and shrub invasion reduce ecosystem functioning and resilience in water-limited climates

NASA Astrophysics Data System (ADS)

Caldeira, Maria C.; Lecomte, Xavier; David, Teresa S.; Pinto, Joaquim G.; Bugalho, Miguel N.; Werner, Christiane

2015-10-01

Extreme drought events and plant invasions are major drivers of global change that can critically affect ecosystem functioning and alter ecosystem-atmosphere exchange. Invaders are expanding worldwide and extreme drought events are projected to increase in frequency and intensity. However, very little is known on how these drivers may interact to affect the functioning and resilience of ecosystems to extreme events. Using a manipulative shrub removal experiment and the co-occurrence of an extreme drought event (2011/2012) in a Mediterranean woodland, we show that native shrub invasion and extreme drought synergistically reduced ecosystem transpiration and the resilience of key-stone oak tree species. Ecosystem transpiration was dominated by the water use of the invasive shrub Cistus ladanifer, which further increased after the extreme drought event. Meanwhile, the transpiration of key-stone tree species decreased, indicating a competitive advantage in favour of the invader. Our results suggest that in Mediterranean-type climates the invasion of water spending species and projected recurrent extreme drought events may synergistically cause critical drought tolerance thresholds of key-stone tree species to be surpassed, corroborating observed higher tree mortality in the invaded ecosystems. Ultimately, this may shift seasonally water limited ecosystems into less desirable alternative states dominated by water spending invasive shrubs.

Improved Accuracy Using Recursive Bayesian Estimation Based Language Model Fusion in ERP-Based BCI Typing Systems

PubMed Central

Orhan, U.; Erdogmus, D.; Roark, B.; Oken, B.; Purwar, S.; Hild, K. E.; Fowler, A.; Fried-Oken, M.

2013-01-01

RSVP Keyboard™ is an electroencephalography (EEG) based brain computer interface (BCI) typing system, designed as an assistive technology for the communication needs of people with locked-in syndrome (LIS). It relies on rapid serial visual presentation (RSVP) and does not require precise eye gaze control. Existing BCI typing systems which uses event related potentials (ERP) in EEG suffer from low accuracy due to low signal-to-noise ratio. Henceforth, RSVP Keyboard™ utilizes a context based decision making via incorporating a language model, to improve the accuracy of letter decisions. To further improve the contributions of the language model, we propose recursive Bayesian estimation, which relies on non-committing string decisions, and conduct an offline analysis, which compares it with the existing naïve Bayesian fusion approach. The results indicate the superiority of the recursive Bayesian fusion and in the next generation of RSVP Keyboard™ we plan to incorporate this new approach. PMID:23366432

Application of a predictive Bayesian model to environmental accounting.

PubMed

Anex, R P; Englehardt, J D

2001-03-30

Environmental accounting techniques are intended to capture important environmental costs and benefits that are often overlooked in standard accounting practices. Environmental accounting methods themselves often ignore or inadequately represent large but highly uncertain environmental costs and costs conditioned by specific prior events. Use of a predictive Bayesian model is demonstrated for the assessment of such highly uncertain environmental and contingent costs. The predictive Bayesian approach presented generates probability distributions for the quantity of interest (rather than parameters thereof). A spreadsheet implementation of a previously proposed predictive Bayesian model, extended to represent contingent costs, is described and used to evaluate whether a firm should undertake an accelerated phase-out of its PCB containing transformers. Variability and uncertainty (due to lack of information) in transformer accident frequency and severity are assessed simultaneously using a combination of historical accident data, engineering model-based cost estimates, and subjective judgement. Model results are compared using several different risk measures. Use of the model for incorporation of environmental risk management into a company's overall risk management strategy is discussed.

A simple Bayesian approach to quantifying confidence level of adverse event incidence proportion in small samples.

PubMed

Liu, Fang

2016-01-01

In both clinical development and post-marketing of a new therapy or a new treatment, incidence of an adverse event (AE) is always a concern. When sample sizes are small, large sample-based inferential approaches on an AE incidence proportion in a certain time period no longer apply. In this brief discussion, we introduce a simple Bayesian framework to quantify, in small sample studies and the rare AE case, (1) the confidence level that the incidence proportion of a particular AE p is over or below a threshold, (2) the lower or upper bounds on p with a certain level of confidence, and (3) the minimum required number of patients with an AE before we can be certain that p surpasses a specific threshold, or the maximum allowable number of patients with an AE after which we can no longer be certain that p is below a certain threshold, given a certain confidence level. The method is easy to understand and implement; the interpretation of the results is intuitive. This article also demonstrates the usefulness of simple Bayesian concepts when it comes to answering practical questions.

SIG-VISA: Signal-based Vertically Integrated Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Mayeda, K. M.; Myers, S. C.; Russell, S.

2013-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software; however, while such detections may constitute a useful summary of station activity, they discard large amounts of information present in the original recorded signal. We present SIG-VISA (Signal-based Vertically Integrated Seismic Analysis), a system for seismic monitoring through Bayesian inference on seismic signals. By directly modeling the recorded signal, our approach incorporates additional information unavailable to detection-based methods, enabling higher sensitivity and more accurate localization using techniques such as waveform matching. SIG-VISA's Bayesian forward model of seismic signal envelopes includes physically-derived models of travel times and source characteristics as well as Gaussian process (kriging) statistical models of signal properties that combine interpolation of historical data with extrapolation of learned physical trends. Applying Bayesian inference, we evaluate the model on earthquakes as well as the 2009 DPRK test event, demonstrating a waveform matching effect as part of the probabilistic inference, along with results on event localization and sensitivity. In particular, we demonstrate increased sensitivity from signal-based modeling, in which the SIGVISA signal model finds statistical evidence for arrivals even at stations for which the IMS station processing failed to register any detection.

A review for identification of initiating events in event tree development process on nuclear power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riyadi, Eko H., E-mail: e.riyadi@bapeten.go.id

2014-09-30

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logicmore » model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.« less

Choosing and Using Introns in Molecular Phylogenetics

PubMed Central

Creer, Simon

2007-01-01

Introns are now commonly used in molecular phylogenetics in an attempt to recover gene trees that are concordant with species trees, but there are a range of genomic, logistical and analytical considerations that are infrequently discussed in empirical studies that utilize intron data. This review outlines expedient approaches for locus selection, overcoming paralogy problems, recombination detection methods and the identification and incorporation of LVHs in molecular systematics. A range of parsimony and Bayesian analytical approaches are also described in order to highlight the methods that can currently be employed to align sequences and treat indels in subsequent analyses. By covering the main points associated with the generation and analysis of intron data, this review aims to provide a comprehensive introduction to using introns (or any non-coding nuclear data partition) in contemporary phylogenetics. PMID:19461984

Detection of fraudulent financial statements using the hybrid data mining approach.

PubMed

Chen, Suduan

2016-01-01

The purpose of this study is to construct a valid and rigorous fraudulent financial statement detection model. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements between the years 2002 and 2013. In the first stage, two decision tree algorithms, including the classification and regression trees (CART) and the Chi squared automatic interaction detector (CHAID) are applied in the selection of major variables. The second stage combines CART, CHAID, Bayesian belief network, support vector machine and artificial neural network in order to construct fraudulent financial statement detection models. According to the results, the detection performance of the CHAID-CART model is the most effective, with an overall accuracy of 87.97 % (the FFS detection accuracy is 92.69 %).

Patterns of drought tolerance in major European temperate forest trees: climatic drivers and levels of variability.

PubMed

Zang, Christian; Hartl-Meier, Claudia; Dittmar, Christoph; Rothe, Andreas; Menzel, Annette

2014-12-01

The future performance of native tree species under climate change conditions is frequently discussed, since increasingly severe and more frequent drought events are expected to become a major risk for forest ecosystems. To improve our understanding of the drought tolerance of the three common European temperate forest tree species Norway spruce, silver fir and common beech, we tested the influence of climate and tree-specific traits on the inter and intrasite variability in drought responses of these species. Basal area increment data from a large tree-ring network in Southern Germany and Alpine Austria along a climatic cline from warm-dry to cool-wet conditions were used to calculate indices of tolerance to drought events and their variability at the level of individual trees and populations. General patterns of tolerance indicated a high vulnerability of Norway spruce in comparison to fir and beech and a strong influence of bioclimatic conditions on drought response for all species. On the level of individual trees, low-growth rates prior to drought events, high competitive status and low age favored resilience in growth response to drought. Consequently, drought events led to heterogeneous and variable response patterns in forests stands. These findings may support the idea of deliberately using spontaneous selection and adaption effects as a passive strategy of forest management under climate change conditions, especially a strong directional selection for more tolerant individuals when frequency and intensity of summer droughts will increase in the course of global climate change. © 2014 John Wiley & Sons Ltd.

Models and simulation of 3D neuronal dendritic trees using Bayesian networks.

PubMed

López-Cruz, Pedro L; Bielza, Concha; Larrañaga, Pedro; Benavides-Piccione, Ruth; DeFelipe, Javier

2011-12-01

Neuron morphology is crucial for neuronal connectivity and brain information processing. Computational models are important tools for studying dendritic morphology and its role in brain function. We applied a class of probabilistic graphical models called Bayesian networks to generate virtual dendrites from layer III pyramidal neurons from three different regions of the neocortex of the mouse. A set of 41 morphological variables were measured from the 3D reconstructions of real dendrites and their probability distributions used in a machine learning algorithm to induce the model from the data. A simulation algorithm is also proposed to obtain new dendrites by sampling values from Bayesian networks. The main advantage of this approach is that it takes into account and automatically locates the relationships between variables in the data instead of using predefined dependencies. Therefore, the methodology can be applied to any neuronal class while at the same time exploiting class-specific properties. Also, a Bayesian network was defined for each part of the dendrite, allowing the relationships to change in the different sections and to model heterogeneous developmental factors or spatial influences. Several univariate statistical tests and a novel multivariate test based on Kullback-Leibler divergence estimation confirmed that virtual dendrites were similar to real ones. The analyses of the models showed relationships that conform to current neuroanatomical knowledge and support model correctness. At the same time, studying the relationships in the models can help to identify new interactions between variables related to dendritic morphology.

A molecular phylogeny of the Canidae based on six nuclear loci.

PubMed

Bardeleben, Carolyne; Moore, Rachael L; Wayne, Robert K

2005-12-01

We have reconstructed the phylogenetic relationships of 23 species in the dog family, Canidae, using DNA sequence data from six nuclear loci. Individual gene trees were generated with maximum parsimony (MP) and maximum likelihood (ML) analysis. In general, these individual gene trees were not well resolved, but several identical groupings were supported by more than one locus. Phylogenetic analysis with a data set combining the six nuclear loci using MP, ML, and Bayesian approaches produced a more resolved tree that agreed with previously published mitochondrial trees in finding three well-defined clades, including the red fox-like canids, the South American foxes, and the wolf-like canids. In addition, the nuclear data set provides novel indel support for several previously inferred clades. Differences between trees derived from the nuclear data and those from the mitochondrial data include the grouping of the bush dog and maned wolf into a clade with the South American foxes, the grouping of the side-striped jackal (Canis adustus) and black-backed jackal (Canis mesomelas) and the grouping of the bat-eared fox (Otocyon megalotis) with the raccoon dog (Nycteruetes procyonoides). We also analyzed the combined nuclear+mitochondrial tree. Many nodes that were strongly supported in the nuclear tree or the mitochondrial tree remained strongly supported in the nuclear+mitochondrial tree. Relationships within the clades containing the red fox-like canids and South American canids are well resolved, whereas the relationships among the wolf-like canids remain largely undetermined. The lack of resolution within the wolf-like canids may be due to their recent divergence and insufficient time for the accumulation of phylogenetically informative signal.

Reduced dry season transpiration is coupled with shallow soil water use in tropical montane forest trees.

PubMed

Muñoz-Villers, Lyssette E; Holwerda, Friso; Alvarado-Barrientos, M Susana; Geissert, Daniel R; Dawson, Todd E

2018-06-25

Tropical montane cloud forests (TMCF) are ecosystems particularly sensitive to climate change; however, the effects of warmer and drier conditions on TMCF ecohydrology remain poorly understood. To investigate functional responses of TMCF trees to reduced water availability, we conducted a study during the 2014 dry season in the lower altitudinal limit of TMCF in central Veracruz, Mexico. Temporal variations of transpiration, depth of water uptake and tree water sources were examined for three dominant, brevi-deciduous species using micrometeorological, sap flow and soil moisture measurements, in combination with oxygen and hydrogen stable isotope composition of rainfall, tree xylem, soil and stream water. Over the course of the dry season, reductions in crown conductance and transpiration were observed in canopy species (43 and 34%, respectively) and mid-story trees (23 and 8%), as atmospheric demand increased and soil moisture decreased. Canopy species consistently showed more depleted isotope values compared to mid-story trees. However, MixSIAR Bayesian model results showed that the evaporated (enriched) soil water pool was the main source for trees despite reduced soil moisture. Additionally, while increases in tree water uptake from deeper to shallower soil water sources occurred, concomitant decreases in transpiration were observed as the dry season progressed. A larger reduction in deep soil water use was observed for canopy species (from 79 ± 19 to 24 ± 20%) compared to mid-story trees (from 12 ± 17 to 10 ± 12%). The increase in shallower soil water sources may reflect a trade-off between water and nutrient requirements in this forest.

Structural system reliability calculation using a probabilistic fault tree analysis method

NASA Technical Reports Server (NTRS)

Torng, T. Y.; Wu, Y.-T.; Millwater, H. R.

1992-01-01

The development of a new probabilistic fault tree analysis (PFTA) method for calculating structural system reliability is summarized. The proposed PFTA procedure includes: developing a fault tree to represent the complex structural system, constructing an approximation function for each bottom event, determining a dominant sampling sequence for all bottom events, and calculating the system reliability using an adaptive importance sampling method. PFTA is suitable for complicated structural problems that require computer-intensive computer calculations. A computer program has been developed to implement the PFTA.

Bayesian statistical inference enhances the interpretation of contemporary randomized controlled trials.

PubMed

Wijeysundera, Duminda N; Austin, Peter C; Hux, Janet E; Beattie, W Scott; Laupacis, Andreas

2009-01-01

Randomized trials generally use "frequentist" statistics based on P-values and 95% confidence intervals. Frequentist methods have limitations that might be overcome, in part, by Bayesian inference. To illustrate these advantages, we re-analyzed randomized trials published in four general medical journals during 2004. We used Medline to identify randomized superiority trials with two parallel arms, individual-level randomization and dichotomous or time-to-event primary outcomes. Studies with P<0.05 in favor of the intervention were deemed "positive"; otherwise, they were "negative." We used several prior distributions and exact conjugate analyses to calculate Bayesian posterior probabilities for clinically relevant effects. Of 88 included studies, 39 were positive using a frequentist analysis. Although the Bayesian posterior probabilities of any benefit (relative risk or hazard ratio<1) were high in positive studies, these probabilities were lower and variable for larger benefits. The positive studies had only moderate probabilities for exceeding the effects that were assumed for calculating the sample size. By comparison, there were moderate probabilities of any benefit in negative studies. Bayesian and frequentist analyses complement each other when interpreting the results of randomized trials. Future reports of randomized trials should include both.

Diversification of the silverspot butterflies (Nymphalidae) in the Neotropics inferred from multi-locus DNA sequences.

PubMed

Massardo, Darli; Fornel, Rodrigo; Kronforst, Marcus; Gonçalves, Gislene Lopes; Moreira, Gilson Rudinei Pires

2015-01-01

The tribe Heliconiini (Lepidoptera: Nymphalidae) is a diverse group of butterflies distributed throughout the Neotropics, which has been studied extensively, in particular the genus Heliconius. However, most of the other lineages, such as Dione, which are less diverse and considered basal within the group, have received little attention. Basic information, such as species limits and geographical distributions remain uncertain for this genus. Here we used multilocus DNA sequence data and the geographical distribution analysis across the entire range of Dione in the Neotropical region in order to make inferences on the evolutionary history of this poorly explored lineage. Bayesian time-tree reconstruction allows inferring two major diversification events in this tribe around 25mya. Lineages thought to be ancient, such as Dione and Agraulis, are as recent as Heliconius. Dione formed a monophyletic clade, sister to the genus Agraulis. Dione juno, D. glycera and D. moneta were reciprocally monophyletic and formed genetic clusters, with the first two more close related than each other in relation to the third. Divergence time estimates support the hypothesis that speciation in Dione coincided with both the rise of Passifloraceae (the host plants) and the uplift of the Andes. Since the sister species D. glycera and D. moneta are specialized feeders on passion-vine lineages that are endemic to areas located either within or adjacent to the Andes, we inferred that they co-speciated with their host plants during this vicariant event. Copyright © 2014 Elsevier Inc. All rights reserved.

Prevalence of cryptic species in morphologically uniform taxa - fast speciation and evolutionary radiation in Asian toads.

PubMed

Liu, Zuyao; Chen, Guoling; Zhu, Tianqi; Zeng, Zhaochi; Lyu, Zhitong; Wang, Jian; Messenger, Kevin; Greenberg, Anthony J; Guo, Zixiao; Yang, Ziheng; Shi, Suhua; Wang, Yingyong

2018-06-16

Diversity and distributions of cryptic species have long been a vexing issue. Identification of species boundaries is made difficult by the lack of obvious morphological differences. Here, we investigate the cryptic diversity and evolutionary history of an underappreciated group of Asian frog species (Megophrys) to explore the pattern and dynamic of amphibian cryptic species. We sequenced four mitochondrial genes and five nuclear genes and delineated species using multiple approaches, combining DNA and mating-call data. A Bayesian species tree was generated to estimate divergence times and to reconstruct ancestral ranges. Macroevolutionary analyses and hybridization tests were conducted to explore the evolutionary dynamics of this cryptic group. Our phylogenies support the current subgenera. We revealed 43 cryptic species, 158% higher than previously thought. The species-delimitation results were further confirmed by mating-call data and morphological divergence. We found that these Asian frogss entered China from the Sunda Shelf 48 Mya, followed by an ancient radiation event during middle Miocene. We confirmed the efficiency of the multispecies coalescent model for delimitation of species with low morphological diversity. Species diversity of Megophrys is severely underappreciated, and species distributions have been misestimated as a result. Copyright © 2018. Published by Elsevier Inc.

Multi-Phase US Spread and Habitat Switching of a Post-Columbian Invasive, Sorghum halepense

PubMed Central

Barney, Jacob N.; Atwater, Daniel Z.; Pederson, Gary A.; Pederson, Jeffrey F.; Chandler, J. Mike; Cox, T. Stan; Cox, Sheila; Dotray, Peter; Kopec, David; Smith, Steven E.; Schroeder, Jill; Wright, Steven D.; Jiao, Yuannian; Kong, Wenqian; Goff, Valorie; Auckland, Susan; Rainville, Lisa K.; Pierce, Gary J.; Lemke, Cornelia; Compton, Rosana; Phillips, Christine; Kerr, Alexandra; Mettler, Matthew; Paterson, Andrew H.

2016-01-01

Johnsongrass (Sorghum halepense) is a striking example of a post-Columbian founder event. This natural experiment within ecological time-scales provides a unique opportunity for understanding patterns of continent-wide genetic diversity following range expansion. Microsatellite markers were used for population genetic analyses including leaf-optimized Neighbor-Joining tree, pairwise FST, mismatch analysis, principle coordinate analysis, Tajima’s D, Fu’s F and Bayesian clusterings of population structure. Evidence indicates two geographically distant introductions of divergent genotypes, which spread across much of the US in <200 years. Based on geophylogeny, gene flow patterns can be inferred to have involved five phases. Centers of genetic diversity have shifted from two introduction sites separated by ~2000 miles toward the middle of the range, consistent with admixture between genotypes from the respective introductions. Genotyping provides evidence for a ‘habitat switch’ from agricultural to non-agricultural systems and may contribute to both Johnsongrass ubiquity and aggressiveness. Despite lower and more structured diversity at the invasion front, Johnsongrass continues to advance northward into cooler and drier habitats. Association genetic approaches may permit identification of alleles contributing to the habitat switch or other traits important to weed/invasive management and/or crop improvement. PMID:27755565

Combining morphometrics with molecular taxonomy: how different are similar foliose keratose sponges from the Australian tropics?

PubMed

Abdul Wahab, M A; Fromont, J; Whalan, S; Webster, N; Andreakis, N

2014-04-01

Sponge taxonomy can be challenging as many groups exhibit extreme morphological plasticity induced by local environmental conditions. Foliose keratose sponges of the sub-family Phyllospongiinae (Dictyoceratida, Thorectidae: Strepsichordaia, Phyllospongia and Carteriospongia) are commonly found in intertidal and subtidal habitats of the Indo-Pacific. Lacking spicules, these sponges can be difficult to differentiate due to the lack of reliable morphological characters for species delineation. We use molecular phylogenies inferred from the nuclear Internal Transcribed Spacer 2 region (ITS2) and morphometrics (19 characters; 52 character states) to identify evolutionarily significant units (ESUs; sensu Moritz) within foliose Phyllosponginiids collected from seven geographic locations across tropical eastern and Western Australia. The ITS2 topology was congruent with the tree derived from Bayesian inference of discrete morphological characters supporting expected taxonomic relationships at the genus level and the identification of five ESUs. However, phylogenies inferred from the ITS2 marker revealed multiple sequence clusters, some of which were characterised by distinct morphological features and specific geographic ranges. Our results are discussed in light of taxonomic incongruences within this study, hidden sponge diversity and the role of vicariant events in influencing present day distribution patterns. Copyright © 2014 Elsevier Inc. All rights reserved.

Diverse sampling of East African haemosporidians reveals chiropteran origin of malaria parasites in primates and rodents.

PubMed

Lutz, Holly L; Patterson, Bruce D; Kerbis Peterhans, Julian C; Stanley, William T; Webala, Paul W; Gnoske, Thomas P; Hackett, Shannon J; Stanhope, Michael J

2016-06-01

Phylogenies of parasites provide hypotheses on the history of their movements between hosts, leading to important insights regarding the processes of host switching that underlie modern-day epidemics. Haemosporidian (malaria) parasites lack a well resolved phylogeny, which has impeded the study of evolutionary processes associated with host-switching in this group. Here we present a novel phylogenetic hypothesis that suggests bats served as the ancestral hosts of malaria parasites in primates and rodents. Expanding upon current taxon sampling of Afrotropical bat and bird parasites, we find strong support for all major nodes in the haemosporidian tree using both Bayesian and maximum likelihood approaches. Our analyses support a single transition of haemosporidian parasites from saurian to chiropteran hosts, and do not support a monophyletic relationship between Plasmodium parasites of birds and mammals. We find, for the first time, that Hepatocystis and Plasmodium parasites of mammals represent reciprocally monophyletic evolutionary lineages. These results highlight the importance of broad taxonomic sampling when analyzing phylogenetic relationships, and have important implications for our understanding of key host switching events in the history of malaria parasite evolution. Copyright © 2016 Elsevier Inc. All rights reserved.

Rates of molecular evolution in tree ferns are associated with body size, environmental temperature, and biological productivity.

PubMed

Barrera-Redondo, Josué; Ramírez-Barahona, Santiago; Eguiarte, Luis E

2018-05-01

Variation in rates of molecular evolution (heterotachy) is a common phenomenon among plants. Although multiple theoretical models have been proposed, fundamental questions remain regarding the combined effects of ecological and morphological traits on rate heterogeneity. Here, we used tree ferns to explore the correlation between rates of molecular evolution in chloroplast DNA sequences and several morphological and environmental factors within a Bayesian framework. We revealed direct and indirect effects of body size, biological productivity, and temperature on substitution rates, where smaller tree ferns living in warmer and less productive environments tend to have faster rates of molecular evolution. In addition, we found that variation in the ratio of nonsynonymous to synonymous substitution rates (dN/dS) in the chloroplast rbcL gene was significantly correlated with ecological and morphological variables. Heterotachy in tree ferns may be influenced by effective population size associated with variation in body size and productivity. Macroevolutionary hypotheses should go beyond explaining heterotachy in terms of mutation rates and instead, should integrate population-level factors to better understand the processes affecting the tempo of evolution at the molecular level. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Recurrent patterns in fluid geochemistry data prior to phreatic eruptions

NASA Astrophysics Data System (ADS)

Rouwet, Dmitri; Sandri, Laura; Todesco, Micol; Tonini, Roberto; Pecoraino, Giovannella; Diliberto, Iole Serena

2016-04-01

Not all volcanic eruptions are magma-driven: the sudden evaporation and expansion of heated groundwater may cause phreatic eruptions, where the magma involvement is absent or negligible. Active crater lakes top some of the volcanoes prone to phreatic activity. This kind of eruption may occur suddenly, and without clear warning: on September 27, 2014 a phreatic eruption of Ontake, Japan, occurred without timely precursors, killing 57 tourists near the volcano summit. Phreatic eruptions can thus be as fatal as higher VEI events, due to the lack of recognised precursory signals, and because of their explosive and violent nature. In this study, we tackle the challenge of recognising precursors to phreatic eruptions, by analysing the records of two "phreatically" active volcanoes in Costa Rica, i.e. Poás and Turrialba, respectively with and without a crater lake. These volcanoes cover a wide range of time scales in eruptive behaviour, possibly culminating into magmatic activity, and have a long-term multi-parameter dataset mostly describing fluid geochemistry. Such dataset is suitable for being analysed by objective pattern recognition techniques, in search for recurrent schemes. The aim is to verify the existence and nature of potential precursory patterns, which will improve our understanding of phreatic events, and allow the assessment of the associated hazard at other volcanoes, such as Campi Flegrei or Vulcano, in Italy. Quantitative forecast of phreatic activity will be performed with BET_UNREST, a Bayesian Event Tree tool recently developed within the framework of FP7 EU VUELCO project. The study will combine the analysis of fluid geochemistry data with pattern recognition and phreatic eruption forecast on medium and short-term. The study will also provide interesting hints on the features that promote or hinder phreatic activity in volcanoes that host well-developed hydrothermal circulation.

Analysis of Genetic Diversity and Structure Pattern of Indigofera Pseudotinctoria in Karst Habitats of the Wushan Mountains Using AFLP Markers.

PubMed

Fan, Yan; Zhang, Chenglin; Wu, Wendan; He, Wei; Zhang, Li; Ma, Xiao

2017-10-16

Indigofera pseudotinctoria Mats is an agronomically and economically important perennial legume shrub with a high forage yield, protein content and strong adaptability, which is subject to natural habitat fragmentation and serious human disturbance. Until now, our knowledge of the genetic relationships and intraspecific genetic diversity for its wild collections is still poor, especially at small spatial scales. Here amplified fragment length polymorphism (AFLP) technology was employed for analysis of genetic diversity, differentiation, and structure of 364 genotypes of I. pseudotinctoria from 15 natural locations in Wushan Montain, a highly structured mountain with typical karst landforms in Southwest China. We also tested whether eco-climate factors has affected genetic structure by correlating genetic diversity with habitat features. A total of 515 distinctly scoreable bands were generated, and 324 of them were polymorphic. The polymorphic information content (PIC) ranged from 0.694 to 0.890 with an average of 0.789 per primer pair. On species level, Nei's gene diversity ( H j ), the Bayesian genetic diversity index ( H B ) and the Shannon information index ( I ) were 0.2465, 0.2363 and 0.3772, respectively. The high differentiation among all sampling sites was detected ( F ST = 0.2217, G ST = 0.1746, G' ST = 0.2060, θ B = 0.1844), and instead, gene flow among accessions ( N m = 1.1819) was restricted. The population genetic structure resolved by the UPGMA tree, principal coordinate analysis, and Bayesian-based cluster analyses irrefutably grouped all accessions into two distinct clusters, i.e., lowland and highland groups. The population genetic structure resolved by the UPGMA tree, principal coordinate analysis, and Bayesian-based cluster analyses irrefutably grouped all accessions into two distinct clusters, i.e., lowland and highland groups. This structure pattern may indicate joint effects by the neutral evolution and natural selection. Restricted N m was observed across all accessions, and genetic barriers were detected between adjacent accessions due to specifically geographical landform.

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure.

PubMed

Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

2017-03-01

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

A small-area ecologic study of myocardial infarction, neighborhood deprivation, and sex: a Bayesian modeling approach.

PubMed

Deguen, Séverine; Lalloue, Benoît; Bard, Denis; Havard, Sabrina; Arveiler, Dominique; Zmirou-Navier, Denis

2010-07-01

Socioeconomic inequalities in the risk of coronary heart disease (CHD) are well documented for men and women. CHD incidence is greater for men but its association with socioeconomic status is usually found to be stronger among women. We explored the sex-specific association between neighborhood deprivation level and the risk of myocardial infarction (MI) at a small-area scale. We studied 1193 myocardial infarction events in people aged 35-74 years in the Strasbourg metropolitan area, France (2000-2003). We used a deprivation index to assess the neighborhood deprivation level. To take into account spatial dependence and the variability of MI rates due to the small number of events, we used a hierarchical Bayesian modeling approach. We fitted hierarchical Bayesian models to estimate sex-specific relative and absolute MI risks across deprivation categories. We tested departure from additive joint effects of deprivation and sex. The risk of MI increased with the deprivation level for both sexes, but was higher for men for all deprivation classes. Relative rates increased along the deprivation scale more steadily for women and followed a different pattern: linear for men and nonlinear for women. Our data provide evidence of effect modification, with departure from an additive joint effect of deprivation and sex. We document sex differences in the socioeconomic gradient of MI risk in Strasbourg. Women appear more susceptible at levels of extreme deprivation; this result is not a chance finding, given the large difference in event rates between men and women.

Detection of photosynthetic responses of cool-temperate forests following extreme climate events using Bayesian inversion

NASA Astrophysics Data System (ADS)

Toda, M.; Knohl, A.; Herbst, M.; Keenan, T. F.; Yokozawa, M.

2016-12-01

The increase in extreme climate events associated with ongoing global warming may create severe damage to terrestrial ecosystems, changing plant structure and the eco-physiological functions that regulate ecosystem carbon exchange. However, most damage is usually due to moderate, rather than catastrophic, disturbances. The nature of plant functional responses to such disturbances, and the resulting effects on the terrestrial carbon cycle, remain poorly understood. To unravel the scientific question, tower-based eddy covariance data in the cool-temperate forests were used to constrain plant eco-physiological parameters in a persimoneous ecosystem model that may have affected carbon dynamics following extreme climate events using the statistic Bayesian inversion approach. In the present study, we raised two types of extreme events relevant for cool-temperate regions, i.e. a typhoon with mechanistic foliage destraction and a heat wave with severe drought. With appropriate evaluation of parameter and predictive uncertainties, the inversion analysis shows annual trajectory of activated photosynthetic responses following climate extremes compared the pre-disturbance state in each forest. We address that forests with moderate disturbance show substantial and rapid photosynthetic recovery, enhanced productivity, and, thus, ecosystem carbon exchange, although the effect of extreme climatic events varies depending on the stand successional phase and the type, intensity, timing and legacy of the disturbance.

THREAT ANTICIPATION AND DECEPTIVE REASONING USING BAYESIAN BELIEF NETWORKS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allgood, Glenn O; Olama, Mohammed M; Lake, Joe E

Recent events highlight the need for tools to anticipate threats posed by terrorists. Assessing these threats requires combining information from disparate data sources such as analytic models, simulations, historical data, sensor networks, and user judgments. These disparate data can be combined in a coherent, analytically defensible, and understandable manner using a Bayesian belief network (BBN). In this paper, we develop a BBN threat anticipatory model based on a deceptive reasoning algorithm using a network engineering process that treats the probability distributions of the BBN nodes within the broader context of the system development process.

Selective Tree-ring Models: A Novel Method for Reconstructing Streamflow Using Tree Rings

NASA Astrophysics Data System (ADS)

Foard, M. B.; Nelson, A. S.; Harley, G. L.

2017-12-01

Surface water is among the most instrumental and vulnerable resources in the Northwest United States (NW). Recent observations show that overall water quantity is declining in streams across the region, while extreme flooding events occur more frequently. Historical streamflow models inform probabilities of extreme flow events (flood or drought) by describing frequency and duration of past events. There are numerous examples of tree-rings being utilized to reconstruct streamflow in the NW. These models confirm that tree-rings are highly accurate at predicting streamflow, however there are many nuances that limit their applicability through time and space. For example, most models predict streamflow from hydrologically altered rivers (e.g. dammed, channelized) which may hinder our ability to predict natural prehistoric flow. They also have a tendency to over/under-predict extreme flow events. Moreover, they often neglect to capture the changing relationships between tree-growth and streamflow over time and space. To address these limitations, we utilized national tree-ring and streamflow archives to investigate the relationships between the growth of multiple coniferous species and free-flowing streams across the NW using novel species-and site-specific streamflow models - a term we coined"selective tree-ring models." Correlation function analysis and regression modeling were used to evaluate the strengths and directions of the flow-growth relationships. Species with significant relationships in the same direction were identified as strong candidates for selective models. Temporal and spatial patterns of these relationships were examined using running correlations and inverse distance weighting interpolation, respectively. Our early results indicate that (1) species adapted to extreme climates (e.g. hot-dry, cold-wet) exhibit the most consistent relationships across space, (2) these relationships weaken in locations with mild climatic variability, and (3) some species appear to be strong candidates for predicting high flow events, while others may be better at pridicting drought. These findings indicate that selective models may outperform traditional models when reconstructing distinctive aspects of streamflow.

Impacts of age-dependent tree sensitivity and dating approaches on dendrogeomorphic time series of landslides

NASA Astrophysics Data System (ADS)

Šilhán, Karel; Stoffel, Markus

2015-05-01

Different approaches and thresholds have been utilized in the past to date landslides with growth ring series of disturbed trees. Past work was mostly based on conifer species because of their well-defined ring boundaries and the easy identification of compression wood after stem tilting. More recently, work has been expanded to include broad-leaved trees, which are thought to produce less and less evident reactions after landsliding. This contribution reviews recent progress made in dendrogeomorphic landslide analysis and introduces a new approach in which landslides are dated via ring eccentricity formed after tilting. We compare results of this new and the more conventional approaches. In addition, the paper also addresses tree sensitivity to landslide disturbance as a function of tree age and trunk diameter using 119 common beech (Fagus sylvatica L.) and 39 Crimean pine (Pinus nigra ssp. pallasiana) trees growing on two landslide bodies. The landslide events reconstructed with the classical approach (reaction wood) also appear as events in the eccentricity analysis, but the inclusion of eccentricity clearly allowed for more (162%) landslides to be detected in the tree-ring series. With respect to tree sensitivity, conifers and broad-leaved trees show the strongest reactions to landslides at ages comprised between 40 and 60 years, with a second phase of increased sensitivity in P. nigra at ages of ca. 120-130 years. These phases of highest sensitivities correspond with trunk diameters at breast height of 6-8 and 18-22 cm, respectively (P. nigra). This study thus calls for the inclusion of eccentricity analyses in future landslide reconstructions as well as for the selection of trees belonging to different age and diameter classes to allow for a well-balanced and more complete reconstruction of past events.

Triggered surface slips in the Coachella Valley area associated with the 1992 Joshua Tree and Landers, California, Earthquakes

USGS Publications Warehouse

Rymer, M.J.

2000-01-01

The Coachella Valley area was strongly shaken by the 1992 Joshua Tree (23 April) and Landers (28 June) earthquakes, and both events caused triggered slip on active faults within the area. Triggered slip associated with the Joshua Tree earthquake was on a newly recognized fault, the East Wide Canyon fault, near the southwestern edge of the Little San Bernardino Mountains. Slip associated with the Landers earthquake formed along the San Andreas fault in the southeastern Coachella Valley. Surface fractures formed along the East Wide Canyon fault in association with the Joshua Tree earthquake. The fractures extended discontinuously over a 1.5-km stretch of the fault, near its southern end. Sense of slip was consistently right-oblique, west side down, similar to the long-term style of faulting. Measured offset values were small, with right-lateral and vertical components of slip ranging from 1 to 6 mm and 1 to 4 mm, respectively. This is the first documented historic slip on the East Wide Canyon fault, which was first mapped only months before the Joshua Tree earthquake. Surface slip associated with the Joshua Tree earthquake most likely developed as triggered slip given its 5 km distance from the Joshua Tree epicenter and aftershocks. As revealed in a trench investigation, slip formed in an area with only a thin (<3 m thick) veneer of alluvium in contrast to earlier documented triggered slip events in this region, all in the deep basins of the Salton Trough. A paleoseismic trench study in an area of 1992 surface slip revealed evidence of two and possibly three surface faulting events on the East Wide Canyon fault during the late Quaternary, probably latest Pleistocene (first event) and mid- to late Holocene (second two events). About two months after the Joshua Tree earthquake, the Landers earthquake then triggered slip on many faults, including the San Andreas fault in the southeastern Coachella Valley. Surface fractures associated with this event formed discontinuous breaks over a 54-km-long stretch of the fault, from the Indio Hills southeastward to Durmid Hill. Sense of slip was right-lateral; only locally was there a minor (~1 mm) vertical component of slip. Measured dextral displacement values ranged from 1 to 20 mm, with the largest amounts found in the Mecca Hills where large slip values have been measured following past triggered-slip events.

The Inference of Gene Trees with Species Trees

PubMed Central

Szöllősi, Gergely J.; Tannier, Eric; Daubin, Vincent; Boussau, Bastien

2015-01-01

This article reviews the various models that have been used to describe the relationships between gene trees and species trees. Molecular phylogeny has focused mainly on improving models for the reconstruction of gene trees based on sequence alignments. Yet, most phylogeneticists seek to reveal the history of species. Although the histories of genes and species are tightly linked, they are seldom identical, because genes duplicate, are lost or horizontally transferred, and because alleles can coexist in populations for periods that may span several speciation events. Building models describing the relationship between gene and species trees can thus improve the reconstruction of gene trees when a species tree is known, and vice versa. Several approaches have been proposed to solve the problem in one direction or the other, but in general neither gene trees nor species trees are known. Only a few studies have attempted to jointly infer gene trees and species trees. These models account for gene duplication and loss, transfer or incomplete lineage sorting. Some of them consider several types of events together, but none exists currently that considers the full repertoire of processes that generate gene trees along the species tree. Simulations as well as empirical studies on genomic data show that combining gene tree–species tree models with models of sequence evolution improves gene tree reconstruction. In turn, these better gene trees provide a more reliable basis for studying genome evolution or reconstructing ancestral chromosomes and ancestral gene sequences. We predict that gene tree–species tree methods that can deal with genomic data sets will be instrumental to advancing our understanding of genomic evolution. PMID:25070970

Reconciliation of Gene and Species Trees

PubMed Central

Rusin, L. Y.; Lyubetskaya, E. V.; Gorbunov, K. Y.; Lyubetsky, V. A.

2014-01-01

The first part of the paper briefly overviews the problem of gene and species trees reconciliation with the focus on defining and algorithmic construction of the evolutionary scenario. Basic ideas are discussed for the aspects of mapping definitions, costs of the mapping and evolutionary scenario, imposing time scales on a scenario, incorporating horizontal gene transfers, binarization and reconciliation of polytomous trees, and construction of species trees and scenarios. The review does not intend to cover the vast diversity of literature published on these subjects. Instead, the authors strived to overview the problem of the evolutionary scenario as a central concept in many areas of evolutionary research. The second part provides detailed mathematical proofs for the solutions of two problems: (i) inferring a gene evolution along a species tree accounting for various types of evolutionary events and (ii) trees reconciliation into a single species tree when only gene duplications and losses are allowed. All proposed algorithms have a cubic time complexity and are mathematically proved to find exact solutions. Solving algorithms for problem (ii) can be naturally extended to incorporate horizontal transfers, other evolutionary events, and time scales on the species tree. PMID:24800245

Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.

2015-12-01

Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be followed in the future.

Extreme drought event and shrub invasion combine to reduce ecosystem functioning and resilience in water-limited climates

NASA Astrophysics Data System (ADS)

Caldeira, Maria; Lecomte, Xavier; David, Teresa; Pinto, Joaquim; Bugalho, Miguel; Werner, Christiane

2016-04-01

Extreme droughts and plant invasions are major drivers of global change that can critically affect ecosystem functioning. Shrub encroachment is increasing in many regions worldwide and extreme events are projected to increase in frequency and intensity, namely in the Mediterranean region. Nevertheless, little is known about how these drivers may interact and affect ecosystem functioning and resilience to extreme droughts. Using a manipulative shrub removal experiment and the co-occurrence of an extreme drought event (2011/2012) in a Mediterranean woodland, we show that the native shrub invasion and extreme drought combined to reduce ecosystem transpiration and the resilience of the key-stone oak tree species. We established six 25 x 25 m paired plots in a shrub (Cistus ladanifer L.) encroached Mediterranean cork-oak (Quercus suber L.) woodland. We measured sapflow and pre-dawn leaf water potential of trees and shrubs and soil water content in all plots during three years. We determined the resilience of tree transpiration to evaluate to what extent trees recovered from the extreme drought event. From February to November 2011 we conducted baseline measurements for plot comparison. In November 2011 all the shrubs from one of all the paired plots were cut and removed. Ecosystem transpiration was dominated by the water use of the invasive shrub, which further increased after the extreme drought. Simultaneously, tree transpiration in invaded plots declined much stronger (67 ± 13 %) than in plots cleared from shrubs (31 ± 11%) relative to the pre-drought year. Trees in invaded plots were not able to recover in the following wetter year showing lower resilience to the extreme drought event. Our results imply that in Mediterranean-type of climates invasion by water spending species can combine with projected recurrent extreme droughts causing critical drought tolerance thresholds of trees to be overcome increasing the probability of tree mortality (Caldeira et.al. 2015). Caldeira M.C., Lecomte X., David T.S., Pinto J.G., Bugalho M.N. & Werner C. (2015). Synergy of extreme drought and shrub invasion reduce ecosystem functioning and resilience in water-limited climates. Scientific Reports, 5, 15110.

The impossibility of probabilities

NASA Astrophysics Data System (ADS)

Zimmerman, Peter D.

2017-11-01

This paper discusses the problem of assigning probabilities to the likelihood of nuclear terrorism events, in particular examining the limitations of using Bayesian priors for this purpose. It suggests an alternate approach to analyzing the threat of nuclear terrorism.

GIGA: a simple, efficient algorithm for gene tree inference in the genomic age

PubMed Central

2010-01-01

Background Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. Results We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. Conclusions GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events. PMID:20534164

GIGA: a simple, efficient algorithm for gene tree inference in the genomic age.

PubMed

Thomas, Paul D

2010-06-09

Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events.

Object-oriented fault tree evaluation program for quantitative analyses

NASA Technical Reports Server (NTRS)

Patterson-Hine, F. A.; Koen, B. V.

1988-01-01

Object-oriented programming can be combined with fault free techniques to give a significantly improved environment for evaluating the safety and reliability of large complex systems for space missions. Deep knowledge about system components and interactions, available from reliability studies and other sources, can be described using objects that make up a knowledge base. This knowledge base can be interrogated throughout the design process, during system testing, and during operation, and can be easily modified to reflect design changes in order to maintain a consistent information source. An object-oriented environment for reliability assessment has been developed on a Texas Instrument (TI) Explorer LISP workstation. The program, which directly evaluates system fault trees, utilizes the object-oriented extension to LISP called Flavors that is available on the Explorer. The object representation of a fault tree facilitates the storage and retrieval of information associated with each event in the tree, including tree structural information and intermediate results obtained during the tree reduction process. Reliability data associated with each basic event are stored in the fault tree objects. The object-oriented environment on the Explorer also includes a graphical tree editor which was modified to display and edit the fault trees.

Sorting through the chaff, nDNA gene trees for phylogenetic inference and hybrid identification of annual sunflowers (Helianthus sect. Helianthus).

PubMed

Moody, Michael L; Rieseberg, Loren H

2012-07-01

The annual sunflowers (Helianthus sect. Helianthus) present a formidable challenge for phylogenetic inference because of ancient hybrid speciation, recent introgression, and suspected issues with deep coalescence. Here we analyze sequence data from 11 nuclear DNA (nDNA) genes for multiple genotypes of species within the section to (1) reconstruct the phylogeny of this group, (2) explore the utility of nDNA gene trees for detecting hybrid speciation and introgression; and (3) test an empirical method of hybrid identification based on the phylogenetic congruence of nDNA gene trees from tightly linked genes. We uncovered considerable topological heterogeneity among gene trees with or without three previously identified hybrid species included in the analyses, as well as a general lack of reciprocal monophyly of species. Nonetheless, partitioned Bayesian analyses provided strong support for the reciprocal monophyly of all species except H. annuus (0.89 PP), the most widespread and abundant annual sunflower. Previous hypotheses of relationships among taxa were generally strongly supported (1.0 PP), except among taxa typically associated with H. annuus, apparently due to the paraphyly of the latter in all gene trees. While the individual nDNA gene trees provided a useful means for detecting recent hybridization, identification of ancient hybridization was problematic for all ancient hybrid species, even when linkage was considered. We discuss biological factors that affect the efficacy of phylogenetic methods for hybrid identification.

Soft-tissue anatomy of the primates: phylogenetic analyses based on the muscles of the head, neck, pectoral region and upper limb, with notes on the evolution of these muscles

PubMed Central

Diogo, R; Wood, B

2011-01-01

Apart from molecular data, nearly all the evidence used to study primate relationships comes from hard tissues. Here, we provide details of the first parsimony and Bayesian cladistic analyses of the order Primates based exclusively on muscle data. The most parsimonious tree obtained from the cladistic analysis of 166 characters taken from the head, neck, pectoral and upper limb musculature is fully congruent with the most recent evolutionary molecular tree of Primates. That is, this tree recovers not only the relationships among the major groups of primates, i.e. Strepsirrhini {Tarsiiformes [Platyrrhini (Cercopithecidae, Hominoidea)]}, but it also recovers the relationships within each of these inclusive groups. Of the 301 character state changes occurring in this tree, ca. 30% are non-homoplasic evolutionary transitions; within the 220 changes that are unambiguously optimized in the tree, ca. 15% are reversions. The trees obtained by using characters derived from the muscles of the head and neck are more similar to the most recent evolutionary molecular tree than are the trees obtained by using characters derived from the pectoral and upper limb muscles. It was recently argued that since the Pan/Homo split, chimpanzees accumulated more phenotypic adaptations than humans, but our results indicate that modern humans accumulated more muscle character state changes than chimpanzees, and that both these taxa accumulated more changes than gorillas. This overview of the evolution of the primate head, neck, pectoral and upper limb musculature suggests that the only muscle groups for which modern humans have more muscles than most other extant primates are the muscles of the face, larynx and forearm. PMID:21689100

Coalescent-Based Analyses of Genomic Sequence Data Provide a Robust Resolution of Phylogenetic Relationships among Major Groups of Gibbons

PubMed Central

Shi, Cheng-Min; Yang, Ziheng

2018-01-01

Abstract The phylogenetic relationships among extant gibbon species remain unresolved despite numerous efforts using morphological, behavorial, and genetic data and the sequencing of whole genomes. A major challenge in reconstructing the gibbon phylogeny is the radiative speciation process, which resulted in extremely short internal branches in the species phylogeny and extensive incomplete lineage sorting with extensive gene-tree heterogeneity across the genome. Here, we analyze two genomic-scale data sets, with ∼10,000 putative noncoding and exonic loci, respectively, to estimate the species tree for the major groups of gibbons. We used the Bayesian full-likelihood method bpp under the multispecies coalescent model, which naturally accommodates incomplete lineage sorting and uncertainties in the gene trees. For comparison, we included three heuristic coalescent-based methods (mp-est, SVDQuartets, and astral) as well as concatenation. From both data sets, we infer the phylogeny for the four extant gibbon genera to be (Hylobates, (Nomascus, (Hoolock, Symphalangus))). We used simulation guided by the real data to evaluate the accuracy of the methods used. Astral, while not as efficient as bpp, performed well in estimation of the species tree even in presence of excessive incomplete lineage sorting. Concatenation, mp-est and SVDQuartets were unreliable when the species tree contains very short internal branches. Likelihood ratio test of gene flow suggests a small amount of migration from Hylobates moloch to H. pileatus, while cross-genera migration is absent or rare. Our results highlight the utility of coalescent-based methods in addressing challenging species tree problems characterized by short internal branches and rampant gene tree-species tree discordance. PMID:29087487

Soft-tissue anatomy of the primates: phylogenetic analyses based on the muscles of the head, neck, pectoral region and upper limb, with notes on the evolution of these muscles.

PubMed

Diogo, R; Wood, B

2011-09-01

Apart from molecular data, nearly all the evidence used to study primate relationships comes from hard tissues. Here, we provide details of the first parsimony and Bayesian cladistic analyses of the order Primates based exclusively on muscle data. The most parsimonious tree obtained from the cladistic analysis of 166 characters taken from the head, neck, pectoral and upper limb musculature is fully congruent with the most recent evolutionary molecular tree of Primates. That is, this tree recovers not only the relationships among the major groups of primates, i.e. Strepsirrhini {Tarsiiformes [Platyrrhini (Cercopithecidae, Hominoidea)]}, but it also recovers the relationships within each of these inclusive groups. Of the 301 character state changes occurring in this tree, ca. 30% are non-homoplasic evolutionary transitions; within the 220 changes that are unambiguously optimized in the tree, ca. 15% are reversions. The trees obtained by using characters derived from the muscles of the head and neck are more similar to the most recent evolutionary molecular tree than are the trees obtained by using characters derived from the pectoral and upper limb muscles. It was recently argued that since the Pan/Homo split, chimpanzees accumulated more phenotypic adaptations than humans, but our results indicate that modern humans accumulated more muscle character state changes than chimpanzees, and that both these taxa accumulated more changes than gorillas. This overview of the evolution of the primate head, neck, pectoral and upper limb musculature suggests that the only muscle groups for which modern humans have more muscles than most other extant primates are the muscles of the face, larynx and forearm. © 2011 The Authors. Journal of Anatomy © 2011 Anatomical Society of Great Britain and Ireland.

Bayesian survival analysis in clinical trials: What methods are used in practice?

PubMed

Brard, Caroline; Le Teuff, Gwénaël; Le Deley, Marie-Cécile; Hampson, Lisa V

2017-02-01

Background Bayesian statistics are an appealing alternative to the traditional frequentist approach to designing, analysing, and reporting of clinical trials, especially in rare diseases. Time-to-event endpoints are widely used in many medical fields. There are additional complexities to designing Bayesian survival trials which arise from the need to specify a model for the survival distribution. The objective of this article was to critically review the use and reporting of Bayesian methods in survival trials. Methods A systematic review of clinical trials using Bayesian survival analyses was performed through PubMed and Web of Science databases. This was complemented by a full text search of the online repositories of pre-selected journals. Cost-effectiveness, dose-finding studies, meta-analyses, and methodological papers using clinical trials were excluded. Results In total, 28 articles met the inclusion criteria, 25 were original reports of clinical trials and 3 were re-analyses of a clinical trial. Most trials were in oncology (n = 25), were randomised controlled (n = 21) phase III trials (n = 13), and half considered a rare disease (n = 13). Bayesian approaches were used for monitoring in 14 trials and for the final analysis only in 14 trials. In the latter case, Bayesian survival analyses were used for the primary analysis in four cases, for the secondary analysis in seven cases, and for the trial re-analysis in three cases. Overall, 12 articles reported fitting Bayesian regression models (semi-parametric, n = 3; parametric, n = 9). Prior distributions were often incompletely reported: 20 articles did not define the prior distribution used for the parameter of interest. Over half of the trials used only non-informative priors for monitoring and the final analysis (n = 12) when it was specified. Indeed, no articles fitting Bayesian regression models placed informative priors on the parameter of interest. The prior for the treatment effect was based on historical data in only four trials. Decision rules were pre-defined in eight cases when trials used Bayesian monitoring, and in only one case when trials adopted a Bayesian approach to the final analysis. Conclusion Few trials implemented a Bayesian survival analysis and few incorporated external data into priors. There is scope to improve the quality of reporting of Bayesian methods in survival trials. Extension of the Consolidated Standards of Reporting Trials statement for reporting Bayesian clinical trials is recommended.

Searching Dynamic Agents with a Team of Mobile Robots

PubMed Central

Juliá, Miguel; Gil, Arturo; Reinoso, Oscar

2012-01-01

This paper presents a new algorithm that allows a team of robots to cooperatively search for a set of moving targets. An estimation of the areas of the environment that are more likely to hold a target agent is obtained using a grid-based Bayesian filter. The robot sensor readings and the maximum speed of the moving targets are used in order to update the grid. This representation is used in a search algorithm that commands the robots to those areas that are more likely to present target agents. This algorithm splits the environment in a tree of connected regions using dynamic programming. This tree is used in order to decide the destination for each robot in a coordinated manner. The algorithm has been successfully tested in known and unknown environments showing the validity of the approach. PMID:23012519

Searching dynamic agents with a team of mobile robots.

PubMed

Juliá, Miguel; Gil, Arturo; Reinoso, Oscar

2012-01-01

This paper presents a new algorithm that allows a team of robots to cooperatively search for a set of moving targets. An estimation of the areas of the environment that are more likely to hold a target agent is obtained using a grid-based Bayesian filter. The robot sensor readings and the maximum speed of the moving targets are used in order to update the grid. This representation is used in a search algorithm that commands the robots to those areas that are more likely to present target agents. This algorithm splits the environment in a tree of connected regions using dynamic programming. This tree is used in order to decide the destination for each robot in a coordinated manner. The algorithm has been successfully tested in known and unknown environments showing the validity of the approach.

Bayesian Weibull tree models for survival analysis of clinico-genomic data

PubMed Central

Clarke, Jennifer; West, Mike

2008-01-01

An important goal of research involving gene expression data for outcome prediction is to establish the ability of genomic data to define clinically relevant risk factors. Recent studies have demonstrated that microarray data can successfully cluster patients into low- and high-risk categories. However, the need exists for models which examine how genomic predictors interact with existing clinical factors and provide personalized outcome predictions. We have developed clinico-genomic tree models for survival outcomes which use recursive partitioning to subdivide the current data set into homogeneous subgroups of patients, each with a specific Weibull survival distribution. These trees can provide personalized predictive distributions of the probability of survival for individuals of interest. Our strategy is to fit multiple models; within each model we adopt a prior on the Weibull scale parameter and update this prior via Empirical Bayes whenever the sample is split at a given node. The decision to split is based on a Bayes factor criterion. The resulting trees are weighted according to their relative likelihood values and predictions are made by averaging over models. In a pilot study of survival in advanced stage ovarian cancer we demonstrate that clinical and genomic data are complementary sources of information relevant to survival, and we use the exploratory nature of the trees to identify potential genomic biomarkers worthy of further study. PMID:18618012

Using a Java Dynamic Tree to manage the terminology in a suite of medical applications.

PubMed

Yang, K; Evens, M W; Trace, D A

2008-01-01

Now that the National Library of Medicine has made SNOMED-CT widely available, we are trying to manage the terminology of a whole suite of medical applications and map our terminology into that in SNOMED. This paper describes the design and implementation of the Java Dynamic Tree that provides structure to our medical terminology and explains how it functions as the core of our system. The tree was designed to reflect the stages in a patient interview, so it contains components for identifying the patient and the provider, a large set of chief complaints, review of systems, physical examination, several history modules, medications, laboratory tests, imaging, and special procedures. The tree is mirrored in a commercial DBMS, which also stores multi-encounter patient data, disorder patterns for our Bayesian diagnostic system, and the data and rules for other expert systems. The DBMS facilitates the import and export of large terminology files. Our Java Dynamic Tree allows the health care provider to view the entire terminology along with the structure that supports it, as well as the mechanism for the generation of progress notes and other documents, in terms of a single hierarchical structure. Changes in terminology can be propagated through the system under the control of the expert. The import/ export facility has been a major help by replacing our original terminology by the terminology in SNOMED-CT.

Remote Detection and Modeling of Abrupt and Gradual Tree Mortality in the Southwestern USA

NASA Astrophysics Data System (ADS)

Muss, J. D.; Xu, C.; McDowell, N. G.

2014-12-01

Current climate models predict a warming and drying trend that has a high probability of increasing the frequency and spatial extent of tree mortality events. Field surveys can be used to identify, date, and attribute a cause of mortality to specific trees, but monetary and time constraints prevent broad-scale surveys, which are necessary to establish regional or global trends in tree mortality. This is significant because widespread forest mortality will likely lead to radical changes in evapotranspiration and surface albedo, which could compound climate change. While understanding the causes and mechanisms of tree mortality events is crucial, it is equally important to be able to detect and monitor mortality and subsequent changes to the ecosystem at broad spatial- and temporal-scales. Over the past five years our ability to remotely detect abrupt forest mortality events has improved greatly, but gradual events—such as those caused by drought or certain types of insects—are still difficult to identify. Moreover, it is virtually impossible to quantify the amount of mortality that has occurred within a mixed pixel. We have developed a system that fuses climate and satellite-derived spectral data to identify both the date and the agent of forest mortality events. This system has been used with Landsat time series data to detect both abrupt and general trends in tree loss that have occurred during the past quarter-century in northern New Mexico. It has also been used with MODIS data to identify pixels with a high likelihood of drought-caused tree mortality in the Southwestern US. These candidate pixels were then fed to ED-FRT, a coupled forest dynamics-radiative transfer model, to generate estimates of drought-induced. We demonstrate a multi-scale approach that can produce results that will be instrumental in advancing our understanding of tree mortality-climate feedbacks, and improve our ability to predict what forests could look like in the future.

Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network

PubMed Central

Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu

2018-01-01

This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit. PMID:29765629

Survey of critical failure events in on-chip interconnect by fault tree analysis

NASA Astrophysics Data System (ADS)

Yokogawa, Shinji; Kunii, Kyousuke

2018-07-01

In this paper, a framework based on reliability physics is proposed for adopting fault tree analysis (FTA) to the on-chip interconnect system of a semiconductor. By integrating expert knowledge and experience regarding the possibilities of failure on basic events, critical issues of on-chip interconnect reliability will be evaluated by FTA. In particular, FTA is used to identify the minimal cut sets with high risk priority. Critical events affecting the on-chip interconnect reliability are identified and discussed from the viewpoint of long-term reliability assessment. The moisture impact is evaluated as an external event.

Vegetation optical depth measured by microwave radiometry as an indicator of tree mortality risk

NASA Astrophysics Data System (ADS)

Rao, K.; Anderegg, W.; Sala, A.; Martínez-Vilalta, J.; Konings, A. G.

2017-12-01

Increased drought-related tree mortality has been observed across several regions in recent years. Vast spatial extent and high temporal variability makes field monitoring of tree mortality cumbersome and expensive. With global coverage and high temporal revisit, satellite remote sensing offers an unprecedented tool to monitor terrestrial ecosystems and identify areas at risk of large drought-driven tree mortality events. To date, studies that use remote sensing data to monitor tree mortality have focused on external climatic thresholds such as temperature and evapotranspiration. However, this approach fails to consider internal water stress in vegetation - which can vary across trees even for similar climatic conditions due to differences in hydraulic behavior, soil type, etc - and may therefore be a poor basis for measuring mortality events. There is a consensus that xylem hydraulic failure often precedes drought-induced mortality, suggesting depleted canopy water content shortly before onset of mortality. Observations of vegetation optical depth (VOD) derived from passive microwave are proportional to canopy water content. In this study, we propose to use variations in VOD as an indicator of potential tree mortality. Since VOD accounts for intrinsic water stress undergone by vegetation, it is expected to be more accurate than external climatic stress indicators. Analysis of tree mortality events in California, USA observed by airborne detection shows a consistent relationship between mortality and the proposed VOD metric. Although this approach is limited by the kilometer-scale resolution of passive microwave radiometry, our results nevertheless demonstrate that microwave-derived estimates of vegetation water content can be used to study drought-driven tree mortality, and may be a valuable tool for mortality predictions if they can be combined with higher-resolution variables.

BOP2: Bayesian optimal design for phase II clinical trials with simple and complex endpoints.

PubMed

Zhou, Heng; Lee, J Jack; Yuan, Ying

2017-09-20

We propose a flexible Bayesian optimal phase II (BOP2) design that is capable of handling simple (e.g., binary) and complicated (e.g., ordinal, nested, and co-primary) endpoints under a unified framework. We use a Dirichlet-multinomial model to accommodate different types of endpoints. At each interim, the go/no-go decision is made by evaluating a set of posterior probabilities of the events of interest, which is optimized to maximize power or minimize the number of patients under the null hypothesis. Unlike other existing Bayesian designs, the BOP2 design explicitly controls the type I error rate, thereby bridging the gap between Bayesian designs and frequentist designs. In addition, the stopping boundary of the BOP2 design can be enumerated prior to the onset of the trial. These features make the BOP2 design accessible to a wide range of users and regulatory agencies and particularly easy to implement in practice. Simulation studies show that the BOP2 design has favorable operating characteristics with higher power and lower risk of incorrectly terminating the trial than some existing Bayesian phase II designs. The software to implement the BOP2 design is freely available at www.trialdesign.org. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Fault-Tree Compiler

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Boerschlein, David P.

1993-01-01

Fault-Tree Compiler (FTC) program, is software tool used to calculate probability of top event in fault tree. Gates of five different types allowed in fault tree: AND, OR, EXCLUSIVE OR, INVERT, and M OF N. High-level input language easy to understand and use. In addition, program supports hierarchical fault-tree definition feature, which simplifies tree-description process and reduces execution time. Set of programs created forming basis for reliability-analysis workstation: SURE, ASSIST, PAWS/STEM, and FTC fault-tree tool (LAR-14586). Written in PASCAL, ANSI-compliant C language, and FORTRAN 77. Other versions available upon request.

Fault-Tree Compiler Program

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Martensen, Anna L.

1992-01-01

FTC, Fault-Tree Compiler program, is reliability-analysis software tool used to calculate probability of top event of fault tree. Five different types of gates allowed in fault tree: AND, OR, EXCLUSIVE OR, INVERT, and M OF N. High-level input language of FTC easy to understand and use. Program supports hierarchical fault-tree-definition feature simplifying process of description of tree and reduces execution time. Solution technique implemented in FORTRAN, and user interface in Pascal. Written to run on DEC VAX computer operating under VMS operating system.

An agglomerative hierarchical clustering approach to visualisation in Bayesian clustering problems

PubMed Central

Dawson, Kevin J.; Belkhir, Khalid

2009-01-01

Clustering problems (including the clustering of individuals into outcrossing populations, hybrid generations, full-sib families and selfing lines) have recently received much attention in population genetics. In these clustering problems, the parameter of interest is a partition of the set of sampled individuals, - the sample partition. In a fully Bayesian approach to clustering problems of this type, our knowledge about the sample partition is represented by a probability distribution on the space of possible sample partitions. Since the number of possible partitions grows very rapidly with the sample size, we can not visualise this probability distribution in its entirety, unless the sample is very small. As a solution to this visualisation problem, we recommend using an agglomerative hierarchical clustering algorithm, which we call the exact linkage algorithm. This algorithm is a special case of the maximin clustering algorithm that we introduced previously. The exact linkage algorithm is now implemented in our software package Partition View. The exact linkage algorithm takes the posterior co-assignment probabilities as input, and yields as output a rooted binary tree, - or more generally, a forest of such trees. Each node of this forest defines a set of individuals, and the node height is the posterior co-assignment probability of this set. This provides a useful visual representation of the uncertainty associated with the assignment of individuals to categories. It is also a useful starting point for a more detailed exploration of the posterior distribution in terms of the co-assignment probabilities. PMID:19337306

Challenges in Species Tree Estimation Under the Multispecies Coalescent Model

PubMed Central

Xu, Bo; Yang, Ziheng

2016-01-01

The multispecies coalescent (MSC) model has emerged as a powerful framework for inferring species phylogenies while accounting for ancestral polymorphism and gene tree-species tree conflict. A number of methods have been developed in the past few years to estimate the species tree under the MSC. The full likelihood methods (including maximum likelihood and Bayesian inference) average over the unknown gene trees and accommodate their uncertainties properly but involve intensive computation. The approximate or summary coalescent methods are computationally fast and are applicable to genomic datasets with thousands of loci, but do not make an efficient use of information in the multilocus data. Most of them take the two-step approach of reconstructing the gene trees for multiple loci by phylogenetic methods and then treating the estimated gene trees as observed data, without accounting for their uncertainties appropriately. In this article we review the statistical nature of the species tree estimation problem under the MSC, and explore the conceptual issues and challenges of species tree estimation by focusing mainly on simple cases of three or four closely related species. We use mathematical analysis and computer simulation to demonstrate that large differences in statistical performance may exist between the two classes of methods. We illustrate that several counterintuitive behaviors may occur with the summary methods but they are due to inefficient use of information in the data by summary methods and vanish when the data are analyzed using full-likelihood methods. These include (i) unidentifiability of parameters in the model, (ii) inconsistency in the so-called anomaly zone, (iii) singularity on the likelihood surface, and (iv) deterioration of performance upon addition of more data. We discuss the challenges and strategies of species tree inference for distantly related species when the molecular clock is violated, and highlight the need for improving the computational efficiency and model realism of the likelihood methods as well as the statistical efficiency of the summary methods. PMID:27927902

A Hierarchical Bayesian Model for Calibrating Estimates of Species Divergence Times

PubMed Central

Heath, Tracy A.

2012-01-01

In Bayesian divergence time estimation methods, incorporating calibrating information from the fossil record is commonly done by assigning prior densities to ancestral nodes in the tree. Calibration prior densities are typically parametric distributions offset by minimum age estimates provided by the fossil record. Specification of the parameters of calibration densities requires the user to quantify his or her prior knowledge of the age of the ancestral node relative to the age of its calibrating fossil. The values of these parameters can, potentially, result in biased estimates of node ages if they lead to overly informative prior distributions. Accordingly, determining parameter values that lead to adequate prior densities is not straightforward. In this study, I present a hierarchical Bayesian model for calibrating divergence time analyses with multiple fossil age constraints. This approach applies a Dirichlet process prior as a hyperprior on the parameters of calibration prior densities. Specifically, this model assumes that the rate parameters of exponential prior distributions on calibrated nodes are distributed according to a Dirichlet process, whereby the rate parameters are clustered into distinct parameter categories. Both simulated and biological data are analyzed to evaluate the performance of the Dirichlet process hyperprior. Compared with fixed exponential prior densities, the hierarchical Bayesian approach results in more accurate and precise estimates of internal node ages. When this hyperprior is applied using Markov chain Monte Carlo methods, the ages of calibrated nodes are sampled from mixtures of exponential distributions and uncertainty in the values of calibration density parameters is taken into account. PMID:22334343

Approximate likelihood calculation on a phylogeny for Bayesian estimation of divergence times.

PubMed

dos Reis, Mario; Yang, Ziheng

2011-07-01

The molecular clock provides a powerful way to estimate species divergence times. If information on some species divergence times is available from the fossil or geological record, it can be used to calibrate a phylogeny and estimate divergence times for all nodes in the tree. The Bayesian method provides a natural framework to incorporate different sources of information concerning divergence times, such as information in the fossil and molecular data. Current models of sequence evolution are intractable in a Bayesian setting, and Markov chain Monte Carlo (MCMC) is used to generate the posterior distribution of divergence times and evolutionary rates. This method is computationally expensive, as it involves the repeated calculation of the likelihood function. Here, we explore the use of Taylor expansion to approximate the likelihood during MCMC iteration. The approximation is much faster than conventional likelihood calculation. However, the approximation is expected to be poor when the proposed parameters are far from the likelihood peak. We explore the use of parameter transforms (square root, logarithm, and arcsine) to improve the approximation to the likelihood curve. We found that the new methods, particularly the arcsine-based transform, provided very good approximations under relaxed clock models and also under the global clock model when the global clock is not seriously violated. The approximation is poorer for analysis under the global clock when the global clock is seriously wrong and should thus not be used. The results suggest that the approximate method may be useful for Bayesian dating analysis using large data sets.

Risk Analysis of Return Support Material on Gas Compressor Platform Project

NASA Astrophysics Data System (ADS)

Silvianita; Aulia, B. U.; Khakim, M. L. N.; Rosyid, Daniel M.

2017-07-01

On a fixed platforms project are not only carried out by a contractor, but two or more contractors. Cooperation in the construction of fixed platforms is often not according to plan, it is caused by several factors. It takes a good synergy between the contractor to avoid miss communication may cause problems on the project. For the example is about support material (sea fastening, skid shoe and shipping support) used in the process of sending a jacket structure to operation place often does not return to the contractor. It needs a systematic method to overcome the problem of support material. This paper analyses the causes and effects of GAS Compressor Platform that support material is not return, using Fault Tree Analysis (FTA) and Event Tree Analysis (ETA). From fault tree analysis, the probability of top event is 0.7783. From event tree analysis diagram, the contractors lose Rp.350.000.000, - to Rp.10.000.000.000, -.

Mines Systems Safety Improvement Using an Integrated Event Tree and Fault Tree Analysis

NASA Astrophysics Data System (ADS)

Kumar, Ranjan; Ghosh, Achyuta Krishna

2017-04-01

Mines systems such as ventilation system, strata support system, flame proof safety equipment, are exposed to dynamic operational conditions such as stress, humidity, dust, temperature, etc., and safety improvement of such systems can be done preferably during planning and design stage. However, the existing safety analysis methods do not handle the accident initiation and progression of mine systems explicitly. To bridge this gap, this paper presents an integrated Event Tree (ET) and Fault Tree (FT) approach for safety analysis and improvement of mine systems design. This approach includes ET and FT modeling coupled with redundancy allocation technique. In this method, a concept of top hazard probability is introduced for identifying system failure probability and redundancy is allocated to the system either at component or system level. A case study on mine methane explosion safety with two initiating events is performed. The results demonstrate that the presented method can reveal the accident scenarios and improve the safety of complex mine systems simultaneously.

Improving the flash flood frequency analysis applying dendrogeomorphological evidences

NASA Astrophysics Data System (ADS)

Ruiz-Villanueva, V.; Ballesteros, J. A.; Bodoque, J. M.; Stoffel, M.; Bollschweiler, M.; Díez-Herrero, A.

2009-09-01

Flash floods are one of the natural hazards that cause major damages worldwide. Especially in Mediterranean areas they provoke high economic losses every year. In mountain areas with high stream gradients, floods events are characterized by extremely high flow and debris transport rates. Flash flood analysis in mountain areas presents specific scientific challenges. On one hand, there is a lack of information on precipitation and discharge due to a lack of spatially well distributed gauge stations with long records. On the other hand, gauge stations may not record correctly during extreme events when they are damaged or the discharge exceeds the recordable level. In this case, no systematic data allows improvement of the understanding of the spatial and temporal occurrence of the process. Since historic documentation is normally scarce or even completely missing in mountain areas, tree-ring analysis can provide an alternative approach. Flash floods may influence trees in different ways: (1) tilting of the stem through the unilateral pressure of the flowing mass or individual boulders; (2) root exposure through erosion of the banks; (3) injuries and scars caused by boulders and wood transported in the flow; (4) decapitation of the stem and resulting candelabra growth through the severe impact of boulders; (5) stem burial through deposition of material. The trees react to these disturbances with specific growth changes such as abrupt change of the yearly increment and anatomical changes like reaction wood or callus tissue. In this study, we sampled 90 cross sections and 265 increment cores of trees heavily affected by past flash floods in order to date past events and to reconstruct recurrence intervals in two torrent channels located in the Spanish Central System. The first study site is located along the Pelayo River, a torrent in natural conditions. Based on the external disturbances of trees and their geomorphological position, 114 Pinus pinaster (Ait.) influenced by flash flood events were sampled using an increment borer. For each tree sampled, additional information were recorded including the geographical position (GPS measure), the geomorphological situation based on a detailed geomorphological map, the social position within neighbouring trees, a description of the external disturbances and information on tree diameter, tree height and the position of the cores extracted. 265 cores were collected. In the laboratory, the 265 samples were analyzed using the standard methods: surface preparation, counting of tree rings as well as measuring of ring widths using a digital LINTAB positioning table and TSAP 4.6 software. Increment curves of the disturbed trees were then crossdated with a reference chronology in order to correct faulty tree-ring series derived from disturbed samples and to determine initiation of abrupt growth suppression or release. The age of the trees in this field site is between 50 and 100 years old. In the field most of the trees were tilted (93 %) and showed exposed roots (64 %). In the laboratory, growth suppressions were detected in 165 samples. Based on the number of trees showing disturbances, the intensity of the disturbance and the spatial distribution of the trees in the field, seven well represented events were dated for the last 50 years: 2005, 2000, 1996, 1976, 1973, 1966 and 1963. The second field site was a reach of 2 km length along the Arenal River, where the stream is channelized. Here stumps from previously felled trees could be analyzed directly in the field. 100 Alnus glutinosa (L.) Gaertn. and Fraxinus angustifolia (Vahl.) cross sections were investigated in order to date internal wounds. Different carpenter tools, sanding paper and magnifying glasses were used to count tree rings and to date the wounds in the field. In addition to the dating in the field, 22 cross sections were sampled and analyzed in the laboratory using the standard methods. The age of the trees ranges between 30 and 50 years. Based on the injuries dated in the field and in the laboratory, and based on the location of the trees, 8 main events were dated for the last 30 years: 2005, 2003, 2000, 1998, 1997, 1995, 1993 and 1978. Additional results are in progress, such as the amount of rainfall responsible for the triggering of the events, estimation of the magnitude, and the influence of the channelization in the case of the Arenal River. The strength of Dendrogeomorphology in flood analysis has been demonstrated, especially in areas where the lack of historical documents, rainfall and flow data limits the use of traditional methods.

Priority Queues for Computer Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor)

1998-01-01

The present invention is embodied in new priority queue data structures for event list management of computer simulations, and includes a new priority queue data structure and an improved event horizon applied to priority queue data structures. ne new priority queue data structure is a Qheap and is made out of linked lists for robust, fast, reliable, and stable event list management and uses a temporary unsorted list to store all items until one of the items is needed. Then the list is sorted, next, the highest priority item is removed, and then the rest of the list is inserted in the Qheap. Also, an event horizon is applied to binary tree and splay tree priority queue data structures to form the improved event horizon for event management.

Try Fault Tree Analysis, a Step-by-Step Way to Improve Organization Development.

ERIC Educational Resources Information Center

Spitzer, Dean

1980-01-01

Fault Tree Analysis, a systems safety engineering technology used to analyze organizational systems, is described. Explains the use of logic gates to represent the relationship between failure events, qualitative analysis, quantitative analysis, and effective use of Fault Tree Analysis. (CT)

Pedologic and geomorphic impacts of a tornado blowdown event in a mixed pine-hardwood forest

Treesearch

Jonathan D. Phillips; Daniel A. Marion; Alice V. Turkington

2008-01-01

Biomechanical effects of trees on soils and surface processes may be extensive in forest environments. Two blowdown sites caused by a November 2005 tornado in the Ouachita National Forest, Arkansas allowed a case study examination of bioturbation associated with a specific forest blowdown event, as well as detailed examination of relationships between tree root systems...

A fast bottom-up algorithm for computing the cut sets of noncoherent fault trees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corynen, G.C.

1987-11-01

An efficient procedure for finding the cut sets of large fault trees has been developed. Designed to address coherent or noncoherent systems, dependent events, shared or common-cause events, the method - called SHORTCUT - is based on a fast algorithm for transforming a noncoherent tree into a quasi-coherent tree (COHERE), and on a new algorithm for reducing cut sets (SUBSET). To assure sufficient clarity and precision, the procedure is discussed in the language of simple sets, which is also developed in this report. Although the new method has not yet been fully implemented on the computer, we report theoretical worst-casemore » estimates of its computational complexity. 12 refs., 10 figs.« less

Quantification of uncertainty in flood risk assessment for flood protection planning: a Bayesian approach

NASA Astrophysics Data System (ADS)

Dittes, Beatrice; Špačková, Olga; Ebrahimian, Negin; Kaiser, Maria; Rieger, Wolfgang; Disse, Markus; Straub, Daniel

2017-04-01

Flood risk estimates are subject to significant uncertainties, e.g. due to limited records of historic flood events, uncertainty in flood modeling, uncertain impact of climate change or uncertainty in the exposure and loss estimates. In traditional design of flood protection systems, these uncertainties are typically just accounted for implicitly, based on engineering judgment. In the AdaptRisk project, we develop a fully quantitative framework for planning of flood protection systems under current and future uncertainties using quantitative pre-posterior Bayesian decision analysis. In this contribution, we focus on the quantification of the uncertainties and study their relative influence on the flood risk estimate and on the planning of flood protection systems. The following uncertainty components are included using a Bayesian approach: 1) inherent and statistical (i.e. limited record length) uncertainty; 2) climate uncertainty that can be learned from an ensemble of GCM-RCM models; 3) estimates of climate uncertainty components not covered in 2), such as bias correction, incomplete ensemble, local specifics not captured by the GCM-RCM models; 4) uncertainty in the inundation modelling; 5) uncertainty in damage estimation. We also investigate how these uncertainties are possibly reduced in the future when new evidence - such as new climate models, observed extreme events, and socio-economic data - becomes available. Finally, we look into how this new evidence influences the risk assessment and effectivity of flood protection systems. We demonstrate our methodology for a pre-alpine catchment in southern Germany: the Mangfall catchment in Bavaria that includes the city of Rosenheim, which suffered significant losses during the 2013 flood event.

Bayesian analysis of time-series data under case-crossover designs: posterior equivalence and inference.

PubMed

Li, Shi; Mukherjee, Bhramar; Batterman, Stuart; Ghosh, Malay

2013-12-01

Case-crossover designs are widely used to study short-term exposure effects on the risk of acute adverse health events. While the frequentist literature on this topic is vast, there is no Bayesian work in this general area. The contribution of this paper is twofold. First, the paper establishes Bayesian equivalence results that require characterization of the set of priors under which the posterior distributions of the risk ratio parameters based on a case-crossover and time-series analysis are identical. Second, the paper studies inferential issues under case-crossover designs in a Bayesian framework. Traditionally, a conditional logistic regression is used for inference on risk-ratio parameters in case-crossover studies. We consider instead a more general full likelihood-based approach which makes less restrictive assumptions on the risk functions. Formulation of a full likelihood leads to growth in the number of parameters proportional to the sample size. We propose a semi-parametric Bayesian approach using a Dirichlet process prior to handle the random nuisance parameters that appear in a full likelihood formulation. We carry out a simulation study to compare the Bayesian methods based on full and conditional likelihood with the standard frequentist approaches for case-crossover and time-series analysis. The proposed methods are illustrated through the Detroit Asthma Morbidity, Air Quality and Traffic study, which examines the association between acute asthma risk and ambient air pollutant concentrations. © 2013, The International Biometric Society.

A machine-learning approach reveals that alignment properties alone can accurately predict inference of lateral gene transfer from discordant phylogenies.

PubMed

Roettger, Mayo; Martin, William; Dagan, Tal

2009-09-01

Among the methods currently used in phylogenomic practice to detect the presence of lateral gene transfer (LGT), one of the most frequently employed is the comparison of gene tree topologies for different genes. In cases where the phylogenies for different genes are incompatible, or discordant, for well-supported branches there are three simple interpretations for the result: 1) gene duplications (paralogy) followed by many independent gene losses have occurred, 2) LGT has occurred, or 3) the phylogeny is well supported but for reasons unknown is nonetheless incorrect. Here, we focus on the third possibility by examining the properties of 22,437 published multiple sequence alignments, the Bayesian maximum likelihood trees for which either do or do not suggest the occurrence of LGT by the criterion of discordant branches. The alignments that produce discordant phylogenies differ significantly in several salient alignment properties from those that do not. Using a support vector machine, we were able to predict the inference of discordant tree topologies with up to 80% accuracy from alignment properties alone.

Regression analysis using dependent Polya trees.

PubMed

Schörgendorfer, Angela; Branscum, Adam J

2013-11-30

Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

SPACE PROPULSION SYSTEM PHASED-MISSION PROBABILITY ANALYSIS USING CONVENTIONAL PRA METHODS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Curtis Smith; James Knudsen

As part of a series of papers on the topic of advance probabilistic methods, a benchmark phased-mission problem has been suggested. This problem consists of modeling a space mission using an ion propulsion system, where the mission consists of seven mission phases. The mission requires that the propulsion operate for several phases, where the configuration changes as a function of phase. The ion propulsion system itself consists of five thruster assemblies and a single propellant supply, where each thruster assembly has one propulsion power unit and two ion engines. In this paper, we evaluate the probability of mission failure usingmore » the conventional methodology of event tree/fault tree analysis. The event tree and fault trees are developed and analyzed using Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE). While the benchmark problem is nominally a "dynamic" problem, in our analysis the mission phases are modeled in a single event tree to show the progression from one phase to the next. The propulsion system is modeled in fault trees to account for the operation; or in this case, the failure of the system. Specifically, the propulsion system is decomposed into each of the five thruster assemblies and fed into the appropriate N-out-of-M gate to evaluate mission failure. A separate fault tree for the propulsion system is developed to account for the different success criteria of each mission phase. Common-cause failure modeling is treated using traditional (i.e., parametrically) methods. As part of this paper, we discuss the overall results in addition to the positive and negative aspects of modeling dynamic situations with non-dynamic modeling techniques. One insight from the use of this conventional method for analyzing the benchmark problem is that it requires significant manual manipulation to the fault trees and how they are linked into the event tree. The conventional method also requires editing the resultant cut sets to obtain the correct results. While conventional methods may be used to evaluate a dynamic system like that in the benchmark, the level of effort required may preclude its use on real-world problems.« less

Bayesian hierarchical modeling for detecting safety signals in clinical trials.

PubMed

Xia, H Amy; Ma, Haijun; Carlin, Bradley P

2011-09-01

Detection of safety signals from clinical trial adverse event data is critical in drug development, but carries a challenging statistical multiplicity problem. Bayesian hierarchical mixture modeling is appealing for its ability to borrow strength across subgroups in the data, as well as moderate extreme findings most likely due merely to chance. We implement such a model for subject incidence (Berry and Berry, 2004 ) using a binomial likelihood, and extend it to subject-year adjusted incidence rate estimation under a Poisson likelihood. We use simulation to choose a signal detection threshold, and illustrate some effective graphics for displaying the flagged signals.

Research frontiers for improving our understanding of drought‐induced tree and forest mortality

USGS Publications Warehouse

Hartmann, Henrik; Moura, Catarina; Anderegg, William R. L.; Ruehr, Nadine; Salmon, Yann; Allen, Craig D.; Arndt, Stefan K.; Breshears, David D.; Davi, Hendrik; Galbraith, David; Ruthrof, Katinka X.; Wunder, Jan; Adams, Henry D.; Bloemen, Jasper; Cailleret, Maxime; Cobb, Richard; Gessler, Arthur; Grams, Thorsten E. E.; Jansen, Steven; Kautz, Markus; Lloret, Francisco; O’Brien, Michael

2018-01-01

Accumulating evidence highlights increased mortality risks for trees during severe drought, particularly under warmer temperatures and increasing vapour pressure deficit (VPD). Resulting forest die‐off events have severe consequences for ecosystem services, biophysical and biogeochemical land–atmosphere processes. Despite advances in monitoring, modelling and experimental studies of the causes and consequences of tree death from individual tree to ecosystem and global scale, a general mechanistic understanding and realistic predictions of drought mortality under future climate conditions are still lacking. We update a global tree mortality map and present a roadmap to a more holistic understanding of forest mortality across scales. We highlight priority research frontiers that promote: (1) new avenues for research on key tree ecophysiological responses to drought; (2) scaling from the tree/plot level to the ecosystem and region; (3) improvements of mortality risk predictions based on both empirical and mechanistic insights; and (4) a global monitoring network of forest mortality. In light of recent and anticipated large forest die‐off events such a research agenda is timely and needed to achieve scientific understanding for realistic predictions of drought‐induced tree mortality. The implementation of a sustainable network will require support by stakeholders and political authorities at the international level.

Exploring the full natural variability of eruption sizes within probabilistic hazard assessment of tephra dispersal

NASA Astrophysics Data System (ADS)

Selva, Jacopo; Sandri, Laura; Costa, Antonio; Tonini, Roberto; Folch, Arnau; Macedonio, Giovanni

2014-05-01

The intrinsic uncertainty and variability associated to the size of next eruption strongly affects short to long-term tephra hazard assessment. Often, emergency plans are established accounting for the effects of one or a few representative scenarios (meant as a specific combination of eruptive size and vent position), selected with subjective criteria. On the other hand, probabilistic hazard assessments (PHA) consistently explore the natural variability of such scenarios. PHA for tephra dispersal needs the definition of eruptive scenarios (usually by grouping possible eruption sizes and vent positions in classes) with associated probabilities, a meteorological dataset covering a representative time period, and a tephra dispersal model. PHA results from combining simulations considering different volcanological and meteorological conditions through a weight given by their specific probability of occurrence. However, volcanological parameters, such as erupted mass, eruption column height and duration, bulk granulometry, fraction of aggregates, typically encompass a wide range of values. Because of such a variability, single representative scenarios or size classes cannot be adequately defined using single values for the volcanological inputs. Here we propose a method that accounts for this within-size-class variability in the framework of Event Trees. The variability of each parameter is modeled with specific Probability Density Functions, and meteorological and volcanological inputs are chosen by using a stratified sampling method. This procedure allows avoiding the bias introduced by selecting single representative scenarios and thus neglecting most of the intrinsic eruptive variability. When considering within-size-class variability, attention must be paid to appropriately weight events falling within the same size class. While a uniform weight to all the events belonging to a size class is the most straightforward idea, this implies a strong dependence on the thresholds dividing classes: under this choice, the largest event of a size class has a much larger weight than the smallest event of the subsequent size class. In order to overcome this problem, in this study, we propose an innovative solution able to smoothly link the weight variability within each size class to the variability among the size classes through a common power law, and, simultaneously, respect the probability of different size classes conditional to the occurrence of an eruption. Embedding this procedure into the Bayesian Event Tree scheme enables for tephra fall PHA, quantified through hazard curves and maps representing readable results applicable in planning risk mitigation actions, and for the quantification of its epistemic uncertainties. As examples, we analyze long-term tephra fall PHA at Vesuvius and Campi Flegrei. We integrate two tephra dispersal models (the analytical HAZMAP and the numerical FALL3D) into BET_VH. The ECMWF reanalysis dataset are used for exploring different meteorological conditions. The results obtained clearly show that PHA accounting for the whole natural variability significantly differs from that based on a representative scenarios, as in volcanic hazard common practice.

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Roth, Dan; Wilkins, David C.

2001-01-01

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.

Plastid phylogenomics of the cool-season grass subfamily: clarification of relationships among early-diverging tribes.

PubMed

Saarela, Jeffery M; Wysocki, William P; Barrett, Craig F; Soreng, Robert J; Davis, Jerrold I; Clark, Lynn G; Kelchner, Scot A; Pires, J Chris; Edger, Patrick P; Mayfield, Dustin R; Duvall, Melvin R

2015-05-04

Whole plastid genomes are being sequenced rapidly from across the green plant tree of life, and phylogenetic analyses of these are increasing resolution and support for relationships that have varied among or been unresolved in earlier single- and multi-gene studies. Pooideae, the cool-season grass lineage, is the largest of the 12 grass subfamilies and includes important temperate cereals, turf grasses and forage species. Although numerous studies of the phylogeny of the subfamily have been undertaken, relationships among some 'early-diverging' tribes conflict among studies, and some relationships among subtribes of Poeae have not yet been resolved. To address these issues, we newly sequenced 25 whole plastomes, which showed rearrangements typical of Poaceae. These plastomes represent 9 tribes and 11 subtribes of Pooideae, and were analysed with 20 existing plastomes for the subfamily. Maximum likelihood (ML), maximum parsimony (MP) and Bayesian inference (BI) robustly resolve most deep relationships in the subfamily. Complete plastome data provide increased nodal support compared with protein-coding data alone at nodes that are not maximally supported. Following the divergence of Brachyelytrum, Phaenospermateae, Brylkinieae-Meliceae and Ampelodesmeae-Stipeae are the successive sister groups of the rest of the subfamily. Ampelodesmeae are nested within Stipeae in the plastome trees, consistent with its hybrid origin between a phaenospermatoid and a stipoid grass (the maternal parent). The core Pooideae are strongly supported and include Brachypodieae, a Bromeae-Triticeae clade and Poeae. Within Poeae, a novel sister group relationship between Phalaridinae and Torreyochloinae is found, and the relative branching order of this clade and Aveninae, with respect to an Agrostidinae-Brizinae clade, are discordant between MP and ML/BI trees. Maximum likelihood and Bayesian analyses strongly support Airinae and Holcinae as the successive sister groups of a Dactylidinae-Loliinae clade. Published by Oxford University Press on behalf of the Annals of Botany Company.

Drought-Adaptation Potential in Fagus sylvatica: Linking Moisture Availability with Genetic Diversity and Dendrochronology

PubMed Central

Pluess, Andrea R.; Weber, Pascale

2012-01-01

Background Microevolution is essential for species persistence especially under anticipated climate change scenarios. Species distribution projection models suggested that the dominant tree species of lowland forests in Switzerland, European beech (Fagus sylvatica L.), might disappear from most areas due to expected longer dry periods. However, if genotypes at the moisture boundary of the species climatic envelope are adapted to lower moisture availability, they can serve as seed source for the continuation of beech forests under changing climates. Methodology/Principal Findings With an AFLP genome scan approach, we studied neutral and potentially adaptive genetic variation in Fagus sylvatica in three regions containing a dry and a mesic site each (n ind. = 241, n markers = 517). We linked this dataset with dendrochronological growth measures and local moisture availabilities based on precipitation and soil characteristics. Genetic diversity decreased slightly at dry sites. Overall genetic differentiation was low (F st = 0.028) and Bayesian cluster analysis grouped all populations together suggesting high (historical) gene flow. The Bayesian outlier analyses indicated 13 markers with three markers differing between all dry and mesic sites and the others between the contrasting sites within individual regions. A total of 41 markers, including seven outlier loci, changed their frequency with local moisture availability. Tree height and median basal growth increments were reduced at dry sites, but marker presence/absence was not related to dendrochronological characteristics. Conclusion and Their Significance The outlier alleles and the makers with changing frequencies in relation to moisture availability indicate microevolutionary processes occurring within short geographic distances. The general genetic similarity among sites suggests that ‘preadaptive’ genes can easily spread across the landscape. Yet, due to the long live span of trees, fostering saplings originating from dry sites and grown within mesic sites might increase resistance of beech forests during the anticipated longer dry periods. PMID:22448260

Drought-adaptation potential in Fagus sylvatica: linking moisture availability with genetic diversity and dendrochronology.

PubMed

Pluess, Andrea R; Weber, Pascale

2012-01-01

Microevolution is essential for species persistence especially under anticipated climate change scenarios. Species distribution projection models suggested that the dominant tree species of lowland forests in Switzerland, European beech (Fagus sylvatica L.), might disappear from most areas due to expected longer dry periods. However, if genotypes at the moisture boundary of the species climatic envelope are adapted to lower moisture availability, they can serve as seed source for the continuation of beech forests under changing climates. With an AFLP genome scan approach, we studied neutral and potentially adaptive genetic variation in Fagus sylvatica in three regions containing a dry and a mesic site each (n(ind.) = 241, n(markers) = 517). We linked this dataset with dendrochronological growth measures and local moisture availabilities based on precipitation and soil characteristics. Genetic diversity decreased slightly at dry sites. Overall genetic differentiation was low (F(st) = 0.028) and Bayesian cluster analysis grouped all populations together suggesting high (historical) gene flow. The Bayesian outlier analyses indicated 13 markers with three markers differing between all dry and mesic sites and the others between the contrasting sites within individual regions. A total of 41 markers, including seven outlier loci, changed their frequency with local moisture availability. Tree height and median basal growth increments were reduced at dry sites, but marker presence/absence was not related to dendrochronological characteristics. CONCLUSION AND THEIR SIGNIFICANCE: The outlier alleles and the makers with changing frequencies in relation to moisture availability indicate microevolutionary processes occurring within short geographic distances. The general genetic similarity among sites suggests that 'preadaptive' genes can easily spread across the landscape. Yet, due to the long live span of trees, fostering saplings originating from dry sites and grown within mesic sites might increase resistance of beech forests during the anticipated longer dry periods.

Phylogenetic relationships of Cranichidinae and Prescottiinae (Orchidaceae, Cranichideae) inferred from plastid and nuclear DNA sequences

PubMed Central

Salazar, Gerardo A.; Cabrera, Lidia I.; Madriñán, Santiago; Chase, Mark W.

2009-01-01

Background and Aims Phylogenetic relationships of subtribes Cranichidinae and Prescottiinae, two diverse groups of neotropical terrestrial orchids, are not satisfactorily understood. A previous molecular phylogenetic study supported monophyly for Cranichidinae, but Prescottiinae consisted of two clades not sister to one another. However, that analysis included only 11 species and eight genera of these subtribes. Here, plastid and nuclear DNA sequences are analysed for an enlarged sample of genera and species of Cranichidinae and Prescottiinae with the aim of clarifying their relationships, evaluating the phylogenetic position of the monospecific genera Exalaria, Ocampoa and Pseudocranichis and examining the value of various structural traits as taxonomic markers. Methods Approx. 6000 bp of nucleotide sequences from nuclear ribosomal (ITS) and plastid DNA (rbcL, matK-trnK and trnL-trnF) were analysed with cladistic parsimony and Bayesian inference for 45 species/14 genera of Cranichidinae and Prescottiinae (plus suitable outgroups). The utility of flower orientation, thickenings of velamen cell walls, hamular viscidium and pseudolabellum to mark clades recovered by the molecular analysis was assessed by tracing these characters on the molecular trees. Key Results Spiranthinae, Cranichidinae, paraphyletic Prescottia (with Pseudocranichis embedded), and a group of mainly Andean ‘prescottioid’ genera (the ‘Stenoptera clade’) were strongly supported. Relationships among these clades were unresolved by parsimony but the Bayesian tree provided moderately strong support for the resolution (Spiranthinae–(Stenoptera clade-(Prescottia/Pseudocranichis–Cranichidinae))). Three of the four structural characters mark clades on the molecular trees, but the possession of a pseudolabellum is variable in the polyphyletic Ponthieva. Conclusions No evidence was found for monophyly of Prescottiinae and the reinstatement of Cranichidinae s.l. (including the genera of ‘Prescottiinae’) is favoured. Cranichidinae s.l. are diagnosed by non-resupinate flowers. Lack of support from parsimony for relationships among the major clades of core spiranthids is suggestive of a rapid morphological radiation or a slow rate of molecular evolution. PMID:19136493

The fundamental theorem of asset pricing under default and collateral in finite discrete time

NASA Astrophysics Data System (ADS)

Alvarez-Samaniego, Borys; Orrillo, Jaime

2006-08-01

We consider a financial market where time and uncertainty are modeled by a finite event-tree. The event-tree has a length of N, a unique initial node at the initial date, and a continuum of branches at each node of the tree. Prices and returns of J assets are modeled, respectively, by a R2JxR2J-valued stochastic process . In this framework we prove a version of the Fundamental Theorem of Asset Pricing which applies to defaultable securities backed by exogenous collateral suffering a contingent linear depreciation.

Multi-Detection Events, Probability Density Functions, and Reduced Location Area

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eslinger, Paul W.; Schrom, Brian T.

2016-03-01

Abstract Several efforts have been made in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) community to assess the benefits of combining detections of radionuclides to improve the location estimates available from atmospheric transport modeling (ATM) backtrack calculations. We present a Bayesian estimation approach rather than a simple dilution field of regard approach to allow xenon detections and non-detections to be combined mathematically. This system represents one possible probabilistic approach to radionuclide event formation. Application of this method to a recent interesting radionuclide event shows a substantial reduction in the location uncertainty of that event.

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

PubMed

Liu, Yang; Traskin, Mikhail; Lorch, Scott A; George, Edward I; Small, Dylan

2015-03-01

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital's expected outcome rate given its patient mix and service is called risk adjustment (Iezzoni 1997). Risk adjustment is critical for accurately evaluating and comparing hospitals' performances since we would not want to unfairly penalize a hospital just because it treats sicker patients. The key to risk adjustment is accurately estimating the probability of an Outcome given patient characteristics. For cases with binary outcomes, the method that is commonly used in risk adjustment is logistic regression. In this paper, we consider ensemble of trees methods as alternatives for risk adjustment, including random forests and Bayesian additive regression trees (BART). Both random forests and BART are modern machine learning methods that have been shown recently to have excellent performance for prediction of outcomes in many settings. We apply these methods to carry out risk adjustment for the performance of neonatal intensive care units (NICU). We show that these ensemble of trees methods outperform logistic regression in predicting mortality among babies treated in NICU, and provide a superior method of risk adjustment compared to logistic regression.

Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.

PubMed

Ding, Mingtao; He, Lihan; Dunson, David; Carin, Lawrence

2012-12-01

A nonparametric Bayesian model is proposed for segmenting time-evolving multivariate spatial point process data. An inhomogeneous Poisson process is assumed, with a logistic stick-breaking process (LSBP) used to encourage piecewise-constant spatial Poisson intensities. The LSBP explicitly favors spatially contiguous segments, and infers the number of segments based on the observed data. The temporal dynamics of the segmentation and of the Poisson intensities are modeled with exponential correlation in time, implemented in the form of a first-order autoregressive model for uniformly sampled discrete data, and via a Gaussian process with an exponential kernel for general temporal sampling. We consider and compare two different inference techniques: a Markov chain Monte Carlo sampler, which has relatively high computational complexity; and an approximate and efficient variational Bayesian analysis. The model is demonstrated with a simulated example and a real example of space-time crime events in Cincinnati, Ohio, USA.

Conceptual issues in Bayesian divergence time estimation

PubMed Central

2016-01-01

Bayesian inference of species divergence times is an unusual statistical problem, because the divergence time parameters are not identifiable unless both fossil calibrations and sequence data are available. Commonly used marginal priors on divergence times derived from fossil calibrations may conflict with node order on the phylogenetic tree causing a change in the prior on divergence times for a particular topology. Care should be taken to avoid confusing this effect with changes due to informative sequence data. This effect is illustrated with examples. A topology-consistent prior that preserves the marginal priors is defined and examples are constructed. Conflicts between fossil calibrations and relative branch lengths (based on sequence data) can cause estimates of divergence times that are grossly incorrect, yet have a narrow posterior distribution. An example of this effect is given; it is recommended that overly narrow posterior distributions of divergence times should be carefully scrutinized. This article is part of the themed issue ‘Dating species divergences using rocks and clocks’. PMID:27325831

Conceptual issues in Bayesian divergence time estimation.

PubMed

Rannala, Bruce

2016-07-19

Bayesian inference of species divergence times is an unusual statistical problem, because the divergence time parameters are not identifiable unless both fossil calibrations and sequence data are available. Commonly used marginal priors on divergence times derived from fossil calibrations may conflict with node order on the phylogenetic tree causing a change in the prior on divergence times for a particular topology. Care should be taken to avoid confusing this effect with changes due to informative sequence data. This effect is illustrated with examples. A topology-consistent prior that preserves the marginal priors is defined and examples are constructed. Conflicts between fossil calibrations and relative branch lengths (based on sequence data) can cause estimates of divergence times that are grossly incorrect, yet have a narrow posterior distribution. An example of this effect is given; it is recommended that overly narrow posterior distributions of divergence times should be carefully scrutinized.This article is part of the themed issue 'Dating species divergences using rocks and clocks'. © 2016 The Author(s).

Species delimitation of the Hyphydrus ovatus complex in western Palaearctic with an update of species distributions (Coleoptera, Dytiscidae)

PubMed Central

Bergsten, Johannes; Weingartner, Elisabeth; Hájek, Jiří

2017-01-01

Abstract The species status of Hyphydrus anatolicus Guignot, 1957 and H. sanctus Sharp, 1882, previously often confused with the widespread H. ovatus (Linnaeus, 1760), are tested with molecular and morphological characters. Cytochrome c oxidase subunit 1 (CO1) was sequenced for 32 specimens of all three species. Gene-trees were inferred with parsimony, time-free bayesian and strict clock bayesian analyses. The GMYC model was used to estimate species limits. All three species were reciprocally monophyletic with CO1 and highly supported. The GMYC species delimitation analysis unequivocally delimited the three species with no other than the three species solution included in the confidence interval. A likelihood ratio test rejected the one-species null model. Important morphological characters distinguishing the species are provided and illustrated. New distributional data are given for the following species: Hyphydrus anatolicus from Slovakia and Ukraine, and H. aubei Ganglbauer, 1891, and H. sanctus from Turkey. PMID:28769697

Smile detectors correlation

NASA Astrophysics Data System (ADS)

Yuksel, Kivanc; Chang, Xin; Skarbek, Władysław

2017-08-01

The novel smile recognition algorithm is presented based on extraction of 68 facial salient points (fp68) using the ensemble of regression trees. The smile detector exploits the Support Vector Machine linear model. It is trained with few hundreds exemplar images by SVM algorithm working in 136 dimensional space. It is shown by the strict statistical data analysis that such geometric detector strongly depends on the geometry of mouth opening area, measured by triangulation of outer lip contour. To this goal two Bayesian detectors were developed and compared with SVM detector. The first uses the mouth area in 2D image, while the second refers to the mouth area in 3D animated face model. The 3D modeling is based on Candide-3 model and it is performed in real time along with three smile detectors and statistics estimators. The mouth area/Bayesian detectors exhibit high correlation with fp68/SVM detector in a range [0:8; 1:0], depending mainly on light conditions and individual features with advantage of 3D technique, especially in hard light conditions.

BEASTling: A software tool for linguistic phylogenetics using BEAST 2

PubMed Central

Forkel, Robert; Kaiping, Gereon A.; Atkinson, Quentin D.

2017-01-01

We present a new open source software tool called BEASTling, designed to simplify the preparation of Bayesian phylogenetic analyses of linguistic data using the BEAST 2 platform. BEASTling transforms comparatively short and human-readable configuration files into the XML files used by BEAST to specify analyses. By taking advantage of Creative Commons-licensed data from the Glottolog language catalog, BEASTling allows the user to conveniently filter datasets using names for recognised language families, to impose monophyly constraints so that inferred language trees are backward compatible with Glottolog classifications, or to assign geographic location data to languages for phylogeographic analyses. Support for the emerging cross-linguistic linked data format (CLDF) permits easy incorporation of data published in cross-linguistic linked databases into analyses. BEASTling is intended to make the power of Bayesian analysis more accessible to historical linguists without strong programming backgrounds, in the hopes of encouraging communication and collaboration between those developing computational models of language evolution (who are typically not linguists) and relevant domain experts. PMID:28796784

BEASTling: A software tool for linguistic phylogenetics using BEAST 2.

PubMed

Maurits, Luke; Forkel, Robert; Kaiping, Gereon A; Atkinson, Quentin D

2017-01-01

We present a new open source software tool called BEASTling, designed to simplify the preparation of Bayesian phylogenetic analyses of linguistic data using the BEAST 2 platform. BEASTling transforms comparatively short and human-readable configuration files into the XML files used by BEAST to specify analyses. By taking advantage of Creative Commons-licensed data from the Glottolog language catalog, BEASTling allows the user to conveniently filter datasets using names for recognised language families, to impose monophyly constraints so that inferred language trees are backward compatible with Glottolog classifications, or to assign geographic location data to languages for phylogeographic analyses. Support for the emerging cross-linguistic linked data format (CLDF) permits easy incorporation of data published in cross-linguistic linked databases into analyses. BEASTling is intended to make the power of Bayesian analysis more accessible to historical linguists without strong programming backgrounds, in the hopes of encouraging communication and collaboration between those developing computational models of language evolution (who are typically not linguists) and relevant domain experts.

Data analysis using scale-space filtering and Bayesian probabilistic reasoning

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Kutulakos, Kiriakos; Robinson, Peter

1991-01-01

This paper describes a program for analysis of output curves from Differential Thermal Analyzer (DTA). The program first extracts probabilistic qualitative features from a DTA curve of a soil sample, and then uses Bayesian probabilistic reasoning to infer the mineral in the soil. The qualifier module employs a simple and efficient extension of scale-space filtering suitable for handling DTA data. We have observed that points can vanish from contours in the scale-space image when filtering operations are not highly accurate. To handle the problem of vanishing points, perceptual organizations heuristics are used to group the points into lines. Next, these lines are grouped into contours by using additional heuristics. Probabilities are associated with these contours using domain-specific correlations. A Bayes tree classifier processes probabilistic features to infer the presence of different minerals in the soil. Experiments show that the algorithm that uses domain-specific correlation to infer qualitative features outperforms a domain-independent algorithm that does not.

Effects of biotic and abiotic factors on resistance versus resilience of Douglas fir to drought.

PubMed

Carnwath, Gunnar; Nelson, Cara

2017-01-01

Significant increases in tree mortality due to drought-induced physiological stress have been documented worldwide. This trend is likely to continue with increased frequency and severity of extreme drought events in the future. Therefore, understanding the factors that influence variability in drought responses among trees will be critical to predicting ecosystem responses to climate change and developing effective management actions. In this study, we used hierarchical mixed-effects models to analyze drought responses of Pseudotsuga menziesii in 20 unmanaged forests stands across a broad range of environmental conditions in northeastern Washington, USA. We aimed to 1) identify the biotic and abiotic attributes most closely associated with the responses of individual trees to drought and 2) quantify the variability in drought responses at different spatial scales. We found that growth rates and competition for resources significantly affected resistance to a severe drought event in 2001: slow-growing trees and trees growing in subordinate canopy positions and/or with more neighbors suffered greater declines in radial growth during the drought event. In contrast, the ability of a tree to return to normal growth when climatic conditions improved (resilience) was unaffected by competition or relative growth rates. Drought responses were significantly influenced by tree age: older trees were more resistant but less resilient than younger trees. Finally, we found differences between resistance and resilience in spatial scale: a significant proportion (approximately 50%) of the variability in drought resistance across the study area was at broad spatial scales (i.e. among different forest types), most likely due to differences in the total amount of precipitation received at different elevations; in contrast, variation in resilience was overwhelmingly (82%) at the level of individual trees within stands and there was no difference in drought resilience among forest types. Our results suggest that for Pseudotsuga menziesii resistance and resilience to drought are driven by different factors and vary at different spatial scales.

A synthesis of radial growth patterns preceding tree mortality

USGS Publications Warehouse

Cailleret, Maxime; Jansen, Steven; Robert, Elisabeth M.R.; Desoto, Lucia; Aakala, Tuomas; Antos, Joseph A.; Beikircher, Barbara; Bigler, Christof; Bugmann, Harald; Caccianiga, Marco; Cada, Vojtech; Camarero, Jesus J.; Cherubini, Paolo; Cochard, Herve; Coyea, Marie R.; Cufar, Katarina; Das, Adrian J.; Davi, Hendrik; Delzon, Sylvain; Dorman, Michael; Gea-Izquierdo, Guillermo; Gillner, Sten; Haavik, Laurel J.; Hartmann, Henrik; Heres, Ana-Maria; Hultine, Kevin R.; Janda, Pavel; Kane, Jeffrey M.; Kharuk, Vyacheslav I.; Kitzberger, Thomas; Klein, Tamir; Kramer, Koen; Lens, Frederic; Levanic, Tom; Calderon, Juan C. Linares; Lloret, Francisco; Lobo-Do-Vale, Raquel; Lombardi, Fabio; Lopez Rodriguez, Rosana; Makinen, Harri; Mayr, Stefan; Meszaros, IIona; Metsaranta, Juha M.; Minunno, Francesco; Oberhuber, Walter; Papadopoulos, Andreas; Peltoniemi, Mikko; Petritan, Any M.; Rohner, Brigitte; Sanguesa-Barreda, Gabriel; Sarris, Dimitrios; Smith, Jeremy M.; Stan, Amanda B.; Sterck, Frank; Stojanovic, Dejan B.; Suarez, Maria L.; Svoboda, Miroslav; Tognetti, Roberto; Torres-Ruiz, Jose M.; Trotsiuk, Volodymyr; Villalba, Ricardo; Vodde, Floor; Westwood, Alana R.; Wyckoff, Peter H.; Zafirov, Nikolay; Martinez-Vilalta, Jordi

2017-01-01

Tree mortality is a key factor influencing forest functions and dynamics, but our understanding of the mechanisms leading to mortality and the associated changes in tree growth rates are still limited. We compiled a new pan-continental tree-ring width database from sites where both dead and living trees were sampled (2970 dead and 4224 living trees from 190 sites, including 36 species), and compared early and recent growth rates between trees that died and those that survived a given mortality event. We observed a decrease in radial growth before death in ca. 84% of the mortality events. The extent and duration of these reductions were highly variable (1–100 years in 96% of events) due to the complex interactions among study species and the source(s) of mortality. Strong and long-lasting declines were found for gymnosperms, shade- and drought-tolerant species, and trees that died from competition. Angiosperms and trees that died due to biotic attacks (especially bark-beetles) typically showed relatively small and short-term growth reductions. Our analysis did not highlight any universal trade-off between early growth and tree longevity within a species, although this result may also reflect high variability in sampling design among sites. The intersite and interspecific variability in growth patterns before mortality provides valuable information on the nature of the mortality process, which is consistent with our understanding of the physiological mechanisms leading to mortality. Abrupt changes in growth immediately before death can be associated with generalized hydraulic failure and/or bark-beetle attack, while long-term decrease in growth may be associated with a gradual decline in hydraulic performance coupled with depletion in carbon reserves. Our results imply that growth-based mortality algorithms may be a powerful tool for predicting gymnosperm mortality induced by chronic stress, but not necessarily so for angiosperms and in case of intense drought or bark-beetle outbreaks.

A synthesis of radial growth patterns preceding tree mortality.

PubMed

Cailleret, Maxime; Jansen, Steven; Robert, Elisabeth M R; Desoto, Lucía; Aakala, Tuomas; Antos, Joseph A; Beikircher, Barbara; Bigler, Christof; Bugmann, Harald; Caccianiga, Marco; Čada, Vojtěch; Camarero, Jesus J; Cherubini, Paolo; Cochard, Hervé; Coyea, Marie R; Čufar, Katarina; Das, Adrian J; Davi, Hendrik; Delzon, Sylvain; Dorman, Michael; Gea-Izquierdo, Guillermo; Gillner, Sten; Haavik, Laurel J; Hartmann, Henrik; Hereş, Ana-Maria; Hultine, Kevin R; Janda, Pavel; Kane, Jeffrey M; Kharuk, Vyacheslav I; Kitzberger, Thomas; Klein, Tamir; Kramer, Koen; Lens, Frederic; Levanic, Tom; Linares Calderon, Juan C; Lloret, Francisco; Lobo-Do-Vale, Raquel; Lombardi, Fabio; López Rodríguez, Rosana; Mäkinen, Harri; Mayr, Stefan; Mészáros, Ilona; Metsaranta, Juha M; Minunno, Francesco; Oberhuber, Walter; Papadopoulos, Andreas; Peltoniemi, Mikko; Petritan, Any M; Rohner, Brigitte; Sangüesa-Barreda, Gabriel; Sarris, Dimitrios; Smith, Jeremy M; Stan, Amanda B; Sterck, Frank; Stojanović, Dejan B; Suarez, Maria L; Svoboda, Miroslav; Tognetti, Roberto; Torres-Ruiz, José M; Trotsiuk, Volodymyr; Villalba, Ricardo; Vodde, Floor; Westwood, Alana R; Wyckoff, Peter H; Zafirov, Nikolay; Martínez-Vilalta, Jordi

2017-04-01

Tree mortality is a key factor influencing forest functions and dynamics, but our understanding of the mechanisms leading to mortality and the associated changes in tree growth rates are still limited. We compiled a new pan-continental tree-ring width database from sites where both dead and living trees were sampled (2970 dead and 4224 living trees from 190 sites, including 36 species), and compared early and recent growth rates between trees that died and those that survived a given mortality event. We observed a decrease in radial growth before death in ca. 84% of the mortality events. The extent and duration of these reductions were highly variable (1-100 years in 96% of events) due to the complex interactions among study species and the source(s) of mortality. Strong and long-lasting declines were found for gymnosperms, shade- and drought-tolerant species, and trees that died from competition. Angiosperms and trees that died due to biotic attacks (especially bark-beetles) typically showed relatively small and short-term growth reductions. Our analysis did not highlight any universal trade-off between early growth and tree longevity within a species, although this result may also reflect high variability in sampling design among sites. The intersite and interspecific variability in growth patterns before mortality provides valuable information on the nature of the mortality process, which is consistent with our understanding of the physiological mechanisms leading to mortality. Abrupt changes in growth immediately before death can be associated with generalized hydraulic failure and/or bark-beetle attack, while long-term decrease in growth may be associated with a gradual decline in hydraulic performance coupled with depletion in carbon reserves. Our results imply that growth-based mortality algorithms may be a powerful tool for predicting gymnosperm mortality induced by chronic stress, but not necessarily so for angiosperms and in case of intense drought or bark-beetle outbreaks. © 2016 John Wiley & Sons Ltd.

Effects of biotic and abiotic factors on resistance versus resilience of Douglas fir to drought

PubMed Central

Nelson, Cara

2017-01-01

Significant increases in tree mortality due to drought-induced physiological stress have been documented worldwide. This trend is likely to continue with increased frequency and severity of extreme drought events in the future. Therefore, understanding the factors that influence variability in drought responses among trees will be critical to predicting ecosystem responses to climate change and developing effective management actions. In this study, we used hierarchical mixed-effects models to analyze drought responses of Pseudotsuga menziesii in 20 unmanaged forests stands across a broad range of environmental conditions in northeastern Washington, USA. We aimed to 1) identify the biotic and abiotic attributes most closely associated with the responses of individual trees to drought and 2) quantify the variability in drought responses at different spatial scales. We found that growth rates and competition for resources significantly affected resistance to a severe drought event in 2001: slow-growing trees and trees growing in subordinate canopy positions and/or with more neighbors suffered greater declines in radial growth during the drought event. In contrast, the ability of a tree to return to normal growth when climatic conditions improved (resilience) was unaffected by competition or relative growth rates. Drought responses were significantly influenced by tree age: older trees were more resistant but less resilient than younger trees. Finally, we found differences between resistance and resilience in spatial scale: a significant proportion (approximately 50%) of the variability in drought resistance across the study area was at broad spatial scales (i.e. among different forest types), most likely due to differences in the total amount of precipitation received at different elevations; in contrast, variation in resilience was overwhelmingly (82%) at the level of individual trees within stands and there was no difference in drought resilience among forest types. Our results suggest that for Pseudotsuga menziesii resistance and resilience to drought are driven by different factors and vary at different spatial scales. PMID:28973008

Windthrown trees on the Kings River Ranger District, Sierra National Forest: meteorological aspects

Treesearch

Michael A. Fosberg

1986-01-01

Blowdown in shelterwood, sanitation cuts, and other partial cuts on the Kings River Ranger District, Sierra National Forest, are due to Mono winds. Both winter storm and Mono winds were considered as causes of winter blowdown. All evidence, e.g., direction of tree-fall and occurrence of high wind events, point to Mono wind events as the cause of blowdown. Only 12...

Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

NASA Astrophysics Data System (ADS)

Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

2018-03-01

Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

Object-Oriented Algorithm For Evaluation Of Fault Trees

NASA Technical Reports Server (NTRS)

Patterson-Hine, F. A.; Koen, B. V.

1992-01-01

Algorithm for direct evaluation of fault trees incorporates techniques of object-oriented programming. Reduces number of calls needed to solve trees with repeated events. Provides significantly improved software environment for such computations as quantitative analyses of safety and reliability of complicated systems of equipment (e.g., spacecraft or factories).

The Imprint of Extreme Climate Events in Century-Long Time Series of Wood Anatomical Traits in High-Elevation Conifers

PubMed Central

Carrer, Marco; Brunetti, Michele; Castagneri, Daniele

2016-01-01

Extreme climate events are of key importance for forest ecosystems. However, both the inherent infrequency, stochasticity and multiplicity of extreme climate events, and the array of biological responses, challenges investigations. To cope with the long life cycle of trees and the paucity of the extreme events themselves, our inferences should be based on long-term observations. In this context, tree rings and the related xylem anatomical traits represent promising sources of information, due to the wide time perspective and quality of the information they can provide. Here we test, on two high-elevation conifers (Larix decidua and Picea abies sampled at 2100 m a.s.l. in the Eastern Alps), the associations among temperature extremes during the growing season and xylem anatomical traits, specifically the number of cells per ring (CN), cell wall thickness (CWT), and cell diameter (CD). To better track the effect of extreme events over the growing season, tree rings were partitioned in 10 sectors. Climate variability has been reconstructed, for 1800–2011 at monthly resolution and for 1926–2011 at daily resolution, by exploiting the excellent availability of very long and high quality instrumental records available for the surrounding area, and taking into account the relationship between meteorological variables and site topographical settings. Summer temperature influenced anatomical traits of both species, and tree-ring anatomical profiles resulted as being associated to temperature extremes. Most of the extreme values in anatomical traits occurred with warm (positive extremes) or cold (negative) conditions. However, 0–34% of occurrences did not match a temperature extreme event. Specifically, CWT and CN extremes were more clearly associated to climate than CD, which presented a bias to track cold extremes. Dendroanatomical analysis, coupled to high-quality daily-resolved climate records, seems a promising approach to study the effects of extreme events on trees, but further investigations are needed to improve our comprehension of the critical role of such elusive events in forest ecosystems. PMID:27242880

Fuel treatment effects on tree mortality following wildfire in dry mixed conifer forests, Washington State, USA

Treesearch

Susan J. Prichard; Maureen C. Kennedy

2012-01-01

Fuel reduction treatments are increasingly used to mitigate future wildfire severity in dry forests, but few opportunities exist to assess their effectiveness. We evaluated the influence of fuel treatment, tree size and species on tree mortality following a large wildfire event in recent thin-only, thin and prescribed burn (thin-Rx) units. Of the trees that died within...

Precipitation thresholds and drought-induced tree die-off: Insights from patterns of Pinus edulis mortality along an environmental stress gradient

Treesearch

Michael J. Clifford; Patrick D. Royer; Neil S. Cobb; David D. Breshears; Paulette L. Ford

2013-01-01

Recent regional tree die-off events appear to have been triggered by a combination of drought and heat - referred to as 'global-change-type drought'. To complement experiments focused on resolving mechanisms of drought-induced tree mortality, an evaluation of how patterns of tree die-off relate to highly spatially variable precipitation is needed....

Unraveling multiple changes in complex climate time series using Bayesian inference

NASA Astrophysics Data System (ADS)

Berner, Nadine; Trauth, Martin H.; Holschneider, Matthias

2016-04-01

Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of observations. Unraveling such transitions yields essential information for the understanding of the observed system. The precise detection and basic characterization of underlying changes is therefore of particular importance in environmental sciences. We present a kernel-based Bayesian inference approach to investigate direct as well as indirect climate observations for multiple generic transition events. In order to develop a diagnostic approach designed to capture a variety of natural processes, the basic statistical features of central tendency and dispersion are used to locally approximate a complex time series by a generic transition model. A Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of such a transition. To systematically investigate time series for multiple changes occurring at different temporal scales, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. Thus, based on a generic transition model a probability expression is derived that is capable to indicate multiple changes within a complex time series. We discuss the method's performance by investigating direct and indirect climate observations. The approach is applied to environmental time series (about 100 a), from the weather station in Tuscaloosa, Alabama, and confirms documented instrumentation changes. Moreover, the approach is used to investigate a set of complex terrigenous dust records from the ODP sites 659, 721/722 and 967 interpreted as climate indicators of the African region of the Plio-Pleistocene period (about 5 Ma). The detailed inference unravels multiple transitions underlying the indirect climate observations coinciding with established global climate events.

Gene-Tree Reconciliation with MUL-Trees to Resolve Polyploidy Events.

PubMed

Gregg, W C Thomas; Ather, S Hussain; Hahn, Matthew W

2017-11-01

Polyploidy can have a huge impact on the evolution of species, and it is a common occurrence, especially in plants. The two types of polyploids-autopolyploids and allopolyploids-differ in the level of divergence between the genes that are brought together in the new polyploid lineage. Because allopolyploids are formed via hybridization, the homoeologous copies of genes within them are at least as divergent as orthologs in the parental species that came together to form them. This means that common methods for estimating the parental lineages of allopolyploidy events are not accurate, and can lead to incorrect inferences about the number of gene duplications and losses. Here, we have adapted an algorithm for topology-based gene-tree reconciliation to work with multi-labeled trees (MUL-trees). By definition, MUL-trees have some tips with identical labels, which makes them a natural representation of the genomes of polyploids. Using this new reconciliation algorithm we can: accurately place allopolyploidy events on a phylogeny, identify the parental lineages that hybridized to form allopolyploids, distinguish between allo-, auto-, and (in most cases) no polyploidy, and correctly count the number of duplications and losses in a set of gene trees. We validate our method using gene trees simulated with and without polyploidy, and revisit the history of polyploidy in data from the clades including both baker's yeast and bread wheat. Our re-analysis of the yeast data confirms the allopolyploid origin and parental lineages previously identified for this group. The method presented here should find wide use in the growing number of genomes from species with a history of polyploidy. [Polyploidy; reconciliation; whole-genome duplication.]. © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Positive density-dependent reproduction regulated by local kinship and size in an understorey tropical tree

PubMed Central

Castilla, Antonio R.; Pope, Nathaniel; Jha, Shalene

2016-01-01

Background and Aims Global pollinator declines and continued habitat fragmentation highlight the critical need to understand reproduction and gene flow across plant populations. Plant size, conspecific density and local kinship (i.e. neighbourhood genetic relatedness) have been proposed as important mechanisms influencing the reproductive success of flowering plants, but have rarely been simultaneously investigated. Methods We conducted this study on a continuous population of the understorey tree Miconia affinis in the Forest Dynamics Plot on Barro Colorado Island in central Panama. We used spatial, reproductive and population genetic data to investigate the effects of tree size, conspecific neighbourhood density and local kinship on maternal and paternal reproductive success. We used a Bayesian framework to simultaneously model the effects of our explanatory variables on the mean and variance of maternal viable seed set and siring success. Key Results Our results reveal that large trees had lower proportions of viable seeds in their fruits but sired more seeds. We documented differential effects of neighbourhood density and local kinship on both maternal and paternal reproductive components. Trees in more dense neighbourhoods produced on average more viable seeds, although this positive density effect was influenced by variance-inflation with increasing local kinship. Neighbourhood density did not have significant effects on siring success. Conclusions This study is one of the first to reveal an interaction among tree size, conspecific density and local kinship as critical factors differentially influencing maternal and paternal reproductive success. We show that both maternal and paternal reproductive success should be evaluated to determine the population-level and individual traits most essential for plant reproduction. In addition to conserving large trees, we suggest the inclusion of small trees and the conservation of dense patches with low kinship as potential strategies for strengthening the reproductive status of tropical trees. PMID:26602288

Positive density-dependent reproduction regulated by local kinship and size in an understorey tropical tree.

PubMed

Castilla, Antonio R; Pope, Nathaniel; Jha, Shalene

2016-02-01

Global pollinator declines and continued habitat fragmentation highlight the critical need to understand reproduction and gene flow across plant populations. Plant size, conspecific density and local kinship (i.e. neighbourhood genetic relatedness) have been proposed as important mechanisms influencing the reproductive success of flowering plants, but have rarely been simultaneously investigated. We conducted this study on a continuous population of the understorey tree Miconia affinis in the Forest Dynamics Plot on Barro Colorado Island in central Panama. We used spatial, reproductive and population genetic data to investigate the effects of tree size, conspecific neighbourhood density and local kinship on maternal and paternal reproductive success. We used a Bayesian framework to simultaneously model the effects of our explanatory variables on the mean and variance of maternal viable seed set and siring success. Our results reveal that large trees had lower proportions of viable seeds in their fruits but sired more seeds. We documented differential effects of neighbourhood density and local kinship on both maternal and paternal reproductive components. Trees in more dense neighbourhoods produced on average more viable seeds, although this positive density effect was influenced by variance-inflation with increasing local kinship. Neighbourhood density did not have significant effects on siring success. This study is one of the first to reveal an interaction among tree size, conspecific density and local kinship as critical factors differentially influencing maternal and paternal reproductive success. We show that both maternal and paternal reproductive success should be evaluated to determine the population-level and individual traits most essential for plant reproduction. In addition to conserving large trees, we suggest the inclusion of small trees and the conservation of dense patches with low kinship as potential strategies for strengthening the reproductive status of tropical trees. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Nitrogen deposition outweighs climatic variability in driving annual growth rate of canopy beech trees: Evidence from long-term growth reconstruction across a geographic gradient.

PubMed

Gentilesca, Tiziana; Rita, Angelo; Brunetti, Michele; Giammarchi, Francesco; Leonardi, Stefano; Magnani, Federico; van Noije, Twan; Tonon, Giustino; Borghetti, Marco

2018-07-01

In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long-term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (G V ) and height (G H ) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site-specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO 2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed-effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long-term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO 2 effects on G V and G H were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (N dep ) effects were repeatedly observed in G V and G H ; the positive effects of N dep on canopy height growth rates, which tended to level off at N dep values greater than approximately 1.0 g m -2  y -1 , were interpreted as positive impacts on forest stand above-ground net productivity at the selected study sites. © 2018 John Wiley & Sons Ltd.

Tree mortality in the eastern Mediterranean, causes and implications under climatic change

NASA Astrophysics Data System (ADS)

Sarris, Dimitrios; Iacovou, Valentina; Hoch, Guenter; Vennetier, Michel; Siegwolf, Rolf; Christodoulakis, Dimitrios; Koerner, Christian

2015-04-01

The eastern Mediterranean has experienced repeated incidents of forest mortality related to drought in recent decades. Such events may become more frequent in the future as drought conditions are projected to further intensify due to global warming. We have been investigating the causes behind such forest mortality events in Pinus halepensis, (the most drought tolerant pine in the Mediterranean). We cored tree stems and sampled various tissue types from dry habitats close to sea level and explored growth responses, stable isotope signals and non-structural carbohydrate (NSC) concentrations. Under intense drought that coincided with pine desiccation events in natural populations our result indicate a significant reduction in tree growth, the most significant in more than a century despite the increase in atmospheric CO2 concentrations in recent decades. This has been accompanied by a lengthening in the integration periods of rainfall needed for pine growth, reaching even 5-6 years before and including the year of mortality occurrence. Oxygen stable isotopes indicate that these signals were associated with a shift in tree water utilization from deeper moisture pools related to past rainfall events. Furthermore, where the driest conditions occur, pine carbon reserves were found to increase in stem tissue, indicating that mortality in these pines cannot be explained by carbon starvation. Our findings suggest that for pine populations that are already water limited (i) a further atmospheric CO2 increase will not compensate for the reduction in growth because of a drier climate, (ii) hydraulic failure appears as the most likely cause of pine desiccation, as no shortage occurs in tree carbon reserves, (iii) a further increase in mortality events may cause these systems to become carbon sources.

Single-accelerometer-based daily physical activity classification.

PubMed

Long, Xi; Yin, Bin; Aarts, Ronald M

2009-01-01

In this study, a single tri-axial accelerometer placed on the waist was used to record the acceleration data for human physical activity classification. The data collection involved 24 subjects performing daily real-life activities in a naturalistic environment without researchers' intervention. For the purpose of assessing customers' daily energy expenditure, walking, running, cycling, driving, and sports were chosen as target activities for classification. This study compared a Bayesian classification with that of a Decision Tree based approach. A Bayes classifier has the advantage to be more extensible, requiring little effort in classifier retraining and software update upon further expansion or modification of the target activities. Principal components analysis was applied to remove the correlation among features and to reduce the feature vector dimension. Experiments using leave-one-subject-out and 10-fold cross validation protocols revealed a classification accuracy of approximately 80%, which was comparable with that obtained by a Decision Tree classifier.

Cladistic analysis of Bantu languages: a new tree based on combined lexical and grammatical data

NASA Astrophysics Data System (ADS)

Rexová, Kateřina; Bastin, Yvonne; Frynta, Daniel

2006-04-01

The phylogeny of the Bantu languages is reconstructed by application of the cladistic methodology to the combined lexical and grammatical data (87 languages, 144 characters). A maximum parsimony tree and Bayesian analysis supported some previously recognized clades, e.g., that of eastern and southern Bantu languages. Moreover, the results revealed that Bantu languages south and east of the equatorial forest are probably monophyletic. It suggests an unorthodox scenario of Bantu expansion including (after initial radiation in their homelands and neighboring territories) just a single passage through rainforest areas followed by a subsequent divergence into major clades. The likely localization of this divergence is in the area west of the Great Lakes. It conforms to the view that demographic expansion and dispersal throughout the dry-forests and savanna regions of subequatorial Africa was associated with the acquisition of new technologies (iron metallurgy and grain cultivation).

The interplay of stressful life events and coping skills on risk for suicidal behavior among youth students in contemporary China: a large scale cross-sectional study.

PubMed

Tang, Fang; Xue, Fuzhong; Qin, Ping

2015-07-31

Stressful life events are common among youth students and may induce psychological problems and even suicidal behaviors in those with poor coping skills. This study aims to assess the influence of stressful life events and coping skills on risk for suicidal behavior and to elucidate the underlying mechanism using a large sample of university students in China. 5972 students, randomly selected from 6 universities, completed the questionnaire survey. Logistic regression analysis was performed to estimate the effect of stressful life events and coping skills on risk for suicidal behavior. Bayesian network was further adopted to probe their probabilistic relationships. Of the 5972 students, 7.64% reported the presence of suicidal behavior (attempt or ideation) within the past one year period. Stressful life events such as strong conflicts with classmates and a failure in study exam constituted strong risk factors for suicidal behavior. The influence of coping skills varied according to the strategies adapted toward problems with a high score of approach coping skills significantly associated with a reduced risk of suicidal behavior. The Bayesian network indicated that the probability of suicidal behavior associated with specific life events was to a large extent conditional on coping skills. For instance, a stressful experience of having strong conflicts with classmates could result in a probability of suicidal behavior of 21.25% and 15.36% respectively, for female and male students with the score of approach coping skills under the average. Stressful life events and deficient coping skills are strong risk factors for suicidal behavior among youth students. The results underscore the importance of prevention efforts to improve coping skills towards stressful life events.

Sensitivity of Global Methane Bayesian Inversion to Surface Observation Data Sets and Chemical-Transport Model Resolution

NASA Astrophysics Data System (ADS)

Lew, E. J.; Butenhoff, C. L.; Karmakar, S.; Rice, A. L.; Khalil, A. K.

2017-12-01

Methane is the second most important greenhouse gas after carbon dioxide. In efforts to control emissions, a careful examination of the methane budget and source strengths is required. To determine methane surface fluxes, Bayesian methods are often used to provide top-down constraints. Inverse modeling derives unknown fluxes using observed methane concentrations, a chemical transport model (CTM) and prior information. The Bayesian inversion reduces prior flux uncertainties by exploiting information content in the data. While the Bayesian formalism produces internal error estimates of source fluxes, systematic or external errors that arise from user choices in the inversion scheme are often much larger. Here we examine model sensitivity and uncertainty of our inversion under different observation data sets and CTM grid resolution. We compare posterior surface fluxes using the data product GLOBALVIEW-CH4 against the event-level molar mixing ratio data available from NOAA. GLOBALVIEW-CH4 is a collection of CH4 concentration estimates from 221 sites, collected by 12 laboratories, that have been interpolated and extracted to provide weekly records from 1984-2008. Differently, the event-level NOAA data records methane mixing ratios field measurements from 102 sites, containing sampling frequency irregularities and gaps in time. Furthermore, the sampling platform types used by the data sets may influence the posterior flux estimates, namely fixed surface, tower, ship and aircraft sites. To explore the sensitivity of the posterior surface fluxes to the observation network geometry, inversions composed of all sites, only aircraft, only ship, only tower and only fixed surface sites, are performed and compared. Also, we investigate the sensitivity of the error reduction associated with the resolution of the GEOS-Chem simulation (4°×5° vs 2°×2.5°) used to calculate the response matrix. Using a higher resolution grid decreased the model-data error at most sites, thereby increasing the information at that site. These different inversions—event-level and interpolated data, higher and lower resolutions—are compared using an ensemble of descriptive and comparative statistics. Analyzing the sensitivity of the inverse model leads to more accurate estimates of the methane source category uncertainty.

Growth and reproduction respond differently to climate in three Neotropical tree species.

PubMed

Alfaro-Sánchez, Raquel; Muller-Landau, Helene C; Wright, S Joseph; Camarero, J Julio

2017-06-01

The response of tropical forests to anthropogenic climate change is critically important to future global carbon budgets, yet remains highly uncertain. Here, we investigate how precipitation, temperature, solar radiation and dry- and wet-season lengths are related to annual tree growth, flower production, and fruit production in three moist tropical forest tree species using long-term datasets from tree rings and litter traps in central Panama. We also evaluated how growth, flower, and fruit production were interrelated. We found that growth was positively correlated with wet-season precipitation in all three species: Jacaranda copaia (r = 0.63), Tetragastris panamensis (r = 0.39) and Trichilia tuberculata (r = 0.39). Flowering and fruiting in Jacaranda were negatively related to current-year dry-season rainfall and positively related to prior-year dry-season rainfall. Flowering in Tetragastris was negatively related to current-year annual mean temperature while Trichilia showed no significant relationships of reproduction with climate. Growth was significantly related to reproduction only in Tetragastris, where it was positively related to previous year fruiting. Our results suggest that tree growth in moist tropical forest tree species is generally reduced by drought events such as those associated with strong El Niño events. In contrast, interannual variation in reproduction is not generally associated with growth and has distinct and species-specific climate responses, with positive effects of El Niño events in some species. Understanding these contrasting climate effects on tree growth and reproduction is critical to predicting changes in tropical forest dynamics and species composition under climate change.

Molecular phylogeny and evolutionary history of Moricandia DC (Brassicaceae).

PubMed

Perfectti, Francisco; Gómez, José M; González-Megías, Adela; Abdelaziz, Mohamed; Lorite, Juan

2017-01-01

The phylogeny of tribe Brassiceae (Brassicaceae) has not yet been resolved because of its complex evolutionary history. This tribe comprises economically relevant species, including the genus Moricandia DC. This genus is currently distributed in North Africa, Middle East, Central Asia and Southern Europe, where it is associated with arid and semi-arid environments. Although some species of Moricandia have been used in several phylogenetic studies, the phylogeny of this genus is not well established. Here we present a phylogenetic analysis of the genus Moricandia using a nuclear (the internal transcribed spacers of the ribosomal DNA) and two plastidial regions (parts of the NADH dehydrogenase subunit F gene and the trn T- trn F region). We also included in the analyses members of their sister genus Rytidocarpus and from the close genus Eruca . The phylogenetic analyses showed a clear and robust phylogeny of the genus Moricandia . The Bayesian inference tree was concordant with the maximum likelihood and timing trees, with the plastidial and nuclear trees showing only minor discrepancies. The genus Moricandia appears to be formed by two main lineages: the Iberian clade including three species, and the African clade including the four species inhabiting the Southern Mediterranean regions plus M. arvensis . We dated the main evolutionary events of this genus, showing that the origin of the Iberian clade probably occurred after a range expansion during the Messinian period, between 7.25 and 5.33 Ma. In that period, an extensive African-Iberian floral and faunal interchange occurred due to the existence of land bridges between Africa and Europa in what is, at present-days, the Strait of Gibraltar. We have demonstrated that a Spanish population previously ascribed to Rytidocarpus moricandioides is indeed a Moricandia species, and we propose to name it as M. rytidocarpoides sp. nov. In addition, in all the phylogenetic analyses, M. foleyi appeared outside the Moricandia lineage but within the genus Eruca . Therefore, M. foleyi should be excluded from the genus Moricandia and be ascribed, at least provisionally, to the genus Eruca .

Arenal-type pyroclastic flows: A probabilistic event tree risk analysis

NASA Astrophysics Data System (ADS)

Meloy, Anthony F.

2006-09-01

A quantitative hazard-specific scenario-modelling risk analysis is performed at Arenal volcano, Costa Rica for the newly recognised Arenal-type pyroclastic flow (ATPF) phenomenon using an event tree framework. These flows are generated by the sudden depressurisation and fragmentation of an active basaltic andesite lava pool as a result of a partial collapse of the crater wall. The deposits of this type of flow include angular blocks and juvenile clasts, which are rarely found in other types of pyroclastic flow. An event tree analysis (ETA) is a useful tool and framework in which to analyse and graphically present the probabilities of the occurrence of many possible events in a complex system. Four event trees are created in the analysis, three of which are extended to investigate the varying individual risk faced by three generic representatives of the surrounding community: a resident, a worker, and a tourist. The raw numerical risk estimates determined by the ETA are converted into a set of linguistic expressions (i.e. VERY HIGH, HIGH, MODERATE etc.) using an established risk classification scale. Three individually tailored semi-quantitative risk maps are then created from a set of risk conversion tables to show how the risk varies for each individual in different areas around the volcano. In some cases, by relocating from the north to the south, the level of risk can be reduced by up to three classes. While the individual risk maps may be broadly applicable, and therefore of interest to the general community, the risk maps and associated probability values generated in the ETA are intended to be used by trained professionals and government agencies to evaluate the risk and effectively manage the long-term development of infrastructure and habitation. With the addition of fresh monitoring data, the combination of both long- and short-term event trees would provide a comprehensive and consistent method of risk analysis (both during and pre-crisis), and as such, an ETA is considered to be a valuable quantitative decision support tool.

Tree mortality from a short-duration freezing event and global-change-type drought in a Southwestern piñon-juniper woodland, USA

PubMed Central

2014-01-01

This study documents tree mortality in Big Bend National Park in Texas in response to the most acute one-year drought on record, which occurred following a five-day winter freeze. I estimated changes in forest stand structure and species composition due to freezing and drought in the Chisos Mountains of Big Bend National Park using permanent monitoring plot data. The drought killed over half (63%) of the sampled trees over the entire elevation gradient. Significant mortality occurred in trees up to 20 cm diameter (P < 0.05). Pinus cembroides Zucc. experienced the highest seedling and tree mortality (P < 0.0001) (55% of piñon pines died), and over five times as many standing dead pines were observed in 2012 than in 2009. Juniperus deppeana vonSteudal and Quercus emoryi Leibmann also experienced significant declines in tree density (P < 0.02) (30.9% and 20.7%, respectively). Subsequent droughts under climate change will likely cause even greater damage to trees that survived this record drought, especially if such events follow freezes. The results from this study highlight the vulnerability of trees in the Southwest to climatic change and that future shifts in forest structure can have large-scale community consequences. PMID:24949231

The Impact of Reconstruction Methods, Phylogenetic Uncertainty and Branch Lengths on Inference of Chromosome Number Evolution in American Daisies (Melampodium, Asteraceae)

PubMed Central

McCann, Jamie; Stuessy, Tod F.; Villaseñor, Jose L.; Weiss-Schneeweiss, Hanna

2016-01-01

Chromosome number change (polyploidy and dysploidy) plays an important role in plant diversification and speciation. Investigating chromosome number evolution commonly entails ancestral state reconstruction performed within a phylogenetic framework, which is, however, prone to uncertainty, whose effects on evolutionary inferences are insufficiently understood. Using the chromosomally diverse plant genus Melampodium (Asteraceae) as model group, we assess the impact of reconstruction method (maximum parsimony, maximum likelihood, Bayesian methods), branch length model (phylograms versus chronograms) and phylogenetic uncertainty (topological and branch length uncertainty) on the inference of chromosome number evolution. We also address the suitability of the maximum clade credibility (MCC) tree as single representative topology for chromosome number reconstruction. Each of the listed factors causes considerable incongruence among chromosome number reconstructions. Discrepancies between inferences on the MCC tree from those made by integrating over a set of trees are moderate for ancestral chromosome numbers, but severe for the difference of chromosome gains and losses, a measure of the directionality of dysploidy. Therefore, reliance on single trees, such as the MCC tree, is strongly discouraged and model averaging, taking both phylogenetic and model uncertainty into account, is recommended. For studying chromosome number evolution, dedicated models implemented in the program ChromEvol and ordered maximum parsimony may be most appropriate. Chromosome number evolution in Melampodium follows a pattern of bidirectional dysploidy (starting from x = 11 to x = 9 and x = 14, respectively) with no prevailing direction. PMID:27611687

The Impact of Reconstruction Methods, Phylogenetic Uncertainty and Branch Lengths on Inference of Chromosome Number Evolution in American Daisies (Melampodium, Asteraceae).

PubMed

McCann, Jamie; Schneeweiss, Gerald M; Stuessy, Tod F; Villaseñor, Jose L; Weiss-Schneeweiss, Hanna

2016-01-01

Chromosome number change (polyploidy and dysploidy) plays an important role in plant diversification and speciation. Investigating chromosome number evolution commonly entails ancestral state reconstruction performed within a phylogenetic framework, which is, however, prone to uncertainty, whose effects on evolutionary inferences are insufficiently understood. Using the chromosomally diverse plant genus Melampodium (Asteraceae) as model group, we assess the impact of reconstruction method (maximum parsimony, maximum likelihood, Bayesian methods), branch length model (phylograms versus chronograms) and phylogenetic uncertainty (topological and branch length uncertainty) on the inference of chromosome number evolution. We also address the suitability of the maximum clade credibility (MCC) tree as single representative topology for chromosome number reconstruction. Each of the listed factors causes considerable incongruence among chromosome number reconstructions. Discrepancies between inferences on the MCC tree from those made by integrating over a set of trees are moderate for ancestral chromosome numbers, but severe for the difference of chromosome gains and losses, a measure of the directionality of dysploidy. Therefore, reliance on single trees, such as the MCC tree, is strongly discouraged and model averaging, taking both phylogenetic and model uncertainty into account, is recommended. For studying chromosome number evolution, dedicated models implemented in the program ChromEvol and ordered maximum parsimony may be most appropriate. Chromosome number evolution in Melampodium follows a pattern of bidirectional dysploidy (starting from x = 11 to x = 9 and x = 14, respectively) with no prevailing direction.