Radioecological and geochemical peculiarities of cryoconite on Novaya Zemlya glaciers.

In recent years, cryoconite has received growing attention from a radioecological point of view, since several studies have shown that this material is extremely efficient in accumulating natural and anthropogenic radionuclides. The Novaya Zemlya Archipelago (Russian Arctic) hosts the second largest glacial system in the Arctic. From 1957 to 1962, numerous atmospheric nuclear explosions were conducted at Novaya Zemlya, but to date, very little is known about the radioecology of its ice cap. Analysis of radionuclides and other chemical elements in cryoconite holes on Nalli Glacier reveals the presence of two main zones at different altitudes that present different radiological features. The first zone is 130-210 m above sea level (a.s.l.), has low radioactivity, high concentrations of lithophile elements and a chalcophile content close to that of upper continental crust clarkes. The second zone (220-370 m a.s.l.) is characterized by high activity levels of radionuclides and "inversion" of geochemical behaviour with lower concentrations of lithophiles and higher chalcophiles. In the upper part of this zone (350-370 m a.s.l.), 137Cs activity reaches the record levels for Arctic cryoconite (5700-8100 Bq/kg). High levels of Sn, Sb, Bi and Ag, significantly exceeding those of upper continental crust clarkes, also appear here. We suggest that a buried layer of contaminated ice that formed during atmospheric nuclear tests serves as a local secondary source of radionuclide contamination. Its melting is responsible for the formation of this zone.

Computing the joint distribution of the total tree length across loci in populations with variable size.

In recent years, a number of methods have been developed to infer complex demographic histories, especially historical population size changes, from genomic sequence data. Coalescent Hidden Markov Models have proven to be particularly useful for this type of inference. Due to the Markovian structure of these models, an essential building block is the joint distribution of local genealogical trees, or statistics of these genealogies, at two neighboring loci in populations of variable size. Here, we present a novel method to compute the marginal and the joint distribution of the total length of the genealogical trees at two loci separated by at most one recombination event for samples of arbitrary size. To our knowledge, no method to compute these distributions has been presented in the literature to date. We show that they can be obtained from the solution of certain hyperbolic systems of partial differential equations. We present a numerical algorithm, based on the method of characteristics, that can be used to efficiently and accurately solve these systems and compute the marginal and the joint distributions. We demonstrate its utility to study the properties of the joint distribution. Our flexible method can be straightforwardly extended to handle an arbitrary fixed number of recombination events, to include the distributions of other statistics of the genealogies as well, and can also be applied in structured populations.

Motile Geobacter dechlorinators migrate into a model source zone of trichloroethene dense non-aqueous phase liquid: experimental evaluation and modeling.

Microbial migration towards a trichloroethene (TCE) dense non-aqueous phase liquid (DNAPL) could facilitate the bioaugmentation of TCE DNAPL source zones. This study characterized the motility of the Geobacter dechlorinators in a TCE to cis-dichloroethene dechlorinating KB-1(™) subculture. No chemotaxis towards or away from TCE was found using an agarose in-plug bridge method. A second experiment placed an inoculated aqueous layer on top of a sterile sand layer and showed that Geobacter migrated several centimeters in the sand layer in just 7days. A random motility coefficient for Geobacter in water of 0.24±0.02cm(2)·day(-1) was fitted. A third experiment used a diffusion-cell setup with a 5.5cm central sand layer separating a DNAPL from an aqueous top layer as a model source zone to examine the effect of random motility on TCE DNAPL dissolution. With top layer inoculation, Geobacter quickly colonized the sand layer, thereby enhancing the initial TCE DNAPL dissolution flux. After 19days, the DNAPL dissolution enhancement was only 24% lower than with an homogenous inoculation of the sand layer. A diffusion-motility model was developed to describe dechlorination and migration in the diffusion-cells. This model suggested that the fast colonization of the sand layer by Geobacter was due to the combination of random motility and growth on TCE.

parallelMCMCcombine: an R package for bayesian methods for big data and analytics.

Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed for data sets that are large only due to large sample sizes. These methods partition big data sets into subsets and perform independent Bayesian Markov chain Monte Carlo analyses on the subsets. The methods then combine the independent subset posterior samples to estimate a posterior density given the full data set. These approaches were shown to be effective for Bayesian models including logistic regression models, Gaussian mixture models and hierarchical models. Here, we introduce the R package parallelMCMCcombine which carries out four of these techniques for combining independent subset posterior samples. We illustrate each of the methods using a Bayesian logistic regression model for simulation data and a Bayesian Gamma model for real data; we also demonstrate features and capabilities of the R package. The package assumes the user has carried out the Bayesian analysis and has produced the independent subposterior samples outside of the package. The methods are primarily suited to models with unknown parameters of fixed dimension that exist in continuous parameter spaces. We envision this tool will allow researchers to explore the various methods for their specific applications and will assist future progress in this rapidly developing field.