Tracing pre-eruptive magma degassing using (Pb-210/Ra-226) disequilibria in the volcanic deposits of the 1980-1986 eruption of Mount St. Helens

Disequilibria between Pb-210 and Ra-226 can be used to trace magma degassing, because the intermediate nuclides, particularly Rn-222, are volatile. Products of the 1980-1986 eruptions of Mount St. Helens have been analysed for (Pb-210/Ra-226). Both excesses and deficits of Pb-210 are encountered suggesting rapid gas transfer. The time scale of diffuse, non-eruptive gas escape prior to 1980 as documented by Pb-210 deficits is on the order of a decade using the model developed by Gauthier and Condomines (Earth Planet. Sci. Lett. 172 (1999) 111-126) for a non-renewed magma chamber and efficient Rn removal. The time required to build-up Pb-210 excess is much shorter (months) as can be observed from steady increases of (Pb-210/Ra-226) with time during 1980-1982. The formation of Pb-210 excess requires both rapid gas transport through the magma and periodic blocking of gas escape routes. Superposed on this time trend is the natural variability of (Pb-210/Ra-226) in a single eruption caused by tapping magma from various depths. The two time scales of gas transport, to create both Pb-210 deficits and Pb-210 excesses, cannot be reconciled in a single event. Rather Pb-210 deficits are associated with pre-eruptive diffuse degassing, while Pb-210 excesses document the more vigorous degassing associated with eruption and recharge of the system. (c) 2006 Elsevier B.V. All rights reserved.

Bayesian estimation of ancestral character states on phylogenies

Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods ( BayesMultiState) is available from the authors.

A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data

We describe a general likelihood-based 'mixture model' for inferring phylogenetic trees from gene-sequence or other character-state data. The model accommodates cases in which different sites in the alignment evolve in qualitatively distinct ways, but does not require prior knowledge of these patterns or partitioning of the data. We call this qualitative variability in the pattern of evolution across sites "pattern-heterogeneity" to distinguish it from both a homogenous process of evolution and from one characterized principally by differences in rates of evolution. We present studies to show that the model correctly retrieves the signals of pattern-heterogeneity from simulated gene-sequence data, and we apply the method to protein-coding genes and to a ribosomal 12S data set. The mixture model outperforms conventional partitioning in both these data sets. We implement the mixture model such that it can simultaneously detect rate- and pattern-heterogeneity. The model simplifies to a homogeneous model or a rate- variability model as special cases, and therefore always performs at least as well as these two approaches, and often considerably improves upon them. We make the model available within a Bayesian Markov-chain Monte Carlo framework for phylogenetic inference, as an easy-to-use computer program.

Simultaneous bridge-localized and mixed-valence character in diruthenium radical cations featuring diethynylaromatic bridging ligands

A series of bimetallic ruthenium complexes [{Ru(dppe)Cp*}2(μ-C≡CArC≡C)] featuring diethynylaromatic bridging ligands (Ar = 1,4-phenylene, 1,4-naphthylene, 9,10-anthrylene) have been prepared and some representative molecular structures determined. A combination of UV–vis–NIR and IR spectroelectrochemical methods and density functional theory (DFT) have been used to demonstrate that one-electron oxidation of compounds [{Ru(dppe)Cp*}2(μ-C≡CArC≡C)](HC≡CArC≡CH = 1,4-diethynylbenzene; 1,4-diethynyl-2,5-dimethoxybenzene; 1,4-diethynylnaphthalene; 9,10-diethynylanthracene) yields solutions containing radical cations that exhibit characteristics of both oxidation of the diethynylaromatic portion of the bridge, and a mixed-valence state. The simultaneous population of bridge-oxidized and mixed-valence states is likely related to a number of factors, including orientation of the plane of the aromatic portion of the bridging ligand with respect to the metal d-orbitals of appropriate π-symmetry.