Extensive halogen-mediated ozone destruction over the tropical Atlantic Ocean

Increasing tropospheric ozone levels over the past 150 years have led to a significant climate perturbation; the prediction of future trends in tropospheric ozone will require a full understanding of both its precursor emissions and its destruction processes. A large proportion of tropospheric ozone loss occurs in the tropical marine boundary layer and is thought to be driven primarily by high ozone photolysis rates in the presence of high concentrations of water vapour. A further reduction in the tropospheric ozone burden through bromine and iodine emitted from open-ocean marine sources has been postulated by numerical models, but thus far has not been verified by observations. Here we report eight months of spectroscopic measurements at the Cape Verde Observatory indicative of the ubiquitous daytime presence of bromine monoxide and iodine monoxide in the tropical marine boundary layer. A year-round data set of co-located in situ surface trace gas measurements made in conjunction with low-level aircraft observations shows that the mean daily observed ozone loss is approximately 50 per cent greater than that simulated by a global chemistry model using a classical photochemistry scheme that excludes halogen chemistry. We perform box model calculations that indicate that the observed halogen concentrations induce the extra ozone loss required for the models to match observations. Our results show that halogen chemistry has a significant and extensive influence on photochemical ozone loss in the tropical Atlantic Ocean boundary layer. The omission of halogen sources and their chemistry in atmospheric models may lead to significant errors in calculations of global ozone budgets, tropospheric oxidizing capacity and methane oxidation rates, both historically and in the future.     

Comparison of the genomes of two Xanthomonas pathogens with differing host specificities

The genus Xanthomonas is a diverse and economically important group of bacterial phytopathogens, belonging to the gamma-subdivision of the Proteobacteria. Xanthomonas axonopodis pv. citri (Xac) causes citrus canker, which affects most commercial citrus cultivars, resulting in significant losses worldwide. Symptoms include canker lesions, leading to abscission of fruit and leaves and general tree decline. Xanthomonas campestris pv. campestris (Xcc) causes black rot, which affects crucifers such as Brassica and Arabidopsis. Symptoms include marginal leaf chlorosis and darkening of vascular tissue, accompanied by extensive wilting and necrosis. Xanthomonas campestris pv. campestris is grown commercially to produce the exopolysaccharide xanthan gum, which is used as a viscosifying and stabilizing agent in many industries. Here we report and compare the complete genome sequences of Xac and Xcc. Their distinct disease phenotypes and host ranges belie a high degree of similarity at the genomic level. More than 80% of genes are shared, and gene order is conserved along most of their respective chromosomes. We identified several groups of strain-specific genes, and on the basis of these groups we propose mechanisms that may explain the differing host specificities and pathogenic processes.     

The geometric combination of Bayesian forecasting models

A nonlinear geometric combination of statistical models is proposed as an alternative approach to the usual linear combination or mixture. Contrary to the linear, the geometric model is closed under the regular exponential family of distributions, as we show. As a consequence, the distribution which results from the combination is unimodal and a single location parameter can be chosen for decision making. In the case of Student t‐distributions (of particular interest in forecasting) the geometric combination can be unimodal under a sufficient condition we have established. A comparative analysis between the geometric and linear combinations of predictive distributions from three Bayesian regression dynamic linear models, in a case of beer sales forecasting in Zimbabwe, shows the geometric model to consistently outperform its linear counterpart as well as its component models. Copyright © 2008 John Wiley & Sons, Ltd.