Going Deeper: Metagenome of a Hadopelagic Microbial Community

The paucity of sequence data from pelagic deep-ocean microbial assemblages has severely restricted molecular exploration of the largest biome on Earth. In this study, an analysis is presented of a large-scale 454-pyrosequencing metagenomic dataset from a hadopelagic environment from 6,000 m depth within the Puerto Rico Trench (PRT). A total of 145 Mbp of assembled sequence data was generated and compared to two pelagic deep ocean metagenomes and two representative surface seawater datasets from the Sargasso Sea. In a number of instances, all three deep metagenomes displayed similar trends, but were most magnified in the PRT, including enrichment in functions for two-component signal transduction mechanisms and transcriptional regulation. Overrepresented transporters in the PRT metagenome included outer membrane porins, diverse cation transporters, and di- and tri-carboxylate transporters that matched well with the prevailing catabolic processes such as butanoate, glyoxylate and dicarboxylate metabolism. A surprisingly high abundance of sulfatases for the degradation of sulfated polysaccharides were also present in the PRT. The most dramatic adaptational feature of the PRT microbes appears to be heavy metal resistance, as reflected in the large numbers of transporters present for their removal. As a complement to the metagenome approach, single-cell genomic techniques were utilized to generate partial whole-genome sequence data from four uncultivated cells from members of the dominant phyla within the PRT, Alphaproteobacteria, Gammaproteobacteria, Bacteroidetes and Planctomycetes. The single-cell sequence data provided genomic context for many of the highly abundant functional attributes identified from the PRT metagenome, as well as recruiting heavily the PRT metagenomic sequence data compared to 172 available reference marine genomes. Through these multifaceted sequence approaches, new insights have been provided into the unique functional attributes present in microbes residing in a deeper layer of the ocean far removed from the more productive sun-drenched zones above

A review of rockfall mechanics and modelling approaches

Abstract: Models can be useful tools to assess the risk posed by rockfall throughout relatively large mountainous areas (>500 km2), in order to improve protection of endangered residential areas and infrastructure. Therefore the purpose of this study was to summarize existing rockfall models and to propose modifications to make them suitable for predicting rockfall at a regional scale. First, the basic mechanics of rockfall are summarized, including knowledge of the main modes of motion: falling, bouncing and rolling. Secondly, existing models are divided in three groups: (1) empirical models, (2) process-based models and (3) Geophysical Information System (GIS)-based models. For each model type its basic principles and ability to predict rockfall runout zones are summarized. The final part is a discussion of how a model for predicting rockfall runout zones at a regional scale should be developed. A GIS-based distribution model is suggested that combines a detailed process-based model and a GIS. Potential rockfall source areas and falltracks are calculated by the GIS component of the model and the rockfall runout zones are calculated by the process-based component. In addition to this model, methods for the estimation of model parameters values at a regional scale have to be developed. Key words: distributed model, GIS, modelling, natural hazard, rockfall.