Abstract: Microbial ecologists can now start digging into the accumulating mountains of metagenomic data to uncover the occurrence of functional genes and their correlations to microbial community members. Limitations and biases in DNA extraction and sequencing technologies impact sequence distributions, and therefore, have to be considered. However, when comparing metagenomes from widely differing environments, these fluctuations have a relatively minor role in microbial community discrimination. As a consequence, any functional gene or species distribution pattern can be compared among metagenomes originating from various environments and projects. In particular, global comparisons would help to define ecosystem specificities, such as involvement and response to climate change (for example, carbon and nitrogen cycle), human health risks (eg, presence of pathogen species, toxin genes and viruses) and biodegradation capacities. Although not all scientists have easy access to high-throughput sequencing technologies, they do have access to the sequences that have been deposited in databases, and therefore, can begin to intensively mine these metagenomic data to generate hypotheses that can be validated experimentally. Information about metabolic functions and microbial species compositions can already be compared among metagenomes from different ecosystems. These comparisons add to our understanding about microbial adaptation and the role of specific microbes in different ecosystems. Concurrent with the rapid growth of sequencing technologies, we have entered a new age of microbial ecology, which will enable researchers to experimentally confirm putative relationships between microbial functions and community structures.

Abstract: Recent glaciological surveys have revealed a significant increase of ice discharge from polar ice caps into the ocean. In parallel, ice flow models have been greatly improved to better reproduce current changes and forecast the future behavior of ice sheets. For these models, surface topography and bedrock elevation are crucial input parameters that largely control the dynamics and the ensuing overall mass balance of the ice sheet. For obvious reasons of inaccessibility, only sparse and uneven bedrock elevation data is available. This raw data is processed to produce Digital Elevation Models (DEMs) on a regular 5 km grid. These DEMs are used to constrain the basal boundary conditions of all ice sheet models. Here, by using a full-Stokes finite element code, we examine the sensitivity of an ice flow model to the accuracy of the bedrock description. In the context of short-term ice sheet forecast, we show that in coastal regions, the bedrock elevation should be known at a resolution of the order of one kilometer. Conversely, a crude description of the bedrock in the interior of the continent does not affect modeling of the ice outflow into the ocean. These findings clearly indicate that coastal regions should be prioritized during future geophysical surveys. They also indicate that a paradigm shift is required to change the current design of DEMs describing the bedrock below the ice sheets: they must give users the opportunity to incorporate high-resolution bedrock elevation data in regions of interest.