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Diffuse degassing through the soil is commonly observed in volcanic areas and monitoring of carbon dioxide flux at the surface can provide a safe and effective way to infer the state of activity of the volcanic system. Continuous measurement stations are often installed on active volcanoes such as Furnas (Azores archipelago), which features low temperature fumaroles, hot and cold CO2 rich springs, and several diffuse degassing areas. As in other volcanoes, fluxes measured at Furnas are often correlated with environmental variables, such as air temperature or barometric pressure, with daily and seasonal cycles that become more evident when gas emission is low. In this work, we study how changes in air temperature and barometric pressure may affect the gas emission through the soil. The TOUGH2 geothermal simulator was used to simulate the gas propagation through the soil as a function of fluctuating atmospheric conditions. Then, a dual parameters study was performed to assess how the rock permeability and the gas source properties affect the resulting fluxes. Numerical results are in good agreement with the observed data at Furnas, and show that atmospheric variables may cause the observed daily cycles in CO2 fluxes. The observed changes depend on soil permeability and on the pressure driving the upward flux. Key Points Modeling the effects of atmospheric variables on surface diffuse degassing Correlation between atmospheric variables and carbon dioxide fluxes Atmospheric effects as possible indicators of changes in system properties

Inferno Crater Lake, Waimangu, one of the largest hot springs in New Zealand, displays vigorous cyclic behavior in lake level and temperature. It provides a natural small‐scale laboratory for investigating the geo‐electrical signature of fluid flows. We measured self‐potential and electrical resistivity to see whether the huge variations of fluid volume, approximately 60,000 m3 during a mean cycle period of 40 days, could be detected. Electrical resistivity measurements revealed spectacular changes over time, with the medium becoming more conductive as the lake receded. This result is consistent with analog models, where the vapor phase is replaced by liquid at recession. The self‐potential survey did not detect temporal changes related to fluid movements. This can be explained by the pH of the pore water (∼2.3), which is close to the point of zero charge of silica.

Continuous monitoring of volcanic gas emissions is crucial for understanding volcanic activity and potential eruptions. However, emissions of volcanic gases underwater are infrequently studied or quantified. This study explores the potential of Distributed Acoustic Sensing (DAS) technology to monitor underwater volcanic degassing. DAS converts fiber-optic cables into high-resolution vibration recording arrays, providing measurements at unprecedented spatio-temporal resolution. We conducted an experiment at Laacher See volcano in Germany, immersing a fiber-optic cable in the lake and interrogating it with a DAS system. We detected and analyzed numerous acoustic signals that we associated with bubble emissions in different lake areas. Three types of text-book bubbles exhibiting characteristic waveforms are all found from our detections, indicating different nucleation processes and bubble sizes. Using clustering algorithms, we classified bubble events into four distinct clusters based on their temporal and spectral characteristics. The temporal distribution of the events provided insights into the evolution of gas seepage patterns. This technology has the potential to revolutionize underwater degassing monitoring and provide valuable information for studying volcanic processes and estimating gas emissions. Furthermore, DAS can be applied to other applications, such as monitoring underwater carbon capture and storage operations or methane leaks associated with climate change.

Our knowledge of species and functional composition of the human gut microbiome is rapidly increasing, but it is still based on very few cohorts and little is known about variation across the world. By combining 22 newly sequenced faecal metagenomes of individuals from four countries with previously published data sets, here we identify three robust clusters (referred to as enterotypes hereafter) that are not nation or continent specific. We also confirmed the enterotypes in two published, larger cohorts, indicating that intestinal microbiota variation is generally stratified, not continuous. This indicates further the existence of a limited number of well-balanced host–microbial symbiotic states that might respond differently to diet and drug intake. The enterotypes are mostly driven by species composition, but abundant molecular functions are not necessarily provided by abundant species, highlighting the importance of a functional analysis to understand microbial communities. Although individual host properties such as body mass index, age, or gender cannot explain the observed enterotypes, data-driven marker genes or functional modules can be identified for each of these host properties. For example, twelve genes significantly correlate with age and three functional modules with the body mass index, hinting at a diagnostic potential of microbial markers. Seeking order among our gut microbes The human gut microbiota consists of a huge number of species and varies greatly between individuals. A comparative metagenomic analysis of the human gut microbiomes of 39 individuals from 6 countries shows that despite this diversity, the microbiota composition can be classified into at least 3 distinct groups, or enterotypes. The enterotypes contain functional markers that correlate with individual features such as age and body mass index, a feature that may be of use in the diagnosis of numerous human disorders such as colorectal cancer and diabetes.