The Bioburden and Ionic Composition of Hypersaline Lake Ices: Novel Habitats on Earth and Their Astrobiological Implications

We present thermophysical, biological, and chemical observations of ice and brine samples from five compositionally diverse hypersaline lakes in British Columbia's interior plateau. Possessing a spectrum of magnesium, sodium, sulfate, carbonate, and chloride salts, these low-temperature high-salinity lakes are analogs for planetary ice-brine environments, including the ice shells of Europa and Enceladus and ice-brine systems on Mars. As such, understanding the thermodynamics and biogeochemistry of these systems can provide insights into the evolution, habitability, and detectability of high-priority astrobiology targets. We show that biomass is typically concentrated in a layer near the base of the ice cover, but that chemical and biological impurities are present throughout the ice. Coupling bioburden, ionic concentration, and seasonal temperature measurements, we demonstrate that impurity entrainment in the ice is directly correlated to ice formation rate and parent fluid composition. We highlight unique phenomena, including brine supercooling, salt hydrate precipitation, and internal brine layers in the ice cover, important processes to be considered for planetary ice-brine environments. These systems can be leveraged to constrain the distribution, longevity, and habitability of low-temperature solar system brines-relevant to interpreting spacecraft data and planning future missions in the lens of both planetary exploration and planetary protection.

Traditional and novel time-series approaches reveal submarine groundwater discharge dynamics under baseline and extreme event conditions

Groundwater is a vital resource for humans and groundwater dependent ecosystems. Coastal aquifers and submarine groundwater discharge (SGD), both influenced by terrestrial and marine forces, are increasingly affected by climate variations and sea-level rise. Despite this, coastal groundwater resources and discharge are frequently poorly constrained, limiting our understanding of aquifer responses to external forces. We apply traditional and novel time-series approaches using an SGD dataset of previously unpublished resolution and duration, to analyze the dependencies between precipitation, groundwater level, and SGD at a model site (Kīholo Bay, Hawai'i). Our objectives include (1) determining the relative contribution of SGD drivers over tidal and seasonal periods, (2) establishing temporal relationships and thresholds of processes influencing SGD, and (3) evaluating the impacts of anomalous events, such as tropical storms, on SGD. This analysis reveals, for example, that precipitation is only a dominant influence during wet periods, and otherwise tides and waves dictate the dynamics of SGD. It also provides time lags between intense storm events and higher SGD rates, as well as thresholds for precipitation, wave height and tides affecting SGD. Overall, we demonstrate an approach for modeling a hydrological system while elucidating coastal aquifer and SGD response in unprecedented detail.

Ice needles weave patterns of stones in freezing landscapes

Patterned ground, defined by the segregation of stones in soil according to size, is one of the most strikingly self-organized characteristics of polar and high-alpine landscapes. The presence of such patterns on Mars has been proposed as evidence for the past presence of surface liquid water. Despite their ubiquity, the dearth of quantitative field data on the patterns and their slow dynamics have hindered fundamental understanding of the pattern formation mechanisms. Here, we use laboratory experiments to show that stone transport is strongly dependent on local stone concentration and the height of ice needles, leading effectively to pattern formation driven by needle ice activity. Through numerical simulations, theory, and experiments, we show that the nonlinear amplification of long wavelength instabilities leads to self-similar dynamics that resemble phase separation patterns in binary alloys, characterized by scaling laws and spatial structure formation. Our results illustrate insights to be gained into patterns in landscapes by viewing the pattern formation through the lens of phase separation. Moreover, they may help interpret spatial structures that arise on diverse planetary landscapes, including ground patterns recently examined using the rover Curiosity on Mars.

Trends in seasonal warm anomalies across the contiguous United States: Contributions from natural climate variability

Many studies have shown the importance of anthropogenic greenhouse gas emissions in contributing to observed upward trends in the occurrences of temperature extremes over the U.S. However, few studies have investigated the contributions of internal variability in the climate system to these observed trends. Here we use daily maximum temperature time series from the North American Land Data Assimilation System Phase 2 (NLDAS-2) dataset to identify trends in seasonal warm anomalies over the contiguous U.S. in the three most recent decades and explore their relationships to low-frequency modes of internal climate variability. The results reveal substantial upward trends in the frequency of warm anomalies in all seasons and in all regions of the U.S., except for portions of the Intermountain West in winter where significant downward trends occur. The strengths and regional coverage of the trends, however, differ considerably by season. These trends can be explained, in part, by the large-scale anomalous atmospheric circulations associated with low-frequency sea-surface temperature oscillations characterized by the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The association between the upward trends in the seasonal warm anomalies and PDO and AMO is further confirmed by the century-long (1871–2012) Twentieth Century Reanalysis dataset.

Ozone trends and their relationship to characteristic weather patterns

Local trends in ozone concentration may differ by meteorological conditions. Furthermore, the trends occurring at the extremes of the Ozone distribution are often not reported even though these may be very different than the trend observed at the mean or median and they may be more relevant to health outcomes. Classify days of observation over a 16-year period into broad categories that capture salient daily local weather characteristics. Determine the rate of change in mean and median O3 concentrations within these different categories to assess how concentration trends are impacted by daily weather. Further examine if trends vary for observations in the extremes of the O3 distribution. We used k-means clustering to categorize days of observation based on the maximum daily temperature, standard deviation of daily temperature, mean daily ground level wind speed, mean daily water vapor pressure and mean daily sea-level barometric pressure. The five cluster solution was determined to be the appropriate one based on cluster diagnostics and cluster interpretability. Trends in cluster frequency and pollution trends within clusters were modeled using Poisson regression with penalized splines as well as quantile regression. There were five characteristic groupings identified. The frequency of days with large standard deviations in hourly temperature decreased over the observation period, whereas the frequency of warmer days with smaller deviations in temperature increased. O3 trends were significantly different within the different weather groupings. Furthermore, the rate of O3 change for the 95th percentile and 5th percentile was significantly different than the rate of change of the median for several of the weather categories.We found that O3 trends vary between different characteristic local weather patterns. O3 trends were significantly different between the different weather groupings suggesting an important interaction between changes in prevailing weather conditions and O3 concentration.

Weather and triggering of ventricular arrhythmias in patients with implantable cardioverter-defibrillators

Outdoor ambient weather has been hypothesized to be responsible for the seasonal distribution of cardiac arrhythmias. Because people spend most of their time indoors, we hypothesized that weather-related arrhythmia risk would be better estimated using an indoor measure or an outdoor measure that correlates well with indoor conditions, such as absolute humidity. The clinical records of 203 patients in eastern Massachusetts, USA, with an implantable cardioverter-defibrillator were abstracted for arrhythmias between 1995 and 2002. We used case-crossover methods to examine the association between weather and ventricular arrhythmia (VA). Among 84 patients who experienced 787 VAs, lower estimated indoor temperature (odds ratio (OR)=1.16, 95% confidence interval (CI) 1.05-1.27 for a 1 °C decrease in the 24-h average) and lower absolute humidity (OR=1.06, 95% CI 1.03-1.08 for a 0.5 g/m(3) decrease in the 96-h average) were associated with increased risk. Lower outdoor temperature increased risk only in warmer months, likely attributable to the poor correlation between outdoor and indoor temperature during cooler months. These results suggest that lower temperature and drier air are associated with increased risk of VA onset among implantable cardioverter-defibrillator patients.

Rich and cold: diversity, distribution and drivers of fungal communities in patterned-ground ecosystems of the North American Arctic

Fungi are abundant and functionally important in the Arctic, yet comprehensive studies of their diversity in relation to geography and environment are not available. We sampled soils in paired plots along the North American Arctic Transect (NAAT), which spans all five bioclimatic subzones of the Arctic. Each pair of plots contrasted relatively bare, cryoturbated patterned-ground features (PGFs) and adjacent vegetated between patterned-ground features (bPGFs). Fungal communities were analysed via sequencing of 7834 ITS-LSU clones. We recorded 1834 OTUs - nearly half the fungal richness previously reported for the entire Arctic. These OTUs spanned eight phyla, 24 classes, 75 orders and 120 families, but were dominated by Ascomycota, with one-fifth belonging to lichens. Species richness did not decline with increasing latitude, although there was a decline in mycorrhizal taxa that was offset by an increase in lichen taxa. The dominant OTUs were widespread even beyond the Arctic, demonstrating no dispersal limitation. Yet fungal communities were distinct in each subzone and were correlated with soil pH, climate and vegetation. Communities in subzone E were distinct from the other subzones, but similar to those of the boreal forest. Fungal communities on disturbed PGFs differed significantly from those of paired stable areas in bPGFs. Indicator species for PGFs included lichens and saprotrophic fungi, while bPGFs were characterized by ectomycorrhizal and pathogenic fungi. Our results suggest that the Arctic does not host a unique mycoflora, while Arctic fungi are highly sensitive to climate and vegetation, with potential to migrate rapidly as global change unfolds.

Stone circles: form and soil kinematics

Distinct surface patterns are ubiquitous and diverse in soils of polar and alpine regions, where the ground temperature oscillates about 0°C. They constitute some of the most striking examples of clearly visible, abiotic self-organization in nature. This paper outlines the interplay of frost-related physical processes that produce these patterns spontaneously and presents unique data documenting subsurface soil rotational motion and surface displacement spanning 20 years in well-developed circles of soil outlined by gravel ridges. These sorted circles are particularly attractive research targets for a number of reasons that provide focus for this paper: (i) their exceptional geometric regularity captures the attention of any observer; (ii) they are currently forming and evolving, hence the underlying processes can be monitored readily, especially because they are localized near the ground surface on a scale of metres, which facilitates comprehensive characterization; and (iii) a recent, highly successful numerical model of sorted circle development helps to draw attention to particular field observations that can be used to assess the model, its assumptions and parameter choices, and to the considerable potential for synergetic field and modelling studies.