ASU Scholarship Showcase

Gas seeps emanating from Yanartaş (Chimera), Turkey, have been documented for thousands of years. Active serpentinization produces hydrogen and a range of carbon gases that may provide fuel for life. Here we report a newly discovered, ephemeral fluid seep emanating from a small gas vent at Yanartaş. Fluids and biofilms were sampled at the source and points downstream. We describe site conditions, and provide microbiological data in the form of enrichment cultures, Scanning electron microscopy (SEM), carbon and nitrogen isotopic composition of solids, and PCR screens of nitrogen cycle genes. Source fluids are pH 11.95, with a Ca:Mg of ~200, and sediments under the ignited gas seep measure 60°C. Collectively, these data suggest the fluid is the product of active serpentinization at depth. Source sediments are primarily calcite and alteration products (chlorite and montmorillonite). Downstream, biofilms are mixed with montmorillonite. SEM shows biofilms distributed homogeneously with carbonates. Organic carbon accounts for 60% of the total carbon at the source, decreasing downstream to <15% as inorganic carbon precipitates. δ¹³C ratios of the organic carbon fraction of solids are depleted (−25 to −28‰) relative to the carbonates (−11 to −20‰). We conclude that heterotrophic processes are dominant throughout the surface ecosystem, and carbon fixation may be key down channel. δ¹⁵N ratios ~3‰, and absence of nifH in extracted DNA suggest that nitrogen fixation is not occurring in sediments. However, the presence of narG and nirS at most locations and in enrichments indicates genomic potential for nitrate and nitrite reduction. This small seep with shallow run-off is likely ephemeral, but abundant preserved microterracettes in the outflow and the surrounding area suggest it has been present for some time. This site and others like it present an opportunity for investigations of preserved deep biosphere signatures, and subsurface-surface interactions.

Background: While there is ample evidence for health risks associated with heat and other extreme weather events today, little is known about the impact of weather patterns on population health in preindustrial societies.

Objective: To investigate the impact of weather patterns on population health in Sweden before and during industrialization.

Methods: We obtained records of monthly mortality and of monthly mean temperatures and precipitation for Skellefteå parish, northern Sweden, for the period 1800-1950. The associations between monthly total mortality, as well as monthly mortality due to infectious and cardiovascular diseases, and monthly mean temperature and cumulative precipitation were modelled using a time series approach for three separate periods, 1800−1859, 1860-1909, and 1910-1950.

Results: We found higher temperatures and higher amounts of precipitation to be associated with lower mortality both in the medium term (same month and two-months lag) and in the long run (lag of six months up to a year). Similar patterns were found for mortality due to infectious and cardiovascular diseases. Furthermore, the effect of temperature and precipitation decreased over time.

Conclusions: Higher temperature and precipitation amounts were associated with reduced death counts with a lag of up to 12 months. The decreased effect over time may be due to improvements in nutritional status, decreased infant deaths, and other changes in society that occurred in the course of the demographic and epidemiological transition.

Contribution: The study contributes to a better understanding of the complex relationship between weather and mortality and, in particular, historical weather-related mortality.

Background: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.

Objectives: This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.
Methods: Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature–health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different “trigger points” at which heat-health intervention measures might be activated.

Results: We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22°C) across multiple health events and diagnoses.

Conclusion: Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.

Background: Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat–mortality relationships.
Objectives: We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method.
Methods: Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series.

Results: In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature–mortality relationships were associated with maximum temperature, although mean temperature results were comparable.

Conclusions: There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature–mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum temperatures in most cities we examined, particularly those typically prone to heat-related mortality.

Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7–8.5 at concentrations up to 6.6×10⁶ 16S rRNA gene copies g^-1 wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95%. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology.

Many studies link the compositions of microbial communities to their environments, but the energetics of organism-specific biomass synthesis as a function of geochemical variables have rarely been assessed. We describe a thermodynamic model that integrates geochemical and metagenomic data for biofilms sampled at five sites along a thermal and chemical gradient in the outflow channel of the hot spring known as “Bison Pool” in Yellowstone National Park. The relative abundances of major phyla in individual communities sampled along the outflow channel are modeled by computing metastable equilibrium among model proteins with amino acid compositions derived from metagenomic sequences. Geochemical conditions are represented by temperature and activities of basis species, including pH and oxidation-reduction potential quantified as the activity of dissolved hydrogen. By adjusting the activity of hydrogen, the model can be tuned to closely approximate the relative abundances of the phyla observed in the community profiles generated from BLAST assignments. The findings reveal an inverse relationship between the energy demand to form the proteins at equal thermodynamic activities and the abundance of phyla in the community. The distance from metastable equilibrium of the communities, assessed using an equation derived from energetic considerations that is also consistent with the information-theoretic entropy change, decreases along the outflow channel. Specific divergences from metastable equilibrium, such as an underprediction of the relative abundances of phototrophic organisms at lower temperatures, can be explained by considering additional sources of energy and/or differences in growth efficiency. Although the metabolisms used by many members of these communities are driven by chemical disequilibria, the results support the possibility that higher-level patterns of chemotrophic microbial ecosystems are shaped by metastable equilibrium states that depend on both the composition of biomass and the environmental conditions.

We have constructed a conceptual model of biogeochemical cycles and metabolic and microbial community shifts within a hot spring ecosystem via coordinated analysis of the “Bison Pool” (BP) Environmental Genome and a complementary contextual geochemical dataset of ∼75 geochemical parameters. 2,321 16S rRNA clones and 470 megabases of environmental sequence data were produced from biofilms at five sites along the outflow of BP, an alkaline hot spring in Sentinel Meadow (Lower Geyser Basin) of Yellowstone National Park. This channel acts as a >22 m gradient of decreasing temperature, increasing dissolved oxygen, and changing availability of biologically important chemical species, such as those containing nitrogen and sulfur. Microbial life at BP transitions from a 92°C chemotrophic streamer biofilm community in the BP source pool to a 56°C phototrophic mat community. We improved automated annotation of the BP environmental genomes using BLAST-based Markov clustering. We have also assigned environmental genome sequences to individual microbial community members by complementing traditional homology-based assignment with nucleotide word-usage algorithms, allowing more than 70% of all reads to be assigned to source organisms. This assignment yields high genome coverage in dominant community members, facilitating reconstruction of nearly complete metabolic profiles and in-depth analysis of the relation between geochemical and metabolic changes along the outflow. We show that changes in environmental conditions and energy availability are associated with dramatic shifts in microbial communities and metabolic function. We have also identified an organism constituting a novel phylum in a metabolic “transition” community, located physically between the chemotroph- and phototroph-dominated sites. The complementary analysis of biogeochemical and environmental genomic data from BP has allowed us to build ecosystem-based conceptual models for this hot spring, reconstructing whole metabolic networks in order to illuminate community roles in shaping and responding to geochemical variability.

Background: Most excess deaths that occur during extreme hot weather events do not have natural heat recorded as an underlying or contributing cause. This study aims to identify the specific individuals who died because of hot weather using only secondary data. A novel approach was developed in which the expected number of deaths was repeatedly sampled from all deaths that occurred during a hot weather event, and compared with deaths during a control period. The deaths were compared with respect to five factors known to be associated with hot weather mortality. Individuals were ranked by their presence in significant models over 100 trials of 10,000 repetitions. Those with the highest rankings were identified as probable excess deaths. Sensitivity analyses were performed on a range of model combinations. These methods were applied to a 2009 hot weather event in greater Vancouver, Canada.

Results: The excess deaths identified were sensitive to differences in model combinations, particularly between univariate and multivariate approaches. One multivariate and one univariate combination were chosen as the best models for further analyses. The individuals identified by multiple combinations suggest that marginalized populations in greater Vancouver are at higher risk of death during hot weather.

Conclusions: This study proposes novel methods for classifying specific deaths as expected or excess during a hot weather event. Further work is needed to evaluate performance of the methods in simulation studies and against clinically identified cases. If confirmed, these methods could be applied to a wide range of populations and events of interest.

Uncovering the chemical and physical links between natural environments and microbial communities is becoming increasingly amenable owing to geochemical observations and metagenomic sequencing. At the hot spring known as Bison Pool in Yellowstone National Park, the cooling of the water in the outflow channel is associated with an increase in oxidation potential estimated from multiple field-based measurements. Representative groups of proteins whose sequences were derived from metagenomic data also exhibit an increase in average oxidation state of carbon in the protein molecules with distance from the hot-spring source. The energetic requirements of reactions to form selected proteins used in the model were computed using amino-acid group additivity for the standard molal thermodynamic properties of the proteins, and the relative chemical stabilities of the proteins were investigated by varying temperature, pH and oxidation state, expressed as activity of dissolved hydrogen. The relative stabilities of the proteins were found to track the locations of the sampling sites when the calculations included a function for hydrogen activity that increases with temperature and is higher, or more reducing, than values consistent with measurements of dissolved oxygen, sulfide and oxidation-reduction potential in the field. These findings imply that spatial patterns in the amino acid compositions of proteins can be linked, through energetics of overall chemical reactions representing the formation of the proteins, to the environmental conditions at this hot spring, even if microbial cells maintain considerably different internal conditions. Further applications of the thermodynamic calculations are possible for other natural microbial ecosystems.

Explosive extrusion of cold material from the interior of icy bodies, or cryovolcanism, has been observed on Enceladus and, perhaps, Europa, Triton, and Ceres. It may explain the observed evidence for a young surface on Charon (Pluto’s surface is masked by frosts). Here, we evaluate prerequisites for cryovolcanism on dwarf planet-class Kuiper belt objects (KBOs). We first review the likely spatial and temporal extent of subsurface liquid, proposed mechanisms to overcome the negative buoyancy of liquid water in ice, and the volatile inventory of KBOs. We then present a new geochemical equilibrium model for volatile exsolution and its ability to drive upward crack propagation. This novel approach bridges geophysics and geochemistry, and extends geochemical modeling to the seldom-explored realm of liquid water at subzero temperatures. We show that carbon monoxide (CO) is a key volatile for gas-driven fluid ascent; whereas CO₂ and sulfur gases only play a minor role. N₂, CH₄, and H₂ exsolution may also drive explosive cryovolcanism if hydrothermal activity produces these species in large amounts (a few percent with respect to water). Another important control on crack propagation is the internal structure: a hydrated core makes explosive cryovolcanism easier, but an undifferentiated crust does not. We briefly discuss other controls on ascent such as fluid freezing on crack walls, and outline theoretical advances necessary to better understand cryovolcanic processes. Finally, we make testable predictions for the 2015 New Horizons flyby of the Pluto-Charon system.