Genetic composition, genetic diversity, and small-scale environmental variation matter for the experimental reintroduction of a rare plant

Aims Reintroduction has become an important tool for the management of endangered plant species. We tested the little-explored effects of small-scale environmental variation, genotypic composition (i.e. identity of genotypes), and genotypic diversity on the population survival of the regionally rare clonal plant Ranunculus reptans. For this species of periodically inundated lakeshores genetic differentiation had been reported between populations and between short-flooded and long-flooded microsites within populations.Methods We established 306 experimental test populations at a previously unoccupied lake shore, comprising either monocultures of 32 genotypes, mixtures of genotypes within populations or mixtures of genotypes between populations. In 2000, three years after planting out at the experimental site, a long-lasting flood caused the death of half of the experimental populations. In 2003, an extreme drought resulted in the lowest summer water levels ever measured.Important findings Despite these climatic extremes, 27 of the established populations survived until the end of the experiment in December 2003. The success of experimental populations largely differed between microsites. Moreover, the success of genotype monocultures depended on genotype and source population. Genetic differentiation between microsites played a minor role for the success of reintroduction. After the flood, populations planted with genotypes from different source populations increased in abundance, whereas populations with genotypes from single source populations and genotype monocultures decreased. We conclude that sources for reintroductions need to be selected carefully. Moreover, mixtures of plants from different populations appear to be the best choice for successful reintroduction, at least in unpredictably varying environments.

Comprehensive environmental study in high risk areas for cancer patients comparing air and water Aspergillus species samples

Background. Nosocomial invasive aspergillosis (a highly fatal disease) is an increasing problem for immunocompromised patients. Aspergillus spp. can be transmitted via air (most commonly) and by water. ^ The hypothesis for this prospective study was that there is an association between patient occupancy, housekeeping practices, patients, visitors, and Aspergillus spp. loading. Rooms were sampled as not terminally cleaned (dirty) and terminally cleaned (clean). The secondary hypothesis was that Aspergillus spp. positive samples collected from more than one sampling location within the same patient room represent the same isolate. ^ Methods. Between April and October 2004, 2873 environmental samples (713 air, 607 water, 1256 surface and 297 spore traps) were collected in and around 209 “clean” and “dirty” patient rooms in a large cancer center hospital. Water sources included aerosolized water from patient room showerheads, sinks, drains, and toilets. Bioaerosol samples were from the patient room and from the running shower, flushing toilet, and outside the building. The surface samples included sink and shower drains, showerheads, and air grills. Aspergillus spp. positive samples were also sent for PCR, molecular typing (n = 89). ^ Results. All water samples were negative for Aspergillus spp. There were a total of 130 positive culturable samples (5.1%). The predominant species found was Aspergillus niger. Of the positive culturable samples, 106 (14.9%) were air and 24 (3.8%) were surface. There were 147 spore trap samples, and 49.5% were positive for Aspergillus/Penicillum spp. Of the culturable positive samples sent for PCR, 16 were indistinguishable matches. There was no significant relationship between air and water samples and positive samples from the same room. ^ Conclusion. Primarily patients, visitors and staff bring the Aspergillus spp. into the hospital. The high number of A. niger samples suggests the spores are entering the hospital from outdoors. Eliminating the materials brought to the patient floors from the outside, requiring employees, staff, and visitors to wear cover up over their street clothes, and improved cleaning procedures could further reduce positive samples. Mold strains change frequently; it is probably more significant to understand pathogenicity of viable spores than to commit resources on molecular strain testing on environmental samples alone. ^

Using GIS methods to assess the occurrence of neural tube defect births by residential proximity at conception to hazardous waste sites

In the United States, approximately 4,000 pregnancies each year are affected by the two most common birth defects, spina bifida and anencephaly. Studies have shown that exposure to environmental chemicals before and after conception may adversely affect reproduction by inducing cell death or dysfunction, which leads to infertility, fetal loss, lowered weight at birth, or birth anomalies in the offspring. The objective of the study was to evaluate the relationship between Neural Tube Defect births and residence at conception in proximity to hazardous waste sites in the Texas-Mexico border region between 1993 and 2000. ^ The study design was a nested matched case-control and utilized secondary data from a project, “The role of chemical and biological factors in the etiology of neural tube birth defects births along the Texas-Mexico Border” (Irina Cech, Principal Investigator). Geographic Information Systems (GIS) database methods were used to compare Neural Tube Defects cases to controls on status of conception residence occurring within a one-mile radius from hazardous waste sites, as compared to conception residence further away. Information on the exposures was obtained from the OnTarget Database and Environment Protection Agency website. Conditional logistic regression was used for the matched case-control study to investigate the relationship between an outcome of being a case or a control and proximity to hazardous waste sites. ^ The result of the study showed a 36 percent non-significant increased risk of having an NTD birth associated with maternal proximity to abandoned hazardous waste sites (95% CI = 0.62–3.02). In addition, there was a 24% non-significant elevated risk of having an NTD birth when living in proximity to air pollutant sites than when living further away (95% CI = 0.67–2.32). Although this study did not find statistically significant associations, it will expand on the existing knowledge of the relationship between NTD and proximity to hazardous waste sites. ^

Psychosocial and environmental predictors of calcium intake, physical activity and bone health among adolescent girls

Objectives. The purpose of this study was to identify the psychosocial and environmental predictors and the pathways they use to influence calcium intake, physical activity and bone health among adolescent girls. Methods. A secondary data analysis using a cross-sectional and longitudinal study design was implemented to examine the associations of interest. Data from the Incorporating More Physical Activity and Calcium in Teens (IMPACT) study collected in 2001-2003 were utilized for the analyses. IMPACT was a 1½ year nutrition and physical activity intervention study conducted among 718 middle-school girls in central Texas. Hierarchical regression modeling and Structural Equation Modeling (SEM) were used to determine the psychosocial predictors of calcium intake, physical activity and bone health at baseline. Hierarchical regression was used to determine if psychosocial factors at baseline were significant predictors of calcium intake and physical activity at follow-up. Data was adjusted for included BMI, lactose intolerance, ethnicity, menarchal status, intervention and participation in 7th grade PE/athletics. Results. Results of the baseline regression analysis revealed that calcium self-efficacy and milk availability at home were the strongest predictors of calcium intake. Friend engagement in physical activity, physical activity self-efficacy and participation in sports teams were the strongest predictors of physical activity. Finally, physical activity outcome expectations, social support and participation in sports teams were significant predictors of stiffness index at baseline. Results of the baseline SEM path analysis found that outcome expectations and milk availability at home directly influenced calcium intake. Knowledge and calcium self-efficacy indirectly influenced calcium intake with outcome expectations as the mediator. Physical activity self-efficacy and social support had significant direct and indirect influence on physical activity with participation in sports teams as the mediator. Participation in sports teams had a direct effect on both physical activity and stiffness index. Results of regression analysis for baseline predicting follow-up showed that participation in sports teams, self-efficacy, outcome expectations and social support at baseline were significant predictors of physical activity at follow-up. Conclusion. Results of this study reinforce the relevance of addressing both, psychosocial and environmental factors which are critical when developing interventions to improve bone health among adolescent girls. ^

An examination of the Gonorrhea Cases & Places study: An analysis of the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory as it relates to risky sexual behavior in African American adults

Objective. The purpose of the study is to provide a holistic depiction of behavioral & environmental factors contributing to risky sexual behaviors among predominantly high school educated, low-income African Americans residing in urban areas of Houston, TX utilizing the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory. ^ Methods. A cross-sectional study was conducted via questionnaires among 215 Houston area residents, 149 were women and 66 were male. Measures used to assess behaviors of the population included a history of homelessness, use of crack/cocaine among several other illicit drugs, the type of sexual partner, age of participant, age of most recent sex partner, whether or not participants sought health care in the last 12 months, knowledge of partner's other sexual activities, symptoms of depression, and places where partner's were met. In an effort to determine risk of sexual encounters, a risk index employing the variables used to assess condom use was created categorizing sexual encounters as unsafe or safe. ^ Results. Variables meeting the significance level of p<.15 for the bivariate analysis of each theory were entered into a binary logistic regression analysis. The block for each theory was significant, suggesting that the grouping assignments of each variable by theory were significantly associated with unsafe sexual behaviors. Within the regression analysis, variables such as sex for drugs/money, low income, and crack use demonstrated an effect size of ≥±1, indicating that these variables had a significant effect on unsafe sexual behavioral practices. ^ Conclusions. Variables assessing behavior and environment demonstrated a significant effect when categorized by relation to designated theories. ^

Environmental sustainability and the human element: Decision making in National Cancer Institute-designated cancer centers and Practice Greenhealth subscribing institutions

Background. Various aspects of sustainability have taken root in the hospital environment; however, decisions to pursue sustainable practices within the framework of a master plan are not fully developed in National Cancer Institute (NCI) -designated cancer centers and subscribing institutions to the Practice Greenhealth (PGH) listserv.^ Methods. This cross sectional study was designed to identify the organizational characteristics each study group pursed to implement sustainability practices, describe the barriers they encountered and reasons behind their choices for undertaking certain sustainability practices. A web-based questionnaire was pilot tested, and then sent out to 64 NCI-designated cancer centers and 1638 subscribing institutions to the PGH listserv.^ Results. Complete responses were received from 39 NCI-designated cancer centers and 58 subscribing institutions to the PGH listserv. NCI-designated cancer centers reported greater progress in integrating sustainability criteria into design and construction projects than hospitals of institutions subscribing to the PHG listserv (p-value = <0.05). Statistically significant differences were also identified between these two study groups in undertaking work life options, conducting energy usage assessments, developing energy conservation and optimization plans, implementing solid waste and hazardous waste minimization programs, using energy efficient vehicles and reporting sustainability progress to external stakeholders. NCI-designated cancer centers were further along in implementing these programs (p-value = <0.05). In comparing the self-identified NCI-designated cancer centers to centers that indicated they were both and NCI and PGH, the later had made greater progress in using their collective buying power to pursue sustainable purchasing practices within the medical community (p-value = <0.05). In both study groups, recycling programs were well developed.^ Conclusions. Employee involvement was viewed as the most important reason for both study groups to pursue recycling initiatives and incorporated environmental criteria into purchasing decisions. A written sustainability commitment did not readily translate into a high percentage that had developed a sustainability master plan. Coordination of sustainability programs through a designated sustainability professional was not being undertaken by a large number of institutions within each study group. This may be due to the current economic downturn or management's attention to the emerging health care legislation being debated in congress. ^ Lifecycle assessments, an element of a carbon footprint, are seen as emerging areas of opportunity for health care institutions that can be used to evaluate the total lifecycle costs of products and services.^

A comparative review of water disinfection methods appropriate for developing countries and their efficacy, cost-efficiency, and usability

Developing countries are heavily burdened by limited access to safe drinking water and subsequent water-related diseases. Numerous water treatment interventions combat this public health crisis, encompassing both traditional and less-common methods. Of these, water disinfection serves as an important means to provide safe drinking water. Existing literature discusses a wide range of traditional treatment options and encourages the use of multi-barrier approaches including coagulation-flocculation, filtration, and disinfection. Most sources do not delve into approaches specifically appropriate for developing countries, nor do they exclusively examine water disinfection methods.^ The objective of this review is to focus on an extensive range of chemical, physio-chemical, and physical water disinfection techniques to provide a compilation, description and evaluation of options available. Such an objective provides further understanding and knowledge to better inform water treatment interventions and explores alternate means of water disinfection appropriate for developing countries. Appropriateness for developing countries corresponds to the effectiveness of an available, easy to use disinfection technique at providing safe drinking water at a low cost.^ Among chemical disinfectants, SWS sodium hypochlorite solution is preferred over sodium hypochlorite bleach due to consistent concentrations. Tablet forms are highly recommended chemical disinfectants because they are effective and very easy to use, but also because they are stable. Examples include sodium dichloroisocyanurate, calcium hypochlorite, and chlorine dioxide, which vary in cost depending on location and availability. Among physio-chemical disinfection options, electrolysis which produces mixed oxidants (MIOX) provides a highly effective disinfection option with a higher upfront cost but very low cost over the long term. Among physical disinfection options, solar disinfection (SODIS) applications are effective, but they treat only a fixed volume of water at a time. They come with higher initial costs but very low on-going costs. Additional effective disinfection techniques may be suitable depending on the location, availability and cost.^

A STUDY OF INFLUENZA AND OF STATISTICAL METHODS USED TO REPORT INFLUENZA

This paper defines and compares several models for describing excess influenza pneumonia mortality in Houston. First, the methodology used by the Center for Disease Control is examined and several variations of this methodology are studied. All of the models examined emphasize the difficulty of omitting epidemic weeks.^ In an attempt to find a better method of describing expected and epidemic mortality, time series methods are examined. Grouping in four-week periods, truncating the data series to adjust epidemic periods, and seasonally-adjusting the series y(,t), by:^ (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI)^ is the best method examined. This new series w(,t) is stationary and a moving average model MA(1) gives a good fit for forecasting influenza and pneumonia mortality in Houston.^ Influenza morbidity, other causes of death, sex, race, age, climate variables, environmental factors, and school absenteeism are all examined in terms of their relationship to influenza and pneumonia mortality. Both influenza morbidity and ischemic heart disease mortality show a very high relationship that remains when seasonal trends are removed from the data. However, when jointly modeling the three series it is obvious that the simple time series MA(1) model of truncated, seasonally-adjusted four-week data gives a better forecast.^

Baseline evaluation of environmental physical activity and nutrition support of Texas Medical Center hospital worksites

Background: Obesity is a major health problem in the United States that has reached epidemic proportions. With most U.S adults spending the majority of their waking hours at work, the influence of the workplace environment on obesity is gaining in importance. Recent research implicates worksites as providing an 'obesogenic' environment as they encourage overeating and reduce the opportunity for physical activity. Objective: The aim of this study is to describe the nutrition and physical activity environment of Texas Medical Center (TMC) hospitals participating in the Shape Up Houston evaluation study to develop a scoring system to quantify the environmental data collected using the Environmental Assessment Tool (EAT) survey and to assess the inter-observer reliability of using the EAT survey. Methods: A survey instrument that was adapted from the Environmental Assessment Tool (EAT) developed by Dejoy DM et al in 2008 to measure the hospital environmental support for nutrition and physical activity was used for this study. The inter-observer reliability of using the EAT survey was measured and total percent agreement scores were computed. Most responses on the EAT survey are dichotomous (Yes and No) and these responses were coded with a '0' for a 'no' response and a '1' for a 'yes' response. A summative scoring system was developed to quantify these responses. Each hospital was given a score for each scale and subscale on the EAT survey in addition to a total score. All analyses were conducted using Stata 11 software. Results: High inter-observer reliability is observed using EAT. The percentage agreement scores ranged from 94.4%–100%. Only 2 of the 5 hospitals had a fitness facility onsite and scores for exercise programs and outdoor facilities available for hospital employees ranged from 0–62% and 0–37.5%, respectively. The healthy eating percentage for hospital cafeterias range from 42%–92% across the different hospitals while the healthy vending scores were 0%–40%. The total TMC 'healthy hospital' score was 49%. Conclusion: The EAT survey is a reliable instrument for measuring the physical activity and nutrition support environment of hospital worksites. The study results showed a large variability among the TMC hospitals in the existing physical activity and nutrition support environment. This study proposes cost effective policy changes that can increase environmental support to healthy eating and active living among TMC hospital employees.^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Raster maps for 29 environmental variables in three geographical regions

Aim: Greater understanding of the processes underlying biological invasions is required to determine and predict invasion risk. Two subspecies of olive (Olea europaea subsp. europaea and Olea europaea subsp. cuspidata) have been introduced into Australia from the Mediterranean Basin and southern Africa during the 19th century. Our aim was to determine to what extent the native environmental niches of these two olive subspecies explain the current spatial segregation of the subspecies in their non-native range. We also assessed whether niche shifts had occurred in the non-native range, and examined whether invasion was associated with increased or decreased occupancy of niche space in the non-native range relative to the native range. Location: South-eastern Australia, Mediterranean Basin and southern Africa. Methods: Ecological niche models (ENMs) were used to quantify the similarity of native and non-native realized niches. Niche shifts were characterized by the relative contribution of niche expansion, stability and contraction based on the relative occupancy of environmental space by the native and non-native populations. Results: Native ENMs indicated that the spatial segregation of the two subspecies in their non-native range was partly determined by differences in their native niches. However, we found that environmentally suitable niches were less occupied in the non-native range relative to the native range, indicating that niche shifts had occurred through a contraction of the native niches after invasion, for both subspecies. Main conclusions: The mapping of environmental factors associated with niche expansion, stability or contraction allowed us to identify areas of greater invasion risk. This study provides an example of successful invasions that are associated with niche shifts, illustrating that introduced plant species are sometimes readily able to establish in novel environments. In these situations the assumption of niche stasis during invasion, which is implicitly assumed by ENMs, may be unreasonable.

Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

Calcite saturation and yield and Mg/Ca, Mn/Ca, Al/Ca, Fe/Ca for four species of planktic foraminifera cleaned using Mg-cleaning and Cd-cleaning methods

Four species of planktic foraminifera from core-tops spanning a depth transect on the Ontong Java Plateau were prepared for Mg/Ca analysis both with (Cd-cleaning) and without (Mg-cleaning) a reductive cleaning step. Reductive cleaning caused etching of foraminiferal calcite, focused on Mg-rich inner calcite, even on tests which had already been partially dissolved at the seafloor. Despite corrosion, there was no difference in Mg/Ca of Pulleniatina obliquiloculata between cleaning methods. Reductive cleaning decreased Mg/Ca by an average (all depths) of ~ 4% for Globigerinoides ruber white and ~ 10% for Neogloboquadrina dutertrei. Mg/Ca of Globigerinoides sacculifer (above the calcite saturation horizon only) was 5% lower after reductive cleaning. The decrease in Mg/Ca due to reductive cleaning appeared insensitive to preservation state for G. ruber, N. dutertrei and P. obliquiloculata. Mg/Ca of Cd-cleaned G. sacculifer appeared less sensitive to dissolution than that of Mg-cleaned. Mg-cleaning is adequate, but SEM and contaminants (Al/Ca, Fe/Ca and Mn/Ca) show that Cd-cleaning is more effective for porous species. A second aspect of the study addressed sample loss during cleaning. Lower yield after Cd-cleaning for G. ruber, G. sacculifer and N. dutertrei confirmed this to be the more aggressive method. Strongest correlations between yield and Delta[CO3^2-] in core-top samples were for Cd-cleaned G. ruber (r = 0.88, p = 0.020) and Cd-cleaned P. obliquiloculata (r = 0.68, p = 0.030). In a down-core record (WIND28K) correlation, r, between yield values > 30% and dissolution index, XDX, was -0.61 (p = 0.002). Where cleaning yield < 30% most Mg-cleaned Mg/Ca values were biased by dissolution.

Environmental characteristics and gas composition of Lost Hammer, Canadian Arctic

We report the first microbiological characterization of a terrestrial methane seep in a cryo-environment in the form of an Arctic hypersaline (~24% salinity), subzero (-5 C), perennial spring, arising through thick permafrost in an area with an average annual air temperature of -15 C. Bacterial and archaeal 16S rRNA gene clone libraries indicated a relatively low diversity of phylotypes within the spring sediment (Shannon index values of 1.65 and 1.39, respectively). Bacterial phylotypes were related to microorganisms such as Loktanella, Gillisia, Halomonas and Marinobacter spp. previously recovered from cold, saline habitats. A proportion of the bacterial phylotypes were cultured, including Marinobacter and Halomonas, with all isolates capable of growth at the in situ temperature (-5 C). Archaeal phylotypes were related to signatures from hypersaline deep-sea methane-seep sediments and were dominated by the anaerobic methane group 1a (ANME-1a) clade of anaerobic methane oxidizing archaea. CARD-FISH analyses indicated that cells within the spring sediment consisted of ~84.0% bacterial and 3.8% archaeal cells with ANME-1 cells accounting for most of the archaeal cells. The major gas discharging from the spring was methane (~50%) with the low CH4/C2 + ratio and hydrogen and carbon isotope signatures consistent with a thermogenic origin of the methane. Overall, this hypersaline, subzero environment supports a viable microbial community capable of activity at in situ temperature and where methane may behave as an energy and carbon source for sustaining anaerobic oxidation of methane-based microbial metabolism. This site also provides a model of how a methane seep can form in a cryo-environment as well as a mechanism for the hypothesized Martian methane plumes.