Modern diatom, cladocera, chironomid, and chrysophyte cyst assemblages as quantitative indicators for the reconstruction of past environmental conditions in the Alps. II. Nutrients

Surface sediments from 68 small lakes in the Alps and 9 well-dated sediment core samples that cover a gradient of total phosphorus (TP) concentrations of 6 to 520 μg TP l-1 were studied for diatom, chrysophyte cyst, cladocera, and chironomid assemblages. Inference models for mean circulation log10 TP were developed for diatoms, chironomids, and benthic cladocera using weighted-averaging partial least squares. After screening for outliers, the final transfer functions have coefficients of determination (r2, as assessed by cross-validation, of 0.79 (diatoms), 0.68 (chironomids), and 0.49 (benthic cladocera). Planktonic cladocera and chrysophytes show very weak relationships to TP and no TP inference models were developed for these biota. Diatoms showed the best relationship with TP, whereas the other biota all have large secondary gradients, suggesting that variables other than TP have a strong influence on their composition and abundance. Comparison with other diatom – TP inference models shows that our model has high predictive power and a low root mean squared error of prediction, as assessed by cross-validation.

An intercontinental comparison of chironomid palaeotemperature inference models: Europe vs North America

Chironomid-temperature inference models based on North American, European and combined surface sediment training sets were compared to assess the overall reliability of their predictions. Between 67 and 76 of the major chironomid taxa in each data set showed a unimodal response to July temperature, whereas between 5 and 22 of the common taxa showed a sigmoidal response. July temperature optima were highly correlated among the training sets, but the correlations for other taxon parameters such as tolerances and weighted averaging partial least squares (WA-PLS) and partial least squares (PLS) regression coefficients were much weaker. PLS, weighted averaging, WA-PLS, and the Modern Analogue Technique, all provided useful and reliable temperature inferences. Although jack-knifed error statistics suggested that two-component WA-PLS models had the highest predictive power, intercontinental tests suggested that other inference models performed better. The various models were able to provide good July temperature inferences, even where neither good nor close modern analogues for the fossil chironomid assemblages existed. When the models were applied to fossil Lateglacial assemblages from North America and Europe, the inferred rates and magnitude of July temperature changes varied among models. All models, however, revealed similar patterns of Lateglacial temperature change. Depending on the model used, the inferred Younger Dryas July temperature decrease ranged between 2.5 and 6°C.

Genetic diversity and differentiation follow secondary succession in a multi-species study on woody plants from subtropical China

Aims: Species diversity and genetic diversity may be affected in parallel by similar environmental drivers. However, genetic diversity may also be affected independently by habitat characteristics. We aim at disentangling relationships between genetic diversity, species diversity and habitat characteristics of woody species in subtropical forest. Methods: We studied 11 dominant tree and shrub species in 27 plots in Gutianshan, China, and assessed their genetic diversity (Ar) and population differentiation (F’ST) with microsatellite markers. We tested if Ar and population specific F’ST were correlated to local species diversity and plot characteristics. Multi-model inference and model averaging were used to determine the relative importance of each predictor. Additionally we tested for isolation-by-distance and isolation-by-elevation by regressing pairwise F’ST against pairwise spatial and elevational distances. Important findings: Genetic diversity was not related to species diversity for any of the study species. Thus, our results do not support joint effects of habitat characteristics on these two levels of biodiversity. Instead, genetic diversity in two understory shrubs, Rhododendron simsii and Vaccinium carlesii, was affected by plot age with decreasing genetic diversity in successionally older plots. Population differentiation increased with plot age in Rhododendron simsii and Lithocarpus glaber. This shows that succession can reduce genetic diversity within, and increase genetic diversity between populations. Furthermore, we found four cases of isolation-by-distance and two cases of isolation-by-elevation. The former indicates inefficient pollen and seed dispersal by animals whereas the latter might be due to phenological asynchronies. These patterns indicate that succession can affect genetic diversity without parallel effects on species diversity and that gene flow in a continuous subtropical forest can be restricted even at a local scale.

Evolution of 1996-1999 La Niña and El Niño Conditions Off the Western Coast of South America: A Remote Sensing Perspective

We present the evolution of oceanographic conditions off the western coast of South America between 1996 and 1999, including the cold periods of 1996 and 1998-1999 and the 1997-1998 El Niño, using satellite observations of sea level, winds, sea surface temperature (SST), and chlorophyll concentration. Following a period of cold SST and low sea levels in 1996, both were anomalously high between March 1997 and May 1998. The anomalies were greatest between 5 degrees S and 15 degrees S, although they extended beyond 40 degrees S. Two distinct peaks in sea level and SST occurred in June-July 1997 and December 1997 to January 1998, separated by a relaxation period (August-November) of weaker anomalies. Satellite winds were upwelling favorable throughout the time period for most of the region and in fact increased between November 1997 and March 1998 between 5 degrees S and 25 degrees S. Satellite-derived chlorophyll concentrations are available for November 1996 to June 1997 (Ocean Color and Temperature Sensor (OCTS)) and then from October 1997 to present (Sea-viewing Wide Field-of-view Sensor (SeaWiFS)). Near-surface chlorophyll concentrations fell from May to June 1997 and from December 1997 to March 1998. The decrease was more pronounced in northern Chile than off the coast of Peru or central Chile and was stronger for larger cross-shelf averaging bins since nearshore concentrations remained relatively high.

Do Proctored Exams Matter In Online Classes?

Does the format of assessment (proctored or un-proctored exams) affect test scores in online principles of economics classes? This study uses data from two courses of principles of economics taught by the same instructor to gain some insight into this issue. When final exam scores are regressed against human capital factors, the R-squared statistic is 61.6% for the proctored format exams while it is only 12.2% for the un-proctored format. Three other exams in the class that had the proctored final were also un-proctored and also produced lower R-squared values, averaging 30.5%. These two findings suggest that some cheating may have taken place in the un-proctored exams. Although it appears some cheating took place, the results suggest that cheating did not pay for these students since the proctored exam grades were 4.9 points higher than the un-proctored exam grades although this difference was significantly different at only the 10% level. One possible explanation for this is that there was slightly higher human capital in the class that had the proctored exam although this must have occurred by chance since the students did not know if the exams were going to be proctored in advance so there is no issue of selection bias. A Oaxaca decomposition of this difference in grades was conducted to see how much was due to human capital and how much was due to the differences in the rates of return to human capital. This analysis reveals that 17% of the difference was due to the higher human capital with the remaining 83% due to differences in the returns to human capital. It is possible that the un-proctored exam format does not encourage as much studying as the proctored format reducing both the returns to human capital and the exam scores.

Multiple gradient echo propeller (MGREP) MRI: Technical development and potential applications

The PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction) magnetic resonance imaging (MRI) technique has inherent advantages over other fast imaging methods, including robust motion correction, reduced image distortion, and resistance to off-resonance effects. These features make PROPELLER highly desirable for T2*-sensitive imaging, high-resolution diffusion imaging, and many other applications. However, PROPELLER has been predominantly implemented as a fast spin-echo (FSE) technique, which is insensitive to T2* contrast, and requires time-inefficient signal averaging to achieve adequate signal-to-noise ratio (SNR) for many applications. These issues presently constrain the potential clinical utility of FSE-based PROPELLER. ^ In this research, our aim was to extend and enhance the potential applications of PROPELLER MRI by developing a novel multiple gradient echo PROPELLER (MGREP) technique that can overcome the aforementioned limitations. The MGREP pulse sequence was designed to acquire multiple gradient-echo images simultaneously, without any increase in total scan time or RF energy deposition relative to FSE-based PROPELLER. A new parameter was also introduced for direct user-control over gradient echo spacing, to allow variable sensitivity to T2* contrast. In parallel to pulse sequence development, an improved algorithm for motion correction was also developed and evaluated against the established method through extensive simulations. The potential advantages of MGREP over FSE-based PROPELLER were illustrated via three specific applications: (1) quantitative T2* measurement, (2) time-efficient signal averaging, and (3) high-resolution diffusion imaging. Relative to the FSE-PROPELLER method, the MGREP sequence was found to yield quantitative T2* values, increase SNR by ∼40% without any increase in acquisition time or RF energy deposition, and noticeably improve image quality in high-resolution diffusion maps. In addition, the new motion algorithm was found to improve the performance considerably in motion-artifact reduction. ^ Overall, this work demonstrated a number of enhancements and extensions to existing PROPELLER techniques. The new technical capabilities of PROPELLER imaging, developed in this thesis research, are expected to serve as the foundation for further expanding the scope of PROPELLER applications. ^

Revising the National Ambient Air Quality Standards: The integration of science and policy

Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^

The association between classroom characteristics and student physical activity in physical education classrooms

Background. With the rapid rise in childhood obesity, physical activity participation among young children has become the subject of much recent attention. Physical education classes have been specifically targeted as a method of providing opportunities for all children to be active. Unfortunately, student participation in moderate-to-vigorous physical activity during these classes still falls far below the current recommendations. While some research to date has reported the levels of activity among elementary-aged children, research is limited on the relationship between these activity levels and the environmental characteristics that exist within the PE classroom. ^ Purpose. The purpose of this study is to examine the association between specific classroom characteristics and contextual characteristics (lesson context, class size, class location, teacher gender, and teacher encouragement for PA) with elementary aged children's moderate-to-vigorous activity during PE class. ^ Methods. A secondary analysis of 211 3rd, 4th and 5th grade physical education classes amongst 39 elementary schools in Harris County, TX and 35 elementary schools in Travis County, TX was conducted using cross-sectional data from the evaluation of a school-based health program. Lesson context and student activity levels were measured using a direct observation measurement tool. Additionally, these variables were further analyzed against a number of classroom characteristics to determine any significant associations. ^ Results. Overall, elementary PE classes are still participating in low levels of moderate-to-vigorous physical activity averaging only 38% of class time. Additionally, close to 25% of class time is spent in classroom management. Male directed classes spent significantly more time in game activities and female directed classes spent more time in fitness, knowledge, and skill activities. Classes that took place outdoors were more active and spent more time in games than those that took place indoors. Significant correlations were demonstrated between class size and time spent in management context. Time spent in management context was also correlated with time spent sitting and standing. Additionally, positive correlations were demonstrated between time very active and teachers that praised students and encouraged physical activity among their classes.^

Bayesian adaptive designs for drug combinations in early phase clinical trials

Treating patients with combined agents is a growing trend in cancer clinical trials. Evaluating the synergism of multiple drugs is often the primary motivation for such drug-combination studies. Focusing on the drug combination study in the early phase clinical trials, our research is composed of three parts: (1) We conduct a comprehensive comparison of four dose-finding designs in the two-dimensional toxicity probability space and propose using the Bayesian model averaging method to overcome the arbitrariness of the model specification and enhance the robustness of the design; (2) Motivated by a recent drug-combination trial at MD Anderson Cancer Center with a continuous-dose standard of care agent and a discrete-dose investigational agent, we propose a two-stage Bayesian adaptive dose-finding design based on an extended continual reassessment method; (3) By combining phase I and phase II clinical trials, we propose an extension of a single agent dose-finding design. We model the time-to-event toxicity and efficacy to direct dose finding in two-dimensional drug-combination studies. We conduct extensive simulation studies to examine the operating characteristics of the aforementioned designs and demonstrate the designs' good performances in various practical scenarios.^

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.

Net primary productivity, POC export, Th234 and U238 activities and abundance of autotrophs during U.S.C.G.C. Healy cruises HLY0802 and HLY0803

Seasonal patterns in the partitioning of phytoplankton carbon during receding sea ice conditions in the eastern Bering Sea water column are presented using rates of 14C net primary productivity (NPP), phototrophic plankton carbon content, and POC export fluxes from shelf and slope waters in the spring (March 30-May 6) and summer (July 3-30) of 2008. At ice-covered and marginal ice zone (MIZ) stations on the inner and middle shelf in spring, NPP averaged 76 ± 93 mmol C/m**2/d, and in ice-free waters on the outer shelf NPP averaged 102 ± 137 mmol C/m**2/d. In summer, rates of NPP were more uniform across the entire shelf and averaged 43 ± 23 mmol C/m**2/d over the entire shelf. A concomitant shift was observed in the phototrophic pico-, nano-, and microplankton community in the chlorophyll maximum, from a diatom dominated system (80 ± 12% autotrophic C) in ice covered and MIZ waters in spring, to a microflagellate dominated system (71 ± 31% autotrophic C) in summer. Sediment trap POC fluxes near the 1% PAR depth in ice-free slope waters increased by 70% from spring to summer, from 10 ± 7 mmol C/m**2/d to 17 ± 5 mmol C/m**2/d, respectively. Over the shelf, under-ice trap fluxes at 20 m were higher, averaging 43 ± 17 mmol C/m**2/d POC export over the shelf and slope estimated from 234Th deficits averaged 11 ± 5 mmol C/m**2/d in spring and 10 ± 2 mmol C/m**2/d in summer. Average e-ratios calculated on a station-by-station basis decreased by ~ 30% from spring to summer, from 0.46 ± 0.48 in ice-covered and MIZ waters, to 0.33 ± 0.26 in summer, though the high uncertainty prevents a statistical differentiation of these data.

Ground beetle (Carabidae) abundance data from north-eastern Australian rainforest, between June 2008 - January 2010, using pitfall traps

Understanding how the environment influences patterns of diversity is vital for effective conservation management, especially in a changing global climate. While assemblage structure and species richness patterns are often correlated with current environmental factors, historical influences may also be considerable, especially for taxa with poor dispersal abilities. Mountain-top regions throughout tropical rainforests can act as important refugia for taxa characterised by low dispersal capacities such as flightless ground beetles (Carabidae), an ecologically significant predatory group. We surveyed flightless ground beetles along elevational gradients in five different subregions within the Australian Wet Tropics World Heritage Area to investigate (1) whether the diversity and composition of flightless ground beetles are elevationally stratified, and, if so, (2) what environmental factors (other than elevation per se) are associated with these patterns. Generalised linear models and model averaging techniques were used to relate patterns of diversity to environmental factors. Unlike most taxonomic groups, flightless ground beetles increased in species richness and abundance with elevation. Additionally, each subregion consisted of distinct assemblages containing a high level of regional endemic species. Species richness was most strongly positively associated with the historical climatic conditions and negatively associated with severity of recent disturbance (treefalls) and current climatic conditions. Assemblage composition was associated with latitude and current and historical climatic conditions. Our results suggest that distributional patterns of flightless ground beetles are not only likely to be associated with factors that change with elevation (current climatic conditions), but also factors that are independent of elevation (recent disturbance and historical climatic conditions). Variation in historical vegetation stability explained both species richness and assemblage composition patterns, probably reflecting the significance of upland refugia at a geographic time scale. These findings are important for conservation management as upland habitats are under threat from climate change.

Chemistry of Jurassic/Cretaceous black shales

Black shale samples of Jurassic to Cretaceous age recovered during the 'Norwegian Shelf Drilling Program' between 1987 and 1991 from Sites 7430/10-U-01 (Barents Sea), 6814/04-U-02 (Norwegian Shelf near the Lofoten) and 6307/07-U-02 (Norwegian Shelf near Trondheim) were analyzed for major and trace elements. These laminated black shales are characterized by high total organic carbon (TOC) and total sulfur (TS) contents as well as by significant enrichments in several redox-sensitive and/or sulfide-forming trace metals (Ag, Bi, Cd, Co, Cr, Cu, Mo, Ni, Re, Sb, Tl, U, V, and Zn). Enrichment factors relative to 'average shale' are comparable to those found in Cenomanian-Turonian boundary event (CTBE) black shales and Mediterranean sapropels. The Re content is high in the studied black shales, with maximum values up to 1221 ng/g. Re/Mo ratios averaging 2.3*10**-3 are close to the seawater value. High trace metal enrichments and Re/Mo ratios close to the seawater value point to a dominantly anoxic and sulfidic water column during black shale formation. Interbeds with higher Re/Mo ratios, especially in high-resolution sampled core sections, point to brief periods of suboxic conditions. Additionally, enhanced Zn concentrations in the black shales from the Barents Sea support the assumption that hydrothermal activity was also high during black shale deposition. Trace metal signatures of black shales at different drill sites on a transect along the Norwegian Shelf are not only influenced by water depth but also by their location in the boreal realm. Metal enrichments are higher in the northern compared to the southern sites. Volgian (=Tithonian 151-144 Ma BP) black shales exhibit elevated trace metal contents in comparison to their Berriasian (144-137 Ma BP) counterparts. This probably reflects a change in the circulation pattern during periods of black shale formation. Therefore different paleoceanographic conditions, probably controlled by climatic change linked to the transgression of the paleo-sealevel and the North Atlantic opening, may have developed from the Volgian to the Berriasian.