An Extreme Value Analysis of Pollutant Concentrations in Surface Soils Due to Atmospheric Deposition

Risk assessments often rely on deterministic models using long-term averages or “steady-state” values of input variables. Such models do not provide the information needed to estimate acute exposures. This study uses extreme value theory to examine the frequency and magnitude of daily pollutant concentrations in surface soils predicted at six U.S. locations. Concentrations are predicted using a deposition-leaching model and 50 years of historical precipitation data. A stochastic model also is used to generate 1000 years of precipitation data as modeling inputs for each location. The annual maximum concentrations at each site are fitted to a Gumbel type I distribution to estimate occurrence probability. For soluble pollutants, the predicted concentration varied substantially with precipitation, and the maximum daily concentrations exceeded annual averages by 4 to 8 times. Observed and synthetic precipitation data produced similar results at most study locations, though the synthetic data provided a slightly better fit to the Gumbel type I distribution. The precipitation model allows the generation of representative precipitation data that extend limited historical records. The extreme value analysis facilitates the evaluation of maximum pollutant concentrations, return periods, and other statistics that are important in evaluating acute exposures.     

Effects of the supply levels and ratios of nitrogen and phosphorus on seed traits of Chenopodium glaucum

全球氮沉降不仅改变土壤氮和磷的有效性, 同时也改变氮磷比例。氮磷供应量、比例及其交互作用可能会影响植物种子性状。该研究在内蒙古草原基于沙培盆栽实验种植灰绿藜(Chenopodium glaucum), 设置3个氮磷供应量水平和3个氮磷比例的正交实验来探究氮磷供应量、比例及其交互作用对灰绿藜种子性状的影响。结果发现氮磷供应量对种子氮浓度、磷浓度和萌发率影响的相对贡献(15%-24%)大于氮磷比例(3%-7%), 而种子大小只受氮磷比例的影响。同时氮磷供应量和比例之间的交互作用显著影响种子氮浓度和磷浓度。同等氮磷比例情况下, 低量养分供应提高种子氮浓度、磷浓度和萌发率。氮磷比例只有在养分匮乏的环境中才会对种子大小和萌发率产生显著影响。总之, 灰绿藜种子不同性状对氮或磷限制的敏感性不同, 同时种子性状也对养分限制表现出适应性和被动响应。     

Environmental and genetic control of crassulacean acid metabolism in two crassulacean species and an F1 hybrid with differing biomass δ13C values

Abstract The growth, biomass δ¹³C values, and ability to accumulate titratable acidity at night were compared in eight environmental treatments for Cremnophila linguifolia, Sedum greggii, and their F₁ hybrid. In the phytotron, differences in treatment daylength, day/night temperature and water availability were all found to have effects on total plant dry weight, nocturnal accumulation of titratable acidity and biomass δ¹³C value of at least some of the genotypes. However, there were differences between the genotypes both in the magnitude and direction of response of the phenotypic properties to the treatment variables. The phytotron δ¹³C values ranged from -12.9 to -19.2‰ for C. linguifolia, from -22.2 to -33.4‰ for S. greggii, and from -19.2 to -24.9‰ for the hybrid. After with-holding water for 76 h both C. linguifolia and the hybrid had midday Ψ_leaf values of -0.23 MPa; however, S. greggii had a value of -1.05 MPa. In contrast to past observations of other species, the daily watered plants of C. linguifolia had less negative δ¹³C values than did the plants watered only weekly.     

The Amount of BCL6 in B Cells Shortly after Antigen Engagement Determines Their Representation in Subsequent Germinal Centers

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How Can the Eco‐efficiency of a Region be Measured and Monitored?

The concept of eco-efficiency is commonly referred to as a business link to sustainable development. In this article, ecoefficiency is examined at a regional level as an approach to promoting the competitiveness of economic activities in the Finnish Kymenlaakso region and mitigating their harmful impacts on the environment. The aim is to develop appropriate indicators for monitoring changes in the eco-efficiency of the region. A starting point is to produce indicators for the environmental and economic dimensions of regional development and use them for measuring regional eco-efficiency. The environmental impact indicators are based on a life-cycle assessment method, producing different types of environmental impact indicators: pressure indicators (e.g., emissions of CO₂), impact category indicators (e.g., CO₂ equivalents in the case of climate change), and a total impact indicator (aggregating different impact category indicator results into a single value). Environmental impact indicators based on direct material input, total material input, and total material requirement of the Kymenlaakso region are also assessed. The economic indicators used are the gross domestic product, the value added, and the output of the main economic sectors of Kymenlaakso. In the eco-efficiency assessment, the economic and environmental impact indicators are monitored in the same graph. In a few cases eco-efficiency ratios can also be calculated (the economic indicators are divided by the environmental indicators). Output (= value added + intermediate consumption) is used as an economic indicator related to the environmental impact indicators, which also cover the upstream processes of the region's activities. In the article, we also discuss the strengths and weaknesses of using the different environmental impact indicators.     

Adaptive developmental plasticity: what is it,how can we recognize it and when can it evolve?

Developmental plasticity describes situations where a specific input during an individual''s development produces a lasting alteration in phenotype. Some instances of developmental plasticity may be adaptive, meaning that the tendency to produce the phenotype conditional on having experienced the developmental input has been under positive selection. We discuss the necessary assumptions and predictions of hypotheses concerning adaptive developmental plasticity (ADP) and develop guidelines for how to test empirically whether a particular example is adaptive. Central to our analysis is the distinction between two kinds of ADP: informational, where the developmental input provides information about the future environment, and somatic state-based, where the developmental input enduringly alters some aspect of the individual''s somatic state. Both types are likely to exist in nature, but evolve under different conditions. In all cases of ADP, the expected fitness of individuals who experience the input and develop the phenotype should be higher than that of those who experience the input and do not develop the phenotype, while the expected fitness of those who do not experience the input and do not develop the phenotype should be higher than those who do not experience the input and do develop the phenotype. We describe ancillary predictions that are specific to just one of the two types of ADP and thus distinguish between them.     

Ethical Considerations for Outcome‐adaptive Trial Designs: A Clinical Researcher's Perspective

In a typical comparative clinical trial the randomization scheme is fixed at the beginning of the study, and maintained throughout the course of the trial. A number of researchers have championed a randomized trial design referred to as ‘outcome‐adaptive randomization.’ In this type of trial, the likelihood of a patient being enrolled to a particular arm of the study increases or decreases as preliminary information becomes available suggesting that treatment may be superior or inferior. While the design merits of outcome‐adaptive trials have been debated, little attention has been paid to significant ethical concerns that arise in the conduct of such studies. These include loss of equipoise, lack of processes for adequate informed consent, and inequalities inherent in the research design which could lead to perceptions of injustice that may have negative implications for patients and the research enterprise. This article examines the ethical difficulties inherent in outcome‐adaptive trials.     

Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)