Estimating extreme flood events:Assumptions, uncertainty and error

Hydrological extremes are amongst the most devastating forms of natural disasters both in terms of lives lost and socio-economic impacts. There is consequently an imperative to robustly estimate the frequency and magnitude of hydrological extremes. Traditionally, engineers have employed purely statistical approaches to the estimation of flood risk. For example, for an observed hydrological timeseries, each annual maximum flood is extracted and a frequency distribution is fit to these data. The fitted distribution is then extrapolated to provide an estimate of the required design risk (i.e. the 1 % Annual Exceedance Probability – AEP). Such traditional approaches are overly simplistic in that risk is implicitly assumed to be static, in other words, that climatological processes are assumed to be randomly distributed in time. In this study, flood risk estimates are evaluated with regards to traditional statistical approaches as well as Pacific Decadal Oscillation (PDO)/El Niño-Southern Oscillation (ENSO) conditional estimates for a flood-prone catchment in eastern Australia. A paleo-reconstruction of pre-instrumental PDO/ENSO occurrence is then employed to estimate uncertainty associated with the estimation of the 1 % AEP flood. The results indicate a significant underestimation of the uncertainty associated with extreme flood events when employing the traditional engineering estimates

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape : A Large-Scale Genome-Wide Interaction Study

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age-and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to similar to 2.8M SNPs with BMI and WHRadjBMI in four strata (men 50y, women 50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR= 50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may providefurther insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.Peer reviewe

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

Contraindre les prédictions d'un modèle distribué : l'incorporation d'une estimation floue des zones saturées au niveau du processus d'apprentissage

[Departement_IRSTEA]GT [TR1_IRSTEA]GMA1-Fonctionnement hydrologique des bassins et des réseaux hydrographiquesInternational audienceDistributed hydrological models are generally overparameterized, resulting in the possibility of multiple parameterizations from many areas of the parameter space, providing acceptable fits to be observed data. In this study, TOPMODEL parameterizations are conditioned on discharges, and then further conditioned on estimates of satured areas derived from ERS-1 snthetic aperture radar (SAR) images combined with the In (a/tan beta) topographic index, and compared to ground thruth saturation measurements made is one small subcatchment. The uncertainty associated with the catchment-wide predictions of saturated area is explicitly incorporated into the conditioning through the weighting of estimtes within a fuzzy set framework. The predictive uncertainty associated with the parameterizations is then assessed using the generalized likelihood uncertainty estimation (GLUE) methodology. It is shown that despite the uncertainty in the predictions of the saturated area the methodology can reject many previously acceptable range of a catchment average transmissivity parameter and of improved predictions of some discharge events.Les modèles hydrologiques distribués sont généralement surparamétrés, d'où une multitude de paramétrisations possibles, capables de reproduire convenablement les données observées. Dans cette étude, les paramétrisations de TOPMODEL sont tout d'abord conditionnées par un apprentissage sur les débits ; puis l'apprentissage se poursuit sur la base d'une estimation floue de l'extension des zones saturées déduite des images radar d'ERS-1 combinées à l'indice topographique, et comparée aux observations terrain d'un petit sous-bassin. L'incertitude associée aux prédictions de l'extension des zones saturées à l'échelle du bassin est explicitement incorporée dans le processus d'apprentissage du modèle à l'aide de mesures de vraisemblance. Les incertitudes sur la prédiction des débits sont alors évaluées à l'aide de la méthode GLUE. On montre, qu'en dépit de l'incertitude portant sur l'estimation des zones saturées, la méthode conduit à rejeter de nombreuses paramétrisations précédemment acceptables, à une réduction importante de la plage de variation du paramètre de transmissivité moyenne, et une amélioration sensible des prédictions du modèle

Self-organization, collective decision making and resource exploitation strategies in social insects

05.65.+b Self-organized systems, 05.10.Ln Monte Carlo methods,

In vitro fermentation of sugar beet arabinan and arabino-oligosaccharides by the human gut microflora

Aims: To determine the fermentation profiles by human gut bacteria of arabino-oligosaccharides of varying degree of polymerization. Materials and Methods: Sugar beet arabinan was hydrolyzed with a commercial pectinase and eight fractions, of varying molecular weight, were isolated by gel-filtration chromatography. Hydrolysis fractions, arabinose, arabinan and fructo-oligosaccharides were fermented anaerobically by gut bacteria. Total bacteria, bifidobacteria, bacteroides, lactobacilli and the Clostridium perfringens/histolyticum sub. grp. were enumerated using fluorescent in situ hybridization. Results: Bifidobacteria were stimulated to different extents depending on molecular weight, i.e. maximum increase in bifidobacteria after 48 h was seen on the lower molecular weight fractions. Lactobacilli fluctuated depending on the initial inoculum levels. Bacteroides numbers varied according to fraction; arabinan, arabinose and higher oligosaccharides (degree of polymerization, dp > 8) resulted in significant increases at 24 h. Only carbohydrate mixtures with dp of 1-2 resulted in significant increases at 48 h (log 8.77 +/- 0.23). Clostridia decreased on all substrates. Conclusions: Arabino-oligosaccharides can be considered as potential prebiotics. Significance and Impact of the Study: Arabinan is widely available as it is a component of sugar beet pulp, a co-product from the sugar beet industry. Generation of prebiotic functionality from arabinan would represent significant added value to a renewable resource