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Soil properties show high heterogeneity at different spatial scales and their correct characterization remains a crucial challenge over large areas. The aim of the study is to quantify the impact of different types of uncertainties that arise from the unresolved soil spatial variability on simulated hydrological states and fluxes. Three perturbation methods are presented for the characterization of uncertainties in soil properties. The methods are applied on the soil map of the upper Neckar catchment (Germany), as an example. The uncertainties are propagated through the distributed mesoscale hydrological model (mHM) to assess the impact on the simulated states and fluxes. The model outputs are analysed by aggregating the results at different spatial and temporal scales. These results show that the impact of the different uncertainties introduced in the original soil map is equivalent when the simulated model outputs are analysed at the model grid resolution (i.e. 500 m). However, several differences are identified by aggregating states and fluxes at different spatial scales (by subcatchments of different sizes or coarsening the grid resolution). Streamflow is only sensitive to the perturbation of long spatial structures while distributed states and fluxes (e.g. soil moisture and groundwater recharge) are only sensitive to the local noise introduced to the original soil properties. A clear identification of the temporal and spatial scale for which finer-resolution soil information is (or is not) relevant is unlikely to be universal. However, the comparison of the impacts on the different hydrological components can be used to prioritize the model improvements in specific applications, either by collecting new measurements or by calibration and data assimilation approaches. In conclusion, the study underlines the importance of a correct characterization of uncertainty in soil properties. With that, soil maps with additional information regarding the unresolved soil spatial variability would provide strong support to hydrological modelling applications.
Fat loads were quantified for 2125 Yellow-browed Warblers Phylloscopus inornatus trapped at a stop-over site in Far East Russia during autumn migration. Flight ranges of 660–820 km were estimated for the fattest individuals, suggesting that they would need to stop for refuelling at least six times to reach their wintering areas in South East Asia.
Recent research has called into question the current practice to estimate individual usual food intake in large-scale studies. In such studies, usual food intake has been defined as diet over the past year. The aim of this review is to summarise the concepts of dietary assessment methods providing food intake data over this time period. A conceptualised framework is given to help researchers to understand the more recent developments to improve dietary assessment in large-scale prospective studies, and also to help to spot the gaps that need to be addressed in future methodological research. The conceptual framework illustrates the current options for the assessment of an individual’s food consumption over 1 year. Ideally, a person’s food intake on each day of this year should be assessed. Due to participants’ burden, and organisational and financial constraints, however, the options are limited to directly requesting the long-term average (e.g. food frequency questionnaires), or selecting a few days with detailed food consumption measurements (e.g. 24-hour dietary recalls) or using snapshot techniques (e.g. barcode scanning of purchases). It seems necessary and important to further evaluate the performance of statistical modelling of the individual usual food intake from all available sources. Future dietary assessment might profit from the growing prominence of internet and telecommunication technologies to further enhance the available data on food consumption for each study participant. Research is crucial to investigate the performance of innovative assessment tools. However, the self-reported nature of the data itself will always lead to bias.
The role of serum amyloid A and sphingosine-1-phosphate on high-density lipoprotein functionality
(2017)
The high-density lipoprotein (HDL) is one of the most important endogenous cardiovascular protective markers. HDL is an attractive target in the search for new pharmaceutical therapies and in the prevention of cardiovascular events. Some of HDL’s anti-atherogenic properties are related to the signaling molecule sphingosine-1-phosphate (S1P), which plays an important role in vascular homeostasis. However, for different patient populations it seems more complicated. Significant changes in HDL’s protective potency are reduced under pathologic conditions and HDL might even serve as a proatherogenic particle. Under uremic conditions especially there is a change in the compounds associated with HDL. S1P is reduced and acute phase proteins such as serum amyloid A (SAA) are found to be elevated in HDL. The conversion of HDL in inflammation changes the functional properties of HDL. High amounts of SAA are associated with the occurrence of cardiovascular diseases such as atherosclerosis. SAA has potent pro-atherogenic properties, which may have impact on HDL’s biological functions, including cholesterol efflux capacity, antioxidative and anti-inflammatory activities. This review focuses on two molecules that affect the functionality of HDL. The balance between functional and dysfunctional HDL is disturbed after the loss of the protective sphingolipid molecule S1P and the accumulation of the acute-phase protein SAA. This review also summarizes the biological activities of lipid-free and lipid-bound SAA and its impact on HDL function.