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Variables Alone (variable + alone)
Selected AbstractsPredictability of river flow and suspended sediment transport in the Mississippi River basin: a non-linear deterministic approachEARTH SURFACE PROCESSES AND LANDFORMS, Issue 6 2005Bellie Sivakumar Abstract As the Mississippi River plays a major role in fulfilling various water demands in North America, accurate prediction of river flow and sediment transport in the basin is crucial for undertaking both short-term emergency measures and long-term management efforts. To this effect, the present study investigates the predictability of river flow and suspended sediment transport in the basin. As most of the existing approaches that link water discharge, suspended sediment concentration and suspended sediment load possess certain limitations (absence of consensus on linkages), this study employs an approach that presents predictions of a variable based on history of the variable alone. The approach, based on non-linear determinism, involves: (1) reconstruction of single-dimensional series in multi-dimensional phase-space for representing the underlying dynamics; and (2) use of the local approximation technique for prediction. For implementation, river flow and suspended sediment transport variables observed at the St. Louis (Missouri) station are studied. Specifically, daily water discharge, suspended sediment concentration and suspended sediment load data are analysed for their predictability and range, by making predictions from one day to ten days ahead. The results lead to the following conclusions: (1) extremely good one-day ahead predictions are possible for all the series; (2) prediction accuracy decreases with increasing lead time for all the series, but the decrease is much more significant for suspended sediment concentration and suspended sediment load; and (3) the number of mechanisms dominantly governing the dynamics is three for each of the series. Copyright © 2005 John Wiley & Sons, Ltd. [source] Global evidence that deforestation amplifies flood risk and severity in the developing worldGLOBAL CHANGE BIOLOGY, Issue 11 2007COREY J. A. BRADSHAW Abstract With the wide acceptance of forest-protection policies in the developing world comes a requirement for clear demonstrations of how deforestation may erode human well-being and economies. For centuries, it has been believed that forests provide protection against flooding. However, such claims have given rise to a heated polemic, and broad-scale quantitative evidence of the possible role of forests in flood protection has not been forthcoming. Using data collected from 1990 to 2000 from 56 developing countries, we show using generalized linear and mixed-effects models contrasted with information-theoretic measures of parsimony that flood frequency is negatively correlated with the amount of remaining natural forest and positively correlated with natural forest area loss (after controlling for rainfall, slope and degraded landscape area). The most parsimonious models accounted for over 65% of the variation in flood frequency, of which nearly 14% was due to forest cover variables alone. During the decade investigated, nearly 100 000 people were killed and 320 million people were displaced by floods, with total reported economic damages exceeding US$1151 billion. Extracted measures of flood severity (flood duration, people killed and displaced, and total damage) showed some weaker, albeit detectable correlations to natural forest cover and loss. Based on an arbitrary decrease in natural forest area of 10%, the model-averaged prediction of flood frequency increased between 4% and 28% among the countries modeled. Using the same hypothetical decline in natural forest area resulted in a 4,8% increase in total flood duration. These correlations suggest that global-scale patterns in mean forest trends across countries are meaningful with respect to flood dynamics. Unabated loss of forests may increase or exacerbate the number of flood-related disasters, negatively impact millions of poor people, and inflict trillions of dollars in damage in disadvantaged economies over the coming decades. This first global-scale empirical demonstration that forests are correlated with flood risk and severity in developing countries reinforces the imperative for large-scale forest protection to protect human welfare, and suggests that reforestation may help to reduce the frequency and severity of flood-related catastrophes. [source] Fragmentation and pre-existing species turnover determine land-snail assemblages of tropical rain forestJOURNAL OF BIOGEOGRAPHY, Issue 10 2009Dinarzarde C. Raheem Abstract Aim, The main aims of the study were: (1) to investigate the effect of fragment age in relation to other patch- and landscape-scale measures of forest fragmentation, and (2) to assess the relative importance of fragmentation, habitat degradation (i.e. degradation caused by selective logging and past shifting cultivation) and putative pre-existing species turnover in structuring current land-snail assemblages. Location, South-western Sri Lanka. Methods, The land-snail fauna was sampled using standardized belt transects. Fifty-seven transects were sampled in 21 lowland rain forest fragments (c. 1,33,000 ha). The spatial arrangement of fragments in the study area was explicitly considered in an effort to take into account the non-random nature of fragmentation and degradation and the possibility that current species composition may reflect patterns of species turnover that existed prior to fragmentation. The data set of 57 land-snail species and 28 environmental and spatial variables was analysed using canonical correspondence analysis and partial canonical correspondence analysis. Results, Fragment age, mean shape complexity (i.e. a landscape-scale measure of shape complexity), altitude, and the spatial variables x (longitude), y (latitude) and y2 explained significant variation in land-snail species composition. None of the three nominal variables quantifying habitat degradation was significantly correlated with variation in species composition. The independent effects of fragment age and mean shape complexity were similar. The combined effect of the spatial variables alone was larger than the independent effects of fragment age, mean shape complexity or altitude, but was of the same order of magnitude. The total variation explained by the spatial variables was comparable to the total non-spatial variation accounted for by fragment age, mean shape complexity and altitude. Main conclusions, Fragment age was found to be one of only two key determinants (the other was shape complexity at the landscape scale) driving fragmentation-related changes in community composition. The influence of pre-fragmentation patterns of species turnover on assemblage structure can be stronger than the effects of fragmentation measures, such as age, and may override the effects of forest degradation. Thus, strong patterns of pre-existing turnover may potentially confound interpretation of the effects of forest fragmentation and degradation. [source] Thin basement membrane nephropathy and IgA glomerulonephritis: Can they be distinguished without renal biopsy?NEPHROLOGY, Issue 5 2007DAVID K PACKHAM SUMMARY: Background: Thin basement membrane nephropathy (TBMN) and IgA glomerulonephritis (IgA gn) are the most common primary glomerular conditions diagnosed on renal biopsy, performed for microscopic haematuria or microscopic haematuria with proteinuria. While up to 50% of patients with IgA gn will develop chronic renal failure, most patients with TBMN enjoy an excellent prognosis. Because TBMN is estimated to occur in up to 1% of the general population, differentiation between the two conditions without resort to renal biopsy is desirable. Methods: This retrospective analysis of 248 patients diagnosed on renal biopsy as having either TBMN or IgA gn, sought to identify clinical or biochemical factors which would have enabled confident differentiation between the two conditions to be made without resort to renal biopsy. Results: No single clinical or pathological variable adequately discriminated between the two conditions. Impaired renal function and heavy proteinuria were highly specific for IgA gn but lacked sensitivity in differentiating from TBMN. Isolated microscopic haematuria (IMH) was a more common finding in patients diagnosed with TBMN but, as a discriminator between TBMN and IgA gn, lacked sufficient specificity. However, if assumptions were made based on the differing incidence of a positive family history between IgA gn and TBMN, then specificity of >99% could be achieved. Conclusion: TBMN and IgA gn cannot be distinguished on the basis of clinical or pathological variables alone. However, in patients with IMH and a positive family history of either IMH or biopsy-proven TBMN, there is usually no need for renal biopsy. [source] A hybrid model of anaerobic E. coli GJT001: Combination of elementary flux modes and cybernetic variablesBIOTECHNOLOGY PROGRESS, Issue 5 2008Jin Il Kim Flux balance analysis (FBA) in combination with the decomposition of metabolic networks into elementary modes has provided a route to modeling cellular metabolism. It is dependent, however, on the availability of external fluxes such as substrate uptake or growth rate before estimates can become available of intracellular fluxes. The framework classically does not allow modeling of metabolic regulation or the formulation of dynamic models except through dynamic measurement of external fluxes. The cybernetic modeling approach of Ramkrishna and coworkers provides a dynamic framework for modeling metabolic systems because of its focus on describing regulatory processes based on cybernetic arguments and hence has the capacity to describe both external and internal fluxes. In this article, we explore the alternative of developing hybrid models combining cybernetic models for the external fluxes with the flux balance approach for estimation of the internal fluxes. The approach has the merit of the simplicity of the early cybernetic models and hence computationally facile while also providing detailed information on intracellular fluxes. The hybrid model of this article is based on elementary mode decomposition of the metabolic network. The uptake rates for the various elementary modes are combined using global cybernetic variables based on maximizing substrate uptake rates. Estimation of intracellular metabolism is based on its stoichiometric coupling with the external fluxes under the assumption of (pseudo-) steady state conditions. The set of parameters of the hybrid model was estimated with the aid of nonlinear optimization routine, by fitting simulations with dynamic experimental data on concentrations of biomass, substrate, and fermentation products. The hybrid model estimations were tested with FBA (based on measured substrate uptake rate) for two different metabolic networks (one is a reduced network which fixes ATP contribution to the biomass and maintenance requirement of ATP, and the other network is a more complex network which has a separate reaction for maintenance.) for the same experiment involving anaerobic growth of E. coli GJT001. The hybrid model estimated glucose consumption and all fermentation byproducts to better than 10%. The FBA makes similar estimations of fermentation products, however, with the exception of succinate. The simulation results show that the global cybernetic variables alone can regulate the metabolic reactions obtaining a very satisfactory fit to the measured fermentation byproducts. In view of the hybrid model's ability to predict biomass growth and fermentation byproducts of anaerobic E. coli GJT001, this reduced order model offers a computationally efficient alternative to more detailed models of metabolism and hence useful for the simulation of bioreactors. [source] | ||||||||||