Wirtschaftspolitik und wirtschaftliche Aussichten in den Industrieländern

Der vorliegende Bericht, der neunte in dieser Reihe, ist das Ergebnis einer Konferenz unabhängiger Ökonomen aus Japan, Westeuropa und Nordamerika. Wie auch im letzten Jahr, stand die Wirtschaftspolitik, die in den Ländern dieser drei Regionen betrieben wurde, im Mittelpunkt der Gespräche. Die Konferenz fand vom 2. -4. November 1977 bei der Brookings Institution in Washington unter dem Vorsitz des Unterzeichneten statt und wurde vom Institut für Weltwirtschaft, dem Japan Economic Research Center und der Brookings Institution gefördert. Die wirtschaftspolitischen Ergebnisse dieser Tagung wurden in einer Pressemitteilung zusammengefaßt und veröffentlicht. Dieser Bericht gibt Auskunft über den Hintergrund, auf dem die wirtschaftspolitischen Empfehlungen zustande kamen. Der erste Abschnitt beschreibt die wirtschaftliche Entwicklung während des vergangenen Jahres in jeder der drei Regionen. Dabei wird der Tatsache Rechnung getragen, daß die wirtschaftliche Entwicklung dieser Länder sowohl Gemeinsamkeiten als auch Unterschiede aufweist. Anschließend wird ein Ausblick für das kommende Jahr gegeben, und die wechselseitigen Einflüsse zwischen den Regionen werden kurz untersucht. Danach folgt eine Diskussion jener Probleme, die in allen oder zumindest den meisten Ländern bestehen und einer befriedigenderen wirtschaftlichen Entwicklung im Wege stehen. Der Bericht endet mit der Darstellung der wirtschaftspolitischen Empfehlungen der Gruppe. Die Tagung und dieser Bericht wurden durch die Förderung durch den German Marshall Fund ermöglicht, dessen Präsident, Robert Gerald Livingston, der Konferenz beiwohnte. Die Teilnehmer der Konferenz, die die wirtschaftspolitischen Empfehlungen erarbeiteten, taten dies im eigenen Namen, nicht aber für die Institute, denen sie angehören. Dieser Bericht wird in Europa vom Institut für Weltwirtschaft, in Japan vom Japan Economic Research Center und in Nordamerika von der Brookings Institution publiziert. --

A method for estimation of elasticities in metabolic networks using steady state and dynamic metabolomics data and linlog kinetics

BACKGROUND: Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living cells. So far dynamic metabolic models generally have been based on mechanistic rate equations which often contain so many parameters that their identifiability from experimental data forms a serious problem. Recently, approximative rate equations, based on the linear logarithmic (linlog) format have been proposed as a suitable alternative with fewer parameters. RESULTS: In this paper we present a method for estimation of the kinetic model parameters, which are equal to the elasticities defined in Metabolic Control Analysis, from metabolite data obtained from dynamic as well as steady state perturbations, using the linlog kinetic format. Additionally, we address the question of parameter identifiability from dynamic perturbation data in the presence of noise. The method is illustrated using metabolite data generated with a dynamic model of the glycolytic pathway of Saccharomyces cerevisiae based on mechanistic rate equations. Elasticities are estimated from the generated data, which define the complete linlog kinetic model of the glycolysis. The effect of data noise on the accuracy of the estimated elasticities is presented. Finally, identifiable subset of parameters is determined using information on the standard deviations of the estimated elasticities through Monte Carlo (MC) simulations. CONCLUSION: The parameter estimation within the linlog kinetic framework as presented here allows the determination of the elasticities directly from experimental data from typical dynamic and/or steady state experiments. These elasticities allow the reconstruction of the full kinetic model of Saccharomyces cerevisiae, and the determination of the control coefficients. MC simulations revealed that certain elasticities are potentially unidentifiable from dynamic data only. Addition of steady state perturbation of enzyme activities solved this problem

Climate change and alpine stream biology: progress, challenges, and opportunities for the future

In alpine regions worldwide, climate change is dramatically altering ecosystems and affecting biodiversity in many ways. For streams, receding alpine glaciers and snowfields, paired with altered precipitation regimes, are driving shifts in hydrology, species distributions, basal resources, and threatening the very existence of some habitats and biota. Alpine streams harbour substantial species and genetic diversity due to significant habitat insularity and environmental heterogeneity. Climate change is expected to affect alpine stream biodiversity across many levels of biological resolution from micro‐ to macroscopic organisms and genes to communities. Herein, we describe the current state of alpine stream biology from an organism‐focused perspective. We begin by reviewing seven standard and emerging approaches that combine to form the current state of the discipline. We follow with a call for increased synthesis across existing approaches to improve understanding of how these imperiled ecosystems are responding to rapid environmental change. We then take a forward‐looking viewpoint on how alpine stream biologists can make better use of existing data sets through temporal comparisons, integrate remote sensing and geographic information system (GIS) technologies, and apply genomic tools to refine knowledge of underlying evolutionary processes. We conclude with comments about the future of biodiversity conservation in alpine streams to confront the daunting challenge of mitigating the effects of rapid environmental change in these sentinel ecosystems

Climate-Induced Range Contraction of a Rare Alpine Aquatic Invertebrate

Climate warming poses a serious threat to alpine-restricted species worldwide, yet few studies have empirically documented climate-induced changes in distributions. The rare stonefly, Zapada glacier (Baumann and Gaufin), endemic to alpine streams of Glacier National Park (GNP), Montana, was recently petitioned for listing under the US Endangered Species Act because of climate-change-induced glacier loss, yet little was known about its current status and distribution. We resampled streams throughout the historical distribution of Z. glacier to investigate trends in occurrence associated with changes in temperature and glacial extent. The current geographic distribution of the species was assessed using morphological characteristics of adults and DNA barcoding of nymphs. Bayesian phylogenetic analysis of mtDNA data revealed 8 distinct clades of the genus corresponding with 7 known species from GNP, and one potentially cryptic species. Climate model simulations indicate that average summer air temperature increased (0.67-1.00 degrees C) during the study period (1960-2012), and glacial surface area decreased by approximate to 35% from 1966 to 2005. We detected Z. glacier in only 1 of the 6 historically occupied streams and at 2 new locations in GNP. These results suggest that an extremely restricted historical distribution of Z. glacier in GNP has been further reduced over the past several decades by an upstream retreat to higher, cooler sites as water temperatures increased and glacial masses decreased. More research is urgently needed to determine the status, distribution, and vulnerability of Z. glacier and other alpine stream invertebrates threatened by climate change in mountainous ecosystems

Correction: Loss of Genetic Diversity and Increased Subdivision in an Endemic Alpine Stonefly Threatened by Climate Change.

[This corrects the article DOI: 10.1371/journal.pone.0157386.]

Data from: Demographic modelling reveals a history of divergence with gene flow for a glacially tied stonefly in a changing post-Pleistocene landscape

Aim: Climate warming is causing extensive loss of glaciers in mountainous regions, yet our understanding of how glacial recession influences evolutionary processes and genetic diversity is limited. Linking genetic structure with the influences shaping it can improve understanding of how species respond to environmental change. Here, we used genome-scale data and demographic modelling to resolve the evolutionary history of Lednia tumana, a rare, aquatic insect endemic to alpine streams. We also employed a range of widely used data filtering approaches to quantify how they influenced population structure results. Location: Alpine streams in the Rocky Mountains of Glacier National Park, Montana, USA. Taxon: Lednia tumana, a stonefly (Order Plecoptera) in the family Nemouridae. Methods: We generated single nucleotide polymorphism data through restriction-site associated DNA sequencing to assess contemporary patterns of genetic structure for 11 L. tumana populations. Using identified clusters, we assessed demographic history through model selection and parameter estimation in a coalescent framework. During population structure analyses, we filtered our data to assess the influence of singletons, missing data and total number of markers on results. Results: Contemporary patterns of population structure indicate that L. tumana exhibits a pattern of isolation-by-distance among populations within three genetic clusters that align with geography. Mean pairwise genetic differentiation (FST) among populations was 0.033. Coalescent-based demographic modelling supported divergence with gene flow among genetic clusters since the end of the Pleistocene (~13-17 kya), likely reflecting the south-to-north recession of ice sheets that accumulated during the Wisconsin glaciation. Main conclusions: We identified a link between glacial retreat, evolutionary history and patterns of genetic diversity for a range-restricted stonefly imperiled by climate change. This finding included a history of divergence with gene flow, an unexpected conclusion for a mountaintop species. Beyond L. tumana, this study demonstrates the complexity of assessing genetic structure for weakly differentiated species, shows the degree to which rare alleles and missing data may influence results, and highlights the usefulness of genome-scale data to extend population genetic inquiry in non-model species

Sampling and demographic information for 116 <i>Lednia tumana</i> individuals.

<p>Shaded boxes indicate adjacent sites that were pooled for combined analysis, and the Combined n refers to the combined totals of those sites.</p

Estimates of G_st analog 95% confidence intervals from SMOGD [29] for historic and 2010 populations of <i>L</i>. <i>tumana</i>.

<p>Estimates of G_st analog 95% confidence intervals from SMOGD [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157386#pone.0157386.ref029" target="_blank">29</a>] for historic and 2010 populations of <i>L</i>. <i>tumana</i>.</p