Suchergebnisse

Diese Ausgabe des "Infodienst Migration" enthält u.a. einen Länderbericht über den westafrikanischen Staat Ghana, der über die Menschenrechtssituation im Land und über Programme und Maßnahmen kirchlicher Organisationen in Ghana informiert. Außerdem gibt ein Beitrag einen Eindruck von der Lebenssituation von Ghanaern in Hamburg. (DÜI-Hff)

AbstractDecision making in environmental projects is usually complex because of heterogeneous stakeholder interests, multiple objectives, long planning and implementation processes, and uncertain outcomes. Conflicting stakeholder interests in particular are often an important impediment to the realization and success of projects. Multiple criteria decision analysis (MCDA) methods are potentially useful for facilitating conflict resolution among stakeholder groups. However, some studies that have applied MCDA methods indicate that users are often skeptical about the value of MCDA methods and prefer the freedom of unaided decision making. We examine whether and how multi‐attribute value theory (MAVT), a particular kind of MCDA, facilitates conflict resolution in environmental projects. Therefore, the MAVT method is applied to a specific river rehabilitation project in Switzerland (Thur River). The main questions are: (1) Can the MAVT method predict the final preferences of stakeholders and therefore anticipate conflicts at an early stage? (2) Do stakeholders reconsider and change their preferences after using the MAVT method? (3) If they do, does this result in more consensus‐oriented decisions? We find that the principal advantage of the method in our case was not the prediction of stakeholders' final preferences, but rather the methods' ability to facilitate more consensus‐oriented decisions. The paper discusses possible reasons for this finding and concludes with recommendations for future applications of the MAVT method in environmental decision making. Copyright © 2006 John Wiley & Sons, Ltd.

A Bayesian uncertainty analysis of 12 parameters of the Bern2.5D climate model is presented. This includes an extensive sensitivity study with respect to the major statistical assumptions. Special attention is given to the parameter representing climate sensitivity. Using the framework of robust Bayesian analysis, the authors first define a nonparametric set of prior distributions for climate sensitivity S and then update the entire set according to Bayes' theorem. The upper and lower probability that S lies above 4.5°C is calculated over the resulting set of posterior distributions. Furthermore, posterior distributions under different assumptions on the likelihood function are computed. The main characteristics of the marginal posterior distributions of climate sensitivity are quite robust with regard to statistical models of climate variability and observational error. However, the influence of prior assumptions on the tails of distributions is substantial considering the important political implications. Moreover, the authors find that ocean heat change data have a considerable potential to constrain climate sensitivity.