Islamist movements at crossroads: the choice between ideology and context-driven approach to politics. Case study on the Hashemite Kingdom of Jordan

The aim of the paper is to analyse the ongoing transformation process within the Islamist movements using the example of the moderate Islamic Action Front party in Jordan. The dilemma of participation in the 2010 general elections raised tensions between the Muslim Brotherhood in Jordan and its political wing, the Islamic Action Front, and between doves and hawks of the same organizations. Internal debate on the future has started recently among different groups within the Islamist movement in Jordan. The research is based on the author‘s recent field experience in Jordan (April–July 2010, Andrew W. Mellon Fellowship at the American Centre of Oriental Research, Amman, Jordan). The author also conducted research in Syria, Lebanon, Palestine and Egypt, where several interviews were carried out with leading and lower level Islamist politicians. The dynamic changes within Islamic Action Front Party in Jordan and its relation with the regime has been used as reference point. The main question of the research was aa how the changing political and regional context shapes decisions of the Islamist with special attention to the acceptance of democratic values and human rights, political participation, and the meanings of Islamic values in the 21st century, possible cooperation with secular parties/movements/the regime.

Modeling the Impacts of Climate Change on Phytogeographical Units. A Case Study of the Moesz Line

Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling.