Work and economic security in the 21st century

In recent decades there has been a transformation of two central concepts of modernity – labour and the household. Ela Bhatt – the founder of the Self-Employed Women’s Association of India (SEWA), has made an important contribution to this transformation. Through the emergence of unions such as SEWA, the notion of who represents labour is being broadened; the marginalised are finding an institutional voice. Increasingly, the household is being recognised as a site of both production and reproduction. SEWA is not a traditional trade union that aims, through collective bargaining with an employer, to improve its members’ wages and working conditions as sellers of their labour power. Instead, it aims to empower women economically in the informal economy by bringing them into the mainstream economy as owners of their labour. The union dimension of SEWA builds their collective power through struggle; the cooperative dimension translates their bargaining power into the economic and social development of its members and their community. Besides, Bhatt’s approach to the self-employed was a direct challenge to the ILO’s tripartism when it was established in the early seventies. The first part of the paper provides a short biography of Ela Bhatt, describes the origins of SEWA, analyses a ‘classification struggle’ over how and who is to define what a worker is. In the second part the author considers SEWAs innovative organizing strategy and is rethinking modernity in the labour context. In the conclusion the paper discusses the lessons that can be learnt from Ela Bhatt.

A Modeling Analysis of Changing Global Land Use as affected by Changing Demands for Wood Products

The 21st century has brought new challenges for forest management at a time when globalization in world trade is increasing and global climate change is becoming increasingly apparent. In addition to various goods and services like food, feed, timber or biofuels being provided to humans, forest ecosystems are a large store of terrestrial carbon and account for a major part of the carbon exchange between the atmosphere and the land surface. Depending on the stage of the ecosystems and/or management regimes, forests can be either sinks, or sources of carbon. At the global scale, rapid economic development and a growing world population have raised much concern over the use of natural resources, especially forest resources. The challenging question is how can the global demands for forest commodities be satisfied in an increasingly globalised economy, and where could they potentially be produced? For this purpose, wood demand estimates need to be integrated in a framework, which is able to adequately handle the competition for land between major land-use options such as residential land or agricultural land. This thesis is organised in accordance with the requirements to integrate the simulation of forest changes based on wood extraction in an existing framework for global land-use modelling called LandSHIFT. Accordingly, the following neuralgic points for research have been identified: (1) a review of existing global-scale economic forest sector models (2) simulation of global wood production under selected scenarios (3) simulation of global vegetation carbon yields and (4) the implementation of a land-use allocation procedure to simulate the impact of wood extraction on forest land-cover. Modelling the spatial dynamics of forests on the global scale requires two important inputs: (1) simulated long-term wood demand data to determine future roundwood harvests in each country and (2) the changes in the spatial distribution of woody biomass stocks to determine how much of the resource is available to satisfy the simulated wood demands. First, three global timber market models are reviewed and compared in order to select a suitable economic model to generate wood demand scenario data for the forest sector in LandSHIFT. The comparison indicates that the ‘Global Forest Products Model’ (GFPM) is most suitable for obtaining projections on future roundwood harvests for further study with the LandSHIFT forest sector. Accordingly, the GFPM is adapted and applied to simulate wood demands for the global forestry sector conditional on selected scenarios from the Millennium Ecosystem Assessment and the Global Environmental Outlook until 2050. Secondly, the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model is utilized to simulate the change in potential vegetation carbon stocks for the forested locations in LandSHIFT. The LPJ data is used in collaboration with spatially explicit forest inventory data on aboveground biomass to allocate the demands for raw forest products and identify locations of deforestation. Using the previous results as an input, a methodology to simulate the spatial dynamics of forests based on wood extraction is developed within the LandSHIFT framework. The land-use allocation procedure specified in the module translates the country level demands for forest products into woody biomass requirements for forest areas, and allocates these on a five arc minute grid. In a first version, the model assumes only actual conditions through the entire study period and does not explicitly address forest age structure. Although the module is in a very preliminary stage of development, it already captures the effects of important drivers of land-use change like cropland and urban expansion. As a first plausibility test, the module performance is tested under three forest management scenarios. The module succeeds in responding to changing inputs in an expected and consistent manner. The entire methodology is applied in an exemplary scenario analysis for India. A couple of future research priorities need to be addressed, particularly the incorporation of plantation establishments; issue of age structure dynamics; as well as the implementation of a new technology change factor in the GFPM which can allow the specification of substituting raw wood products (especially fuelwood) by other non-wood products.

Das Einzugsgebiet der Fulda - Untersuchung der Methoden der Hochwasserstatistik im Zeichen des Klimawandels

Numerous studies have proven an effect of a probable climate change on the hydrosphere’s different subsystems. In the 21st century global and regional redistribution of water has to be expected and it is very likely that extreme weather phenomenon will occur more frequently. From a global view the flood situation will exacerbate. In contrast to these discoveries the classical approach of flood frequency analysis provides terms like “mean flood recurrence interval”. But for this analysis to be valid there is a need for the precondition of stationary distribution parameters which implies that the flood frequencies are constant in time. Newer approaches take into account extreme value distributions with time-dependent parameters. But the latter implies a discard of the mentioned old terminology that has been used up-to-date in engineering hydrology. On the regional scale climate change affects the hydrosphere in various ways. So, the question appears to be whether in central Europe the classical approach of flood frequency analysis is not usable anymore and whether the traditional terminology should be renewed. In the present case study hydro-meteorological time series of the Fulda catchment area (6930 km²), upstream of the gauging station Bonaforth, are analyzed for the time period 1960 to 2100. At first a distributed catchment area model (SWAT2005) is build up, calibrated and finally validated. The Edertal reservoir is regulated as well by a feedback control of the catchments output in case of low water. Due to this intricacy a special modeling strategy has been necessary: The study area is divided into three SWAT basin models and an additional physically-based reservoir model is developed. To further improve the streamflow predictions of the SWAT model, a correction by an artificial neural network (ANN) has been tested successfully which opens a new way to improve hydrological models. With this extension the calibration and validation of the SWAT model for the Fulda catchment area is improved significantly. After calibration of the model for the past 20th century observed streamflow, the SWAT model is driven by high resolution climate data of the regional model REMO using the IPCC scenarios A1B, A2, and B1, to generate future runoff time series for the 21th century for the various sub-basins in the study area. In a second step flood time series HQ(a) are derived from the 21st century runoff time series (scenarios A1B, A2, and B1). Then these flood projections are extensively tested with regard to stationarity, homogeneity and statistical independence. All these tests indicate that the SWAT-predicted 21st-century trends in the flood regime are not significant. Within the projected time the members of the flood time series are proven to be stationary and independent events. Hence, the classical stationary approach of flood frequency analysis can still be used within the Fulda catchment area, notwithstanding the fact that some regional climate change has been predicted using the IPCC scenarios. It should be noted, however, that the present results are not transferable to other catchment areas. Finally a new method is presented that enables the calculation of extreme flood statistics, even if the flood time series is non-stationary and also if the latter exhibits short- and longterm persistence. This method, which is called Flood Series Maximum Analysis here, enables the calculation of maximum design floods for a given risk- or safety level and time period.

Mobiles Lernen

In ihrer Arbeit "Mobiles Lernen. Analyse des Wissenschaftsprozesses der britischen und deutschsprachigen medienpädagogischen und erziehungswissenschaftlichen Mobile-Learning-Diskussion." zeichnet Judith Seipold die Phasen und Entwicklungslinien der bisherigen und naturwüchsigen Diskussion um das Mobile Lernen nach. Dabei eröffnet sie mit ihrer Analyse des vornehmlich britischen Wissenschaftsprozesses des Mobilen Lernens ab Beginn des 21. Jahrhunderts den Blick auf die Struktur der medienpädagogischen und erziehungswissenschaftlichen Mobile-Learning-Diskussion, auf deren Kontexte, Bezugspunkte, Perspektiven und theoretische Schwerpunkte, aber auch Erfolge und Problembereiche in der praktischen Umsetzung des Lernens mit Mobiltechnologien in formalisierten Lernkontexten wie dem des Schulunterrichts. Auf diese Weise liefert die Autorin eine Systematik, die nicht nur die britische Diskussion für die deutschsprachige Medienpädagogik verfügbar macht, sondern auch eine neue und systematisch begründete Reflexionsebene für eine aktuelle medienpädagogische Entwicklung – das Mobile Lernen – bildet. Zunächst widmet sich die Autorin der Analyse des Wissenschaftsprozesses der bisherigen britischen und teils auch der deutschsprachigen Mobile-Learning-Diskussion. Um diesen Prozess in seiner Struktur greifbar zu machen, skizziert sie die Bezugsdisziplinen, aus denen die medienpädagogische und erziehungswissenschaftliche Mobile-Learning-Forschung schöpft, arbeitet die Legitimationsbasis auf, auf die sich Mobiles Lernen stützt, zeichnet die historische Entwicklung der Diskussion nach, die sowohl Alltagsnutzung von Mobiltechnologien als auch den Fachdiskurs einschließt, und erläutert innerhalb ihres Modells der Phasen und Entwicklungslinien Mobilen Lernens Theorien, Konzepte und Modelle, die in der Mobile-Learning-Community als zentral für Analyse und Planung Mobilen Lernens erachtet werden. Konzepte und Modelle, die in der Mobile-Learning-Diskussion die Rolle der Lernenden in das Zentrum der Betrachtungen rücken und eine explizite Handlungsorientierung unterstützen, sind Kernbereich des theoriebasierten Teils der Arbeit. Überlegungen zu einer „Sozio-kulturellen Ökologie Mobilen Lernens“, zu „user-generated contexts“ und zu einer „kulturökologisch informierten Didaktik des Mobilen Lernens“ sind dabei sowohl reflektierende Einordnung aktueller Konzepte und Modelle als auch theoretische und konzeptionelle Basis für die praktische Umsetzung Mobilen Lernens. Um die Rolle der Handlungskompetenzen, kulturellen Praktiken und Strukturen der Lerner bei der Nutzung von Mobiltechnologien für Lernen analytisch zu fassen, finden im Praxis-Kapitel Planungs- und Analyseschemata unter Rückgriff auf Beispiele aus der Praxisforschung und der Implementierung mobilen Lernens in den Schulunterricht Anwendung. Ihre Erörterungen rahmt die Autorin abschließend kritisch und weist zum einen auf bildungspolitische, strukturelle und handlungspraktische Implikationen hin, die sich aus der Mobile-Learning-Diskussion ergeben; zum anderen lenkt sie das Augenmerk auf Gegensätze und Dialektiken des Mobilen Lernens, die sich im Spannungsfeld zwischen alltäglicher mobiler Mediennutzung und der teils theoretisch informierten schulischen Verwendung von Mobiltechnologien zum Lernen entfalten. Sie gilt es, im weiteren Verlauf der Diskussion zu hinterfragen und aufzulösen.

The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.