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Research on collective resilience processes still lacks a detailed understanding of psychological mechanisms at work when groups cope with adverse conditions, i.e., long-term processes, and how such mechanisms affect physical and mental well-being. As collective resilience will play a crucial part in facing looming climate change-related events such as floods, it is important to investigate these processes further. To this end, this study takes a novel holistic approach by combining resilience research, social psychology, and an archeological perspective to investigate the role of social identity as a collective resilience factor in the past and present. We hypothesize that social identification buffers against the negative effects of environmental threats in participants, which increases somatic symptoms related to stress, in a North Sea region historically prone to floods. A cross-sectional study (N = 182) was conducted to analyze the moderating effects of social identification on the relations between perceived threat of North Sea floods and both well-being and life satisfaction. The results support our hypothesis that social identification attenuates the relationship between threat perception and well-being, such that the relation is weaker for more strongly identified individuals. Contrary to our expectations, we did not find this buffering effect to be present for life satisfaction. Future resilience studies should further explore social identity as a resilience factor and how it operates in reducing environmental stress put on individuals and groups. Further, to help communities living in flood-prone areas better cope with future environmental stress, we recommend implementing interventions strengthening their social identities and hence collective resilience.
Die Auswirkungen des globalen Klimawandels werden zunehmend sichtbar. In Deutschland haben sich die Jahresdurchschnittstemperatur im vergangenen Jahrhundert um 1 °C und die jährliche Niederschlagsmenge um + 9 % erhöht. Bezogen auf die Jahreszeiten ergeben sich jedoch deutliche Unterschiede, während die Sommermonate zunehmend niederschlagsärmer werden, erhöht sich die Niederschlagsmenge in den Wintermonaten überproportional (Schönwiese, 2002; Schönwiese & Janoschitz, 2005). Welche Folgen diese Veränderungen für die Waldökosysteme haben werden, wird in der Forstwirtschaft zu nehmend diskutiert. Allerdings gibt es bisher nur ökophysiologische, autökologische Ansätze. Synökologische Ansätze, die insbesondere auch die potenziellen Schadinsekten und damit die indirekten Auswirkungen des Klimawandels berücksichtigen, fehlen zumeist. Dies gilt auch für die Rotbuche deren waldbauliche Zukunft in jüngster Zeit diskutiert wurde (Rennenberg & al., 2004; Ammer & al., 2005; Kölling, & al., 2005).
This chapter argues that paying attention to the weather and its associated processes of geological, biological, and social weathering can destabilize knowledge traditions that insist on dichotomies. Looking to specific histories and current conditions in Guyana and Suriname, this chapter shows how notions of weathering can accommodate a wide range of referents, ranging from the weathering of rock to socio-political and historical afterlives of violent colonial displacements.
Climate change has become one of the most prominent concerns globally. In this paper, the authors study the transition risk of greenhouse gas emission reduction in structural environmental-macroeconomic DSGE models. First, they analyze the uncertainty in model prediction on the effect of unanticipated and pre-announced carbon price increases. Second, they conduct optimal model-robust policy in different settings. They find that reducing emissions by 40% causes 0.7% to 4% output loss with 2% on average. Pre-announcement of carbon prices affects the inflation dynamics significantly. The central bank should react slightly less to inflation and output growth during the transition risk. With optimal carbon price designs, it should react even less to inflation, and more to output growth.
This thesis develops a conceptual framework for a better understanding of the impact of slow-onset climate and environmental changes on human migration in developing countries. Its regional focus is on the West African Sahel, where the majority of the population depends on agriculture and thus is highly vulnerable to environmental changes. Migration from fragile environments is predominantly considered one of several household strategies to adapt to and minimise the risk of environmental stress. Based on qualitative and quantitative data from two selected rural study areas, Bandiagara in Mali and Linguère in Senegal, this thesis analyses the drivers of migration from the two areas.
The findings illustrate that, even though people highly depend on the natural environment, migration motives are manifold and that migration often is not a household strategy to cope with environmental changes. Although environmental conditions shape migration in the region and the migrants’ support is crucial for most households, environmental stress plays a relatively small role as a driver of migration - at least in Mali, where it is considerably less important than in Senegal. On the contrary, migration is often driven by better opportunities elsewhere rather than by livelihood stressors in the home area. Particularly the migration of young people is often an individual rather than a household decision and influenced by individual aspirations, such as aspirations for consumer goods or a better future, rather than by environmental stress.
This thesis claims that research should consider people’s capabilities to migrate or to stay as well as their individual aspirations and preferences - in addition to the household’s needs and the opportunities elsewhere. This is important in order to explain why some people stay in and others migrate from an area affected by environmental stress, though living under similar conditions. Depending on people’s capabilities to choose freely between staying and migrating and their preferences and aspirations for one or the other activity, people can either be “voluntary migrants”, “voluntary non-migrants”, “forced migrants” or “trapped people”.
Moreover, it is important to consider social trends and transformation processes in the analysis of the linkages between environment change and migration. Higher education levels and aspirations to a “modern” lifestyle among young people, for instance, might decrease the impact of environmental factors on migration, despite worsening environmental conditions.
New particle formation in the upper free troposphere is a major global source of cloud condensation nuclei (CCN)1,2,3,4. However, the precursor vapours that drive the process are not well understood. With experiments performed under upper tropospheric conditions in the CERN CLOUD chamber, we show that nitric acid, sulfuric acid and ammonia form particles synergistically, at rates that are orders of magnitude faster than those from any two of the three components. The importance of this mechanism depends on the availability of ammonia, which was previously thought to be efficiently scavenged by cloud droplets during convection. However, surprisingly high concentrations of ammonia and ammonium nitrate have recently been observed in the upper troposphere over the Asian monsoon region5,6. Once particles have formed, co-condensation of ammonia and abundant nitric acid alone is sufficient to drive rapid growth to CCN sizes with only trace sulfate. Moreover, our measurements show that these CCN are also highly efficient ice nucleating particles—comparable to desert dust. Our model simulations confirm that ammonia is efficiently convected aloft during the Asian monsoon, driving rapid, multi-acid HNO3–H2SO4–NH3 nucleation in the upper troposphere and producing ice nucleating particles that spread across the mid-latitude Northern Hemisphere.
Observed global and European spatiotemporal related fields of surface air temperature, mean-sea-level pressure and precipitation are analyzed statistically with respect to their response to external forcing factors such as anthropogenic greenhouse gases, anthropogenic sulfate aerosol, solar variations and explosive volcanism, and known internal climate mechanisms such as the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). As a first step, a principal component analysis (PCA) is applied to the observed spatiotemporal related fields to obtain spatial patterns with linear independent temporal structure. In a second step, the time series of each of the spatial patterns is subject to a stepwise regression analysis in order to separate it into signals of the external forcing factors and internal climate mechanisms as listed above as well as the residuals. Finally a back-transformation leads to the spatiotemporally related patterns of all these signals being intercompared. Two kinds of significance tests are applied to the anthropogenic signals. First, it is tested whether the anthropogenic signal is significant compared with the complete residual variance including natural variability. This test answers the question whether a significant anthropogenic climate change is visible in the observed data. As a second test the anthropogenic signal is tested with respect to the climate noise component only. This test answers the question whether the anthropogenic signal is significant among others in the observed data. Using both tests, regions can be specified where the anthropogenic influence is visible (second test) and regions where the anthropogenic influence has already significantly changed climate (first test).
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
Background: In the face of ongoing climate warming, vector-borne diseases are expected to increase in Europe, including tick-borne diseases (TBD). The most abundant tick-borne diseases in Germany are Tick-Borne Encephalitis (TBE) and Lyme Borreliosis (LB), with Ixodes ricinus as the main vector.
Methods: In this study, we display and compare the spatial and temporal patterns of reported cases of human TBE and LB in relation to some associated factors. The comparison may help with the interpretation of observed spatial and temporal patterns.
Results: The spatial patterns of reported TBE cases show a clear and consistent pattern over the years, with many cases in the south and only few and isolated cases in the north of Germany. The identification of spatial patterns of LB disease cases is more difficult due to the different reporting practices in the individual federal states. Temporal patterns strongly fluctuate between years, and are relatively synchronized between both diseases, suggesting common driving factors. Based on our results we found no evidence that weather conditions affect the prevalence of both diseases. Both diseases show a gender bias with LB bing more commonly diagnosed in females, contrary to TBE being more commonly diagnosed in males.
Conclusion: For a further investigation of of the underlying driving factors and their interrelations, longer time series as well as standardised reporting and surveillance system would be required.
A list of authors and their affiliations appears at the end of the paper New-particle formation is a major contributor to urban smog, but how it occurs in cities is often puzzling. If the growth rates of urban particles are similar to those found in cleaner environments (1–10 nanometres per hour), then existing understanding suggests that new urban particles should be rapidly scavenged by the high concentration of pre-existing particles. Here we show, through experiments performed under atmospheric conditions in the CLOUD chamber at CERN, that below about +5 degrees Celsius, nitric acid and ammonia vapours can condense onto freshly nucleated particles as small as a few nanometres in diameter. Moreover, when it is cold enough (below −15 degrees Celsius), nitric acid and ammonia can nucleate directly through an acid–base stabilization mechanism to form ammonium nitrate particles. Given that these vapours are often one thousand times more abundant than sulfuric acid, the resulting particle growth rates can be extremely high, reaching well above 100 nanometres per hour. However, these high growth rates require the gas-particle ammonium nitrate system to be out of equilibrium in order to sustain gas-phase supersaturations. In view of the strong temperature dependence that we measure for the gas-phase supersaturations, we expect such transient conditions to occur in inhomogeneous urban settings, especially in wintertime, driven by vertical mixing and by strong local sources such as traffic. Even though rapid growth from nitric acid and ammonia condensation may last for only a few minutes, it is nonetheless fast enough to shepherd freshly nucleated particles through the smallest size range where they are most vulnerable to scavenging loss, thus greatly increasing their survival probability. We also expect nitric acid and ammonia nucleation and rapid growth to be important in the relatively clean and cold upper free troposphere, where ammonia can be convected from the continental boundary layer and nitric acid is abundant from electrical storms.