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In the last decade, the number and dimensions of catastrophic flooding events in the Niger River Basin (NRB) have markedly increased. Despite the devastating impact of the floods on the population and the mainly agriculturally based economy of the riverine nations, awareness of the hazards in policy and science is still low. The urgency of this topic and the existing research deficits are the motivation for the present dissertation.
The thesis is an initial detailed assessment of the increasing flood risk in the NRB. The research strategy is based on four questions regarding (1) features of the change in flood risk, (2) reasons for the change in the flood regime, (3) expected changes of the flood regime given climate and land use changes, and (4) recommendations from previous analysis for reducing the flood risk in the NRB.
The question examining the features of change in the flood regime is answered by means of statistical analysis. Trend, correlation, changepoint, and variance analyses show that, in addition to the factors exposure and vulnerability, the hazard itself has also increased significantly in the NRB, in accordance with the decadal climate pattern of West Africa. The northern arid and semi-arid parts of the NRB are those most affected by the changes.
As potential reasons for the increase in flood magnitudes, climate and land use changes are attributed by means of a hypothesis-testing framework. Two different approaches, based on either data analysis or simulation, lead to similar results, showing that the influence of climatic changes is generally larger compared to that of land use changes. Only in the dry areas of the NRB is the influence of land use changes comparable to that of climatic alterations.
Future changes of the flood regime are evaluated using modelling results. First ensembles of statistically and dynamically downscaled climate models based on different emission scenarios are analyzed. The models agree with a distinct increase in temperature. The precipitation signal, however, is not coherent. The climate scenarios are used to drive an eco-hydrological model. The influence of climatic changes on the flood regime is uncertain due to the unclear precipitation signal. Still, in general, higher flood peaks are expected. In a next step, effects of land use changes are integrated into the model. Different scenarios show that regreening might help to reduce flood peaks. In contrast, an expansion of agriculture might enhance the flood peaks in the NRB. Similarly to the analysis of observed changes in the flood regime, the impacts of climate- and land use changes for the future scenarios are also most severe in the dry areas of the NRB.
In order to answer the final research question, the results of the above analysis are integrated into a range of recommendations for science and policy on how to reduce flood risk in the NRB. The main recommendations include a stronger consideration of the enormous natural climate variability in the NRB and a focus on so called “no-regret” adaptation strategies which account for high uncertainty, as well as a stronger consideration of regional differences. Regarding the prevention and mitigation of catastrophic flooding, the most vulnerable and sensitive areas in the basin, the arid and semi-arid Sahelian and Sudano-Sahelian regions, should be prioritized. Eventually, an active, science-based and science-guided flood policy is recommended. The enormous population growth in the NRB in connection with the expected deterioration of environmental and climatic conditions is likely to enhance the region´s vulnerability to flooding. A smart and sustainable flood policy can help mitigate these negative impacts of flooding on the development of riverine societies in West Africa.
Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100
(2015)
Arctic animals face dramatic habitat alteration due to ongoing climate change. Understanding how such species have responded to past glacial cycles can help us forecast their response to today's changing climate. Gray whales are among those marine species likely to be strongly affected by Arctic climate change, but a thorough analysis of past climate impacts on this species has been complicated by lack of information about an extinct population in the Atlantic. While little is known about the history of Atlantic gray whales or their relationship to the extant Pacific population, the extirpation of the Atlantic population during historical times has been attributed to whaling. We used a combination of ancient and modern DNA, radiocarbon dating and predictive habitat modelling to better understand the distribution of gray whales during the Pleistocene and Holocene. Our results reveal that dispersal between the Pacific and Atlantic was climate dependent and occurred both during the Pleistocene prior to the last glacial period and the early Holocene immediately following the opening of the Bering Strait. Genetic diversity in the Atlantic declined over an extended interval that predates the period of intensive commercial whaling, indicating this decline may have been precipitated by Holocene climate or other ecological causes. These first genetic data for Atlantic gray whales, particularly when combined with predictive habitat models for the year 2100, suggest that two recent sightings of gray whales in the Atlantic may represent the beginning of the expansion of this species' habitat beyond its currently realized range.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007–2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash–Sutcliffe efficiency of 0.72 and a Kling–Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
Cities to the rescue?
(2017)
Despite the proliferation and promise of subnational climate initiatives, the institutional architecture of transnational municipal networks (TMNs) is not well understood. With a view to close this research gap, the article empirically assesses the assumption that TMNs are a viable substitute for ambitious international action under the United Nations Framework Convention on Climate Change (UNFCCC). It addresses the aggregate phenomenon in terms of geographical distribution, central players, mitigation ambition and monitoring provisions. Examining thirteen networks, it finds that membership in TMNs is skewed toward Europe and North America while countries from the Global South are underrepresented; that only a minority of networks commit to quantified emission reductions and that these are not more ambitious than Parties to the UNFCCC; and finally that the monitoring provisions are fairly limited. In sum, the article shows that transnational municipal networks are not (yet) the representative, ambitious and transparent player they are thought to be.
John Birks
(2015)
We describe the career of John Birks as a pioneering scientist who has, over a career spanning five decades, transformed palaeoecology from a largely descriptive to a rigorous quantitative science relevant to contemporary questions in ecology and environmental change. We review his influence on students and colleagues not only at Cambridge and Bergen Universities, his places of primary employment, but also on individuals and research groups in Europe and North America. We also introduce the collection of papers that we have assembled in his honour. The papers are written by his former students and close colleagues and span many of the areas of palaeoecology to which John himself has made major contributions. These include the relationship between ecology and palaeoecology, late-glacial and Holocene palaeoecology, ecological succession, climate change and vegetation history, the role of palaeoecological techniques in reconstructing and understanding the impact of human activity on terrestrial and freshwater ecosystems and numerical analysis of multivariate palaeoecological data.
The Arctic is considered as a focal region in the ongoing climate change debate. The currently observed and predicted climate warming is particularly pronounced in the high northern latitudes. Rising temperatures in the Arctic cause progressive deepening and duration of permafrost thawing during the arctic summer, creating an ‘active layer’ with high bioavailability of nutrients and labile carbon for microbial consumption. The microbial mineralization of permafrost carbon creates large amounts of greenhouse gases, including carbon dioxide and methane, which can be released to the atmosphere, creating a positive feedback to global warming. However, to date, the microbial communities that drive the overall carbon cycle and specifically methane production in the Arctic are poorly constrained. To assess how these microbial communities will respond to the predicted climate changes, such as an increase in atmospheric and soil temperatures causing increased bioavailability of organic carbon, it is necessary to investigate the current status of this environment, but also how these microbial communities reacted to climate changes in the past. This PhD thesis investigated three records from two different study sites in the Russian Arctic, including permafrost, lake shore and lake deposits from Siberia and Chukotka. A combined stratigraphic approach of microbial and molecular organic geochemical techniques were used to identify and quantify characteristic microbial gene and lipid biomarkers. Based on this data it was possible to characterize and identify the climate response of microbial communities involved in past carbon cycling during the Middle Pleistocene and the Late Pleistocene to Holocene. It is shown that previous warmer periods were associated with an expansion of bacterial and archaeal communities throughout the Russian Arctic, similar to present day conditions. Different from this situation, past glacial and stadial periods experienced a substantial decrease in the abundance of Bacteria and Archaea. This trend can also be confirmed for the community of methanogenic archaea that were highly abundant and diverse during warm and particularly wet conditions. For the terrestrial permafrost, a direct effect of the temperature on the microbial communities is likely. In contrast, it is suggested that the temperature rise in scope of the glacial-interglacial climate variations led to an increase of the primary production in the Arctic lake setting, as can be seen in the corresponding biogenic silica distribution. The availability of this algae-derived carbon is suggested to be a driver for the observed pattern in the microbial abundance. This work demonstrates the effect of climate changes on the community composition of methanogenic archae. Methanosarcina-related species were abundant throughout the Russian Arctic and were able to adapt to changing environmental conditions. In contrast, members of Methanocellales and Methanomicrobiales were not able to adapt to past climate changes. This PhD thesis provides first evidence that past climatic warming led to an increased abundance of microbial communities in the Arctic, closely linked to the cycling of carbon and methane production. With the predicted climate warming, it may, therefore, be anticipated that extensive amounts of microbial communities will develop. Increasing temperatures in the Arctic will affect the temperature sensitive parts of the current microbiological communities, possibly leading to a suppression of cold adapted species and the prevalence of methanogenic archaea that tolerate or adapt to increasing temperatures. These changes in the composition of methanogenic archaea will likely increase the methane production potential of high latitude terrestrial regions, changing the Arctic from a carbon sink to a source.
Semi-empirical sea-level models (SEMs) exploit physically motivated empirical relationships between global sea level and certain drivers, in the following global mean temperature. This model class evolved as a supplement to process-based models (Rahmstorf (2007)) which were unable to fully represent all relevant processes. They thus failed to capture past sea-level change (Rahmstorf et al. (2012)) and were thought likely to underestimate future sea-level rise. Semi-empirical models were found to be a fast and useful tool for exploring the uncertainties in future sea-level rise, consistently giving significantly higher projections than process-based models.
In the following different aspects of semi-empirical sea-level modelling have been studied. Models were first validated using various data sets of global sea level and temperature. SEMs were then used on the glacier contribution to sea level, and to infer past global temperature from sea-level data via inverse modelling. Periods studied encompass the instrumental period, covered by tide gauges (starting 1700 CE (Common Era) in Amsterdam) and satellites (first launched in 1992 CE), the era from 1000 BCE (before CE) to present, and the full length of the Holocene (using proxy data). Accordingly different data, model formulations and implementations have been used. It could be shown in Bittermann et al. (2013) that SEMs correctly predict 20th century sea-level when calibrated with data until 1900 CE. SEMs also turned out to give better predictions than the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report (AR4, IPCC (2007)) models, for the period from 1961–2003 CE.
With the first multi-proxy reconstruction of global sea-level as input, estimate of the human-induced component of modern sea-level change and projections of future sea-level rise were calculated (Kopp et al. (2016)). It turned out with 90% confidence that more than 40 % of the observed 20th century sea-level rise is indeed anthropogenic. With the new semi-empirical and IPCC (2013) 5th assessment report (AR5) projections the gap between SEM and process-based model projections closes, giving higher credibility to both. Combining all scenarios, from strong mitigation to business as usual, a global sea-level rise of 28–131 cm relative to 2000 CE, is projected with 90% confidence. The decision for a low carbon pathway could halve the expected global sea-level rise by 2100 CE.
Present day temperature and thus sea level are driven by the globally acting greenhouse-gas forcing. Unlike that, the Milankovich forcing, acting on Holocene timescales, results mainly in a northern-hemisphere temperature change. Therefore a semi-empirical model can be driven with northernhemisphere temperatures, which makes it possible to model the main subcomponent of sea-level change over this period. It showed that an additional positive constant rate of the order of the estimated Antarctic sea-level contribution is then required to explain the sea-level evolution over the Holocene. Thus the global sea level, following the climatic optimum, can be interpreted as the sum of a temperature induced sea-level drop and a positive long-term contribution, likely an ongoing response to deglaciation coming from Antarctica.
The evolution of life on Earth has been driven by disturbances of different types and magnitudes over the 4.6 million years of Earth’s history (Raup, 1994, Alroy, 2008). One example for such disturbances are mass extinctions which are characterized by an exceptional increase in the extinction rate affecting a great number of taxa in a short interval of geologic time (Sepkoski, 1986). During the 541 million years of the Phanerozoic, life on Earth suffered five exceptionally severe mass extinctions named the “Big Five Extinctions”. Many mass extinctions are linked to changes in climate
(Feulner, 2009). Hence, the study of past mass extinctions is not only intriguing, but can also provide insights into the complex nature of the Earth system. This thesis aims at deepening our understanding of the triggers of mass extinctions and how they affected life. To accomplish this, I investigate changes in climate during two of the Big Five extinctions using a coupled climate model.
During the Devonian (419.2–358.9 million years ago) the first vascular plants and vertebrates evolved on land while extinction events occurred in the ocean (Algeo et al., 1995). The causes of these formative changes, their interactions and their links to changes in climate are still poorly understood. Therefore, we explore the sensitivity of the Devonian climate to various boundary conditions using an intermediate-complexity climate model (Brugger et al., 2019). In contrast to Le Hir et al. (2011), we find only a minor biogeophysical effect of changes in vegetation cover due to unrealistically high soil albedo values used in the earlier study. In addition, our results cannot support the strong influence of orbital parameters on the Devonian climate, as simulated with a climate model with a strongly simplified ocean model (De Vleeschouwer et al., 2013, 2014, 2017). We can only reproduce the changes in Devonian climate suggested by proxy data by decreasing atmospheric CO2. Still, finding agreement between the evolution of sea surface temperatures reconstructed from proxy data (Joachimski et al., 2009) and our simulations remains challenging and suggests a lower δ18O ratio of Devonian seawater. Furthermore, our study of the sensitivity of the Devonian climate reveals a prevailing mode of climate variability on a timescale of decades to centuries. The quasi-periodic ocean temperature fluctuations are linked to a physical mechanism of changing sea-ice cover, ocean convection and overturning in high northern latitudes.
In the second study of this thesis (Dahl et al., under review) a new reconstruction of atmospheric CO2 for the Devonian, which is based on CO2-sensitive carbon isotope fractionation in the earliest vascular plant fossils, suggests a much earlier drop of atmo- spheric CO2 concentration than previously reconstructed, followed by nearly constant CO2 concentrations during the Middle and Late Devonian. Our simulations for the Early Devonian with identical boundary conditions as in our Devonian sensitivity study (Brugger et al., 2019), but with a low atmospheric CO2 concentration of 500 ppm, show no direct conflict with available proxy and paleobotanical data and confirm that under the simulated climatic conditions carbon isotope fractionation represents a robust proxy for atmospheric CO2. To explain the earlier CO2 drop we suggest that early forms of vascular land plants have already strongly influenced weathering. This new perspective on the Devonian questions previous ideas about the climatic conditions and earlier explanations for the Devonian mass extinctions.
The second mass extinction investigated in this thesis is the end-Cretaceous mass extinction (66 million years ago) which differs from the Devonian mass extinctions in terms of the processes involved and the timescale on which the extinctions occurred. In the two studies presented here (Brugger et al., 2017, 2021), we model the climatic effects of the Chicxulub impact, one of the proposed causes of the end-Cretaceous extinction, for the first millennium after the impact. The light-dimming effect of stratospheric sulfate aerosols causes severe cooling, with a decrease of global annual mean surface air temperature of at least 26◦C and a recovery to pre-impact temperatures after more than 30 years. The sudden surface cooling of the ocean induces deep convection which brings nutrients from the deep ocean via upwelling to the surface ocean. Using an ocean biogeochemistry model we explore the combined effect of ocean mixing and iron-rich dust originating from the impactor on the marine biosphere. As soon as light levels have recovered, we find a short, but prominent peak in marine net primary productivity. This newly discovered mechanism could result in toxic effects for marine near-surface ecosystems. Comparison of our model results to proxy data (Vellekoop et al., 2014, 2016, Hull et al., 2020) suggests that carbon release from the terrestrial biosphere is required in addition to the carbon dioxide which can be attributed to the target material. Surface ocean acidification caused by the addition of carbon dioxide and sulfur is only moderate. Taken together, the results indicate a significant contribution of the Chicxulub impact to the end-Cretaceous mass extinction by triggering multiple stressors for the Earth system.
Although the sixth extinction we face today is characterized by human intervention in nature, this thesis shows that we can gain many insights into future extinctions from studying past mass extinctions, such as the importance of the rate of change (Rothman, 2017), the interplay of multiple stressors (Gunderson et al., 2016), and changes in the carbon cycle (Rothman, 2017, Tierney et al., 2020).
Enacted in 2009, the National Policy on Climate Change (PNMC) is a milestone in the institutionalisation of climate action in Brazil. It sets greenhouse gas (GHG) emission reduction targets and a set of principles and directives that are intended to lay the foundations for a cross-sectoral and multilevel climate policy in the country. However, after more than a decade since its establishment, the PNMC has experienced several obstacles related to its governance, such as coordination, planning and implementation issues. All of these issues pose threats to the effectiveness of GHG mitigation actions in the country.
By looking at the intragovernmental and intergovernmental relationships that have taken place during the lifetime of the PNMC and its sectoral plans on agriculture (the Sectoral Plan for Mitigation and Adaptation to Climate Change for the Consolidation of a Low-Carbon Economy in Agriculture [ABC Plan]), transport and urban mobility (the Sectoral Plan for Transportation and Urban Mobility for Mitigation and Adaption of Climate Change [PSTM]), this exploratory qualitative research investigates the Brazilian climate change governance guided by the following relevant questions: how are climate policy arrangements organised and coordinated among governmental actors to mitigate GHG emissions in Brazil? What might be the reasons behind how such arrangements are established? What are the predominant governance gaps of the different GHG mitigation actions examined? Why do these governance gaps occur?
Theoretically grounded in the literature on multilevel governance and coordination of public policies, this study employs a novel analytical framework that aims to identify and discuss the occurrence of four types of governance gaps (i.e. politics, institutions and processes, resources and information) in the three GHG mitigation actions (cases) examined (i.e. the PNMC, ABC Plan and PSTM). The research results are twofold. First, they reveal that Brazil has struggled to organise and coordinate governmental actors from different policy constituencies and different levels of government in the implementation of the GHG mitigation actions examined. Moreover, climate policymaking has mostly been influenced by the Ministry of Environment (MMA) overlooking the multilevel and cross-sectoral approaches required for a country’s climate policy to mitigate and adapt to climate change, especially if it is considered an economy-wide Nationally Determined Contribution (NDC), as the Brazilian one is.
Second, the study identifies a greater manifestation of gaps in politics (e.g. lack of political will in supporting climate action), institutions and processes (e.g. failures in the design of institutions and policy instruments, coordination and monitoring flaws, and difficulties in building climate federalism) in all cases studied. It also identifies that there have been important advances in the production of data and information for decision-making and, to a lesser extent, in the allocation of technical and financial resources in the cases studied; however, it is necessary to highlight the limitation of these improvements due to turf wars, a low willingness to share information among federal government players, a reduced volume of financial resources and an unequal distribution of capacities among the federal ministries and among the three levels of government.
A relevant finding is that these gaps tend to be explained by a combination of general and sectoral set aspects. Regarding the general aspects, which are common to all cases examined, the following can be mentioned: i) unbalanced policy capabilities existing among the different levels of government, ii) a limited (bureaucratic) practice to produce a positive coordination mode within cross-sectoral policies, iii) the socioeconomic inequalities that affect the way different governments and economic sectors perceive the climate issue (selective perception) and iv) the reduced dialogue between national and subnational governments on the climate agenda (poor climate federalism). The following sectoral aspects can be mentioned: i) the presence of path dependencies that make the adoption of transformative actions harder and ii) the absence of perceived co-benefits that the climate agenda can bring to each economic sector (e.g. reputational gains, climate protection and access to climate financial markets).
By addressing the theoretical and practical implications of the results, this research provides key insights to tackle the governance gaps identified and to help Brazil pave the way to achieving its NDCs and net-zero targets. At the theoretical level, this research and the current country’s GHG emissions profile suggest that the Brazilian climate policy is embedded in a cross-sectoral and multilevel arena, which requires the effective involvement of different levels of political and bureaucratic powers and the consideration of the country’s socioeconomic differences. Thus, the research argues that future improvements of the Brazilian climate policy and its governance setting must frame climate policy as an economic development agenda, the ramifications of which go beyond the environmental sector. An initial consequence of this new perspective may be a shift in the political and technical leadership from the MMA to the institutions of the centre of government (Executive Office of the President of Brazil) and those in charge of the country’s economic policy (Ministry of Economy). This change could provide greater capacity for coordination, integration and enforcement as well as for addressing certain expected gaps (e.g. financial and technical resources). It could also lead to greater political prioritisation of the agenda at the highest levels of government. Moreover, this shift of the institutional locus could contribute to greater harmonisation between domestic development priorities and international climate politics. Finally, the research also suggests that this approach would reduce bureaucratic elitism currently in place due to climate policy being managed by Brazilian governmental institutions, which is still a theme of a few ministries and a reason for the occurrence of turf wars.
Climate change of anthropogenic origin is affecting Earth’s biodiversity and therefore ecosystems and their services. High latitude ecosystems are even more impacted than the rest of Northern Hemisphere because of the amplified polar warming. Still, it is challenging to predict the dynamics of high latitude ecosystems because of complex interaction between abiotic and biotic components. As the past is the key to the future, the interpretation of past ecological changes to better understand ongoing processes is possible. In the Quaternary, the Pleistocene experienced several glacial and interglacial stages that affected past ecosystems. During the last Glacial, the Pleistocene steppe-tundra was covering most of unglaciated northern hemisphere and disappeared in parallel to the megafauna’s extinction at the transition to the Holocene (~11,700 years ago). The origin of the steppe-tundra decline is not well understood and knowledge on the mechanisms, which caused shifts in past communities and ecosystems, is of high priority as they are likely comparable to those affecting modern ecosystems. Lake or permafrost core sediments can be retrieved to investigate past biodiversity at transitions between glacial and interglacial stages. Siberia and Beringia were the origin of dispersal of the steppe-tundra, which make investigation this area of high priority. Until recently, macrofossils and pollen were the most common approaches. They are designed to reconstruct past composition changes but have limit and biases. Since the end of the 20th century, sedimentary ancient DNA (sedaDNA) can also be investigated. My main objectives were, by using sedaDNA approaches to provide scientific evidence of compositional and diversity changes in the Northern Hemisphere ecosystems at the transition between Quaternary glacial and interglacial stages.
In this thesis, I provide snapshots of entire ancient ecosystems and describe compositional changes between Quaternary glacial and interglacial stages, and confirm the vegetation composition and the spatial and temporal boundaries of the Pleistocene steppe-tundra. I identify a general loss of plant diversity with extinction events happening in parallel of megafauna’ extinction. I demonstrate how loss of biotic resilience led to the collapse of a previously well-established system and discuss my results in regards to the ongoing climate change. With further work to constrain biases and limits, sedaDNA can be used in parallel or even replace the more established macrofossils and pollen approaches as my results support the robustness and potential of sedaDNA to answer new palaeoecological questions such as plant diversity changes, loss and provide snapshots of entire ancient biota.
Changes in species' distributions are classically projected based on their climate envelopes. For Siberian forests, which have a tremendous significance for vegetation-climate feedbacks, this implies future shifts of each of the forest-forming larch (Larix) species to the north-east. However, in addition to abiotic factors, reliable projections must assess the role of historical biogeography and biotic interactions. Here, we use sedimentary ancient DNA and individual-based modelling to investigate the distribution of larch species and mitochondrial haplotypes through space and time across the treeline ecotone on the southern Taymyr peninsula, which at the same time presents a boundary area of two larch species. We find spatial and temporal patterns, which suggest that forest density is the most influential driver determining the precise distribution of species and mitochondrial haplotypes. This suggests a strong influence of competition on the species' range shifts. These findings imply possible climate change outcomes that are directly opposed to projections based purely on climate envelopes. Investigations of such fine-scale processes of biodiversity change through time are possible using paleoenvironmental DNA, which is available much more readily than visible fossils and can provide information at a level of resolution that is not reached in classical palaeoecology.
Forests are a key resource serving a multitude of functions such as providing income to forest owners, supplying industries with timber, protecting water resources, and maintaining biodiversity. Recently much attention has been given to the role of forests in the global carbon cycle and their management for increased carbon sequestration as a possible mitigation option against climate change. Furthermore, the use of harvested wood can contribute to the reduction of atmospheric carbon through (i) carbon sequestration in wood products, (ii) the substitution of non-wood products with wood products, and (iii) through the use of wood as a biofuel to replace fossil fuels. Forest resource managers are challenged by the task to balance these multiple while simultaneously meeting economic requirements and taking into consideration the demands of stakeholder groups. Additionally, risks and uncertainties with regard to uncontrollable external variables such as climate have to be considered in the decision making process. In this study a scientific stakeholder dialogue with forest-related stakeholder groups in the Federal State of Brandenburg was accomplished. The main results of this dialogue were the definition of major forest functions (carbon sequestration, groundwater recharge, biodiversity, and timber production) and priority setting among them by the stakeholders using the pair-wise comparison technique. The impact of different forest management strategies and climate change scenarios on the main functions of forest ecosystems were evaluated at the Kleinsee management unit in south-east Brandenburg. Forest management strategies were simulated over 100 years using the forest growth model 4C and a wood product model (WPM). A current climate scenario and two climate change scenarios based on global circulation models (GCMs) HadCM2 and ECHAM4 were applied. The climate change scenario positively influenced stand productivity, carbon sequestration, and income. The impact on the other forest functions was small. Furthermore, the overall utility of forest management strategies were compared under the priority settings of stakeholders by a multi-criteria analysis (MCA) method. Significant differences in priority setting and the choice of an adequate management strategy were found for the environmentalists on one side and the more economy-oriented forest managers of public and private owned forests on the other side. From an ecological perspective, a conservation strategy would be preferable under all climate scenarios, but the business as usual management would also fit the expectations under the current climate. In contrast, a forest manager in public-owned forests or a private forest owner would prefer a management strategy with an intermediate thinning intensity and a high share of pine stands to enhance income from timber production while maintaining the other forest functions. The analysis served as an example for the combined application of simulation tools and a MCA method for the evaluation of management strategies under multi-purpose and multi-user settings with changing climatic conditions. Another focus was set on quantifying the overall effect of forest management on carbon sequestration in the forest sector and the wood industry sector plus substitution effects. To achieve this objective, the carbon emission reduction potential of material and energy substitution (Smat and Sen) was estimated based on a literature review. On average, for each tonne of dry wood used in a wood product substituting a non-wood product, 0.71 fewer tonnes of fossil carbon are emitted into to the atmosphere. Based on Smat and Sen, the calculation of the carbon emission reduction through substitution was implemented in the WPM. Carbon sequestration and substitution effects of management strategies were simulated at three local scales using the WPM and the forest growth models 4C (management unit level) or EFISCEN (federal state of Brandenburg and Germany). An investigation was conducted on the influence of uncertainties in the initialisation of the WPM, Smat, and basic conditions of the wood product sector on carbon sequestration. Results showed that carbon sequestration in the wood industry sector plus substitution effects exceeded sequestration in the forest sector. In contrast to the carbon pools in the forest sector, which acted as sink or source, the substitution effects continually reduced carbon emission as long as forests are managed and timber is harvested. The main climate protection function was investigated for energy substitution which accounted for about half of the total carbon sequestration, followed by carbon storage in landfills. In Germany, the absolute annual carbon sequestration in the forest and wood industry sector plus substitution effects was 19.9 Mt C. Over 50 years the wood industry sector contributed 70% of the total carbon sequestration plus substitution effects.
This is a cumulative dissertation comprising three original studies (one published, one in revision, one submitted; Effective December 2017) investigating how reptile species in arid Australia respond to various climatic parameters at different spatial scales and analysing the two potential main underlying mechanisms: thermoregulatory behaviour and species interactions. This dissertation combines extensive individual-based field data across trophic levels, selected field experiments, statistical analyses, and predictive modelling techniques. Mechanisms and processes detected in this dissertation can now be used to predict potential future changes in the community of arid-zone lizards. This knowledge will help improving our fundamental understanding of the consequences of global change and thereby prevent biodiversity loss in a vulnerable ecosystem.
In the wake of 21st century, humanity witnessed a phenomenal raise of urban agglomerations as powerhouses for innovation and socioeconomic growth. Driving much of national (and in few instances even global) economy, such a gargantuan raise of cities is also accompanied by subsequent increase in energy, resource consumption and waste generation. Much of anthropogenic transformation of Earth's environment in terms of environmental pollution at local level to planetary scale in the form of climate change is currently taking place in cities. Projected to be crucibles for entire humanity by the end of this century, the ultimate fate of humanity predominantly lies in the hands of technological innovation, urbanites' attitudes towards energy/resource consumption and development pathways undertaken by current and future cities. Considering the unparalleled energy, resource consumption and emissions currently attributed to global cities, this thesis addresses these issues from an efficiency point of view. More specifically, this thesis addresses the influence of population size, density, economic geography and technology in improving urban greenhouse gas (GHG) emission efficiency and identifies the factors leading to improved eco-efficiency in cities. In order to investigate the in uence of these factors in improving emission and resource efficiency in cities, a multitude of freely available datasets were coupled with some novel methodologies and analytical approaches in this thesis.
Merging the well-established Kaya Identity to the recently developed urban scaling laws, an Urban Kaya Relation is developed to identify whether large cities are more emission efficient and the intrinsic factors leading to such (in)efficiency. Applying Urban Kaya Relation to a global dataset of 61 cities in 12 countries, this thesis identifed that large cities in developed regions of the world will bring emission efficiency gains because of the better technologies implemented in these cities to produce and utilize energy consumption while the opposite is the case for cities in developing regions. Large cities in developing countries are less efficient mainly because of their affluence and lack of efficient technologies. Apart from the in uence of population size on emission efficiency, this thesis identified the crucial role played by population density in improving building and on-road transport sector related emission efficiency in cities. This is achieved by applying the City Clustering Algorithm (CCA) on two different gridded land use datasets and a standard emission inventory to attribute these sectoral emissions to all inhabited settlements in the USA. Results show that doubling the population density would entail a reduction in the total CO2 emissions in buildings and on-road sectors typically by at least 42 %. Irrespective of their population size and density, cities are often blamed for their intensive resource consumption that threatens not only local but also global sustainability. This thesis merged the concept of urban metabolism with benchmarking and identified cities which are eco-efficient. These cities enable better socioeconomic conditions while being less burden to the environment. Three environmental burden indicators (annual average NO2 concentration, per capita waste generation and water consumption) and two socioeconomic indicators (GDP per capita and employment ratio) for 88 most populous European cities are considered in this study. Using two different non-parametric ranking methods namely regression residual ranking and Data Envelopment Analysis (DEA), eco-efficient cities and their determining factors are identified. This in-depth analysis revealed that mature cities with well-established economic structures such as Munich, Stockholm and Oslo are eco-efficient. Further, correlations between objective eco-efficiency ranking with each of the indicator rankings and the ranking of urbanites' subjective perception about quality of life are analyzed. This analysis revealed that urbanites' perception about quality of life is not merely confined to the socioeconomic well-being but rather to their combination with lower environmental burden.
In summary, the findings of this dissertation has three general conclusions for improving emission and ecological efficiency in cities. Firstly, large cities in emerging nations face a huge challenge with respect to improving their emission efficiency. The task in front of these cities is threefold: (1) deploying efficient technologies for the generation of electricity and improvement of public transportation to unlock their leap frogging potential, (2) addressing the issue of energy poverty and (3) ensuring that these cities do not develop similar energy consumption patterns with infrastructure lock-in behavior similar to those of cities in developed regions. Secondly, the on-going urban sprawl as a global phenomenon will decrease the emission efficiency within the building and transportation sector. Therefore, local policy makers should identify adequate fiscal and land use policies to curb urban sprawl. Lastly, since mature cities with well-established economic structures are more eco-efficient and urbanites' perception re ects its combination with decreasing environmental burden; there is a need to adopt and implement strategies which enable socioeconomic growth in cities whilst decreasing their environment burden.
The relationship between climate and forest productivity is an intensively studied subject in forest science. This Thesis is embedded within the general framework of future forest growth under climate change and its implications for the ongoing forest conversion. My objective is to investigate the future forest productivity at different spatial scales (from a single specific forest stand to aggregated information across Germany) with focus on oak-pine forests in the federal state of Brandenburg. The overarching question is: how are the oak-pine forests affected by climate change described by a variety of climate scenarios. I answer this question by using a model based analysis of tree growth processes and responses to different climate scenarios with emphasis on drought events. In addition, a method is developed which considers climate change uncertainty of forest management planning.
As a first 'screening' of climate change impacts on forest productivity, I calculated the change in net primary production on the base of a large set of climate scenarios for different tree species and the total area of Germany. Temperature increases up to 3 K lead to positive effects on the net primary production of all selected tree species. But, in water-limited regions this positive net primary production trend is dependent on the length of drought periods which results in a larger uncertainty regarding future forest productivity. One of the regions with the highest uncertainty of net primary production development is the federal state of Brandenburg.
To enhance the understanding and ability of model based analysis of tree growth sensitivity to drought stress two water uptake approaches in pure pine and mixed oak-pine stands are contrasted. The first water uptake approach consists of an empirical function for root water uptake. The second approach is more mechanistic and calculates the differences of soil water potential along a soil-plant-atmosphere continuum. I assumed the total root resistance to vary at low, medium and high total root resistance levels. For validation purposes three data sets on different tree growth relevant time scales are used. Results show that, except the mechanistic water uptake approach with high total root resistance, all transpiration outputs exceeded observed values. On the other hand high transpiration led to a better match of observed soil water content. The strongest correlation between simulated and observed annual tree ring width occurred with the mechanistic water uptake approach and high total root resistance. The findings highlight the importance of severe drought as a main reason for small diameter increment, best supported by the mechanistic water uptake approach with high root resistance. However, if all aspects of the data sets are considered no approach can be judged superior to the other. I conclude that the uncertainty of future productivity of water-limited forest ecosystems under changing environmental conditions is linked to simulated root water uptake.
Finally my study aimed at the impacts of climate change combined with management scenarios on an oak-pine forest to evaluate growth, biomass and the amount of harvested timber. The pine and the oak trees are 104 and 9 years old respectively. Three different management scenarios with different thinning intensities and different climate scenarios are used to simulate the performance of management strategies which explicitly account for the risks associated with achieving three predefined objectives (maximum carbon storage, maximum harvested timber, intermediate). I found out that in most cases there is no general management strategy which fits best to different objectives. The analysis of variance in the growth related model outputs showed an increase of climate uncertainty with increasing climate warming. Interestingly, the increase of climate-induced uncertainty is much higher from 2 to 3 K than from 0 to 2 K.
Semi-arid areas are, due to their climatic setting, characterized by small water resources. An increasing water demand as a consequence of population growth and economic development as well as a decreasing water availability in the course of possible climate change may aggravate water scarcity in future, which often exists already for present-day conditions in these areas. Understanding the mechanisms and feedbacks of complex natural and human systems, together with the quantitative assessment of future changes in volume, timing and quality of water resources are a prerequisite for the development of sustainable measures of water management to enhance the adaptive capacity of these regions. For this task, dynamic integrated models, containing a hydrological model as one component, are indispensable tools. The main objective of this study is to develop a hydrological model for the quantification of water availability in view of environmental change over a large geographic domain of semi-arid environments. The study area is the Federal State of Ceará (150 000 km2) in the semi-arid north-east of Brazil. Mean annual precipitation in this area is 850 mm, falling in a rainy season with duration of about five months. Being mainly characterized by crystalline bedrock and shallow soils, surface water provides the largest part of the water supply. The area has recurrently been affected by droughts which caused serious economic losses and social impacts like migration from the rural regions. The hydrological model Wasa (Model of Water Availability in Semi-Arid Environments) developed in this study is a deterministic, spatially distributed model being composed of conceptual, process-based approaches. Water availability (river discharge, storage volumes in reservoirs, soil moisture) is determined with daily resolution. Sub-basins, grid cells or administrative units (municipalities) can be chosen as spatial target units. The administrative units enable the coupling of Wasa in the framework of an integrated model which contains modules that do not work on the basis of natural spatial units. The target units mentioned above are disaggregated in Wasa into smaller modelling units within a new multi-scale, hierarchical approach. The landscape units defined in this scheme capture in particular the effect of structured variability of terrain, soil and vegetation characteristics along toposequences on soil moisture and runoff generation. Lateral hydrological processes at the hillslope scale, as reinfiltration of surface runoff, being of particular importance in semi-arid environments, can thus be represented also within the large-scale model in a simplified form. Depending on the resolution of available data, small-scale variability is not represented explicitly with geographic reference in Wasa, but by the distribution of sub-scale units and by statistical transition frequencies for lateral fluxes between these units. Further model components of Wasa which respect specific features of semi-arid hydrology are: (1) A two-layer model for evapotranspiration comprises energy transfer at the soil surface (including soil evaporation), which is of importance in view of the mainly sparse vegetation cover. Additionally, vegetation parameters are differentiated in space and time in dependence on the occurrence of the rainy season. (2) The infiltration module represents in particular infiltration-excess surface runoff as the dominant runoff component. (3) For the aggregate description of the water balance of reservoirs that cannot be represented explicitly in the model, a storage approach respecting different reservoirs size classes and their interaction via the river network is applied. (4) A model for the quantification of water withdrawal by water use in different sectors is coupled to Wasa. (5) A cascade model for the temporal disaggregation of precipitation time series, adapted to the specific characteristics of tropical convective rainfall, is applied for the generating rainfall time series of higher temporal resolution. All model parameters of Wasa can be derived from physiographic information of the study area. Thus, model calibration is primarily not required. Model applications of Wasa for historical time series generally results in a good model performance when comparing the simulation results of river discharge and reservoir storage volumes with observed data for river basins of various sizes. The mean water balance as well as the high interannual and intra-annual variability is reasonably represented by the model. Limitations of the modelling concept are most markedly seen for sub-basins with a runoff component from deep groundwater bodies of which the dynamics cannot be satisfactorily represented without calibration. Further results of model applications are: (1) Lateral processes of redistribution of runoff and soil moisture at the hillslope scale, in particular reinfiltration of surface runoff, lead to markedly smaller discharge volumes at the basin scale than the simple sum of runoff of the individual sub-areas. Thus, these processes are to be captured also in large-scale models. The different relevance of these processes for different conditions is demonstrated by a larger percentage decrease of discharge volumes in dry as compared to wet years. (2) Precipitation characteristics have a major impact on the hydrological response of semi-arid environments. In particular, underestimated rainfall intensities in the rainfall input due to the rough temporal resolution of the model and due to interpolation effects and, consequently, underestimated runoff volumes have to be compensated in the model. A scaling factor in the infiltration module or the use of disaggregated hourly rainfall data show good results in this respect. The simulation results of Wasa are characterized by large uncertainties. These are, on the one hand, due to uncertainties of the model structure to adequately represent the relevant hydrological processes. On the other hand, they are due to uncertainties of input data and parameters particularly in view of the low data availability. Of major importance is: (1) The uncertainty of rainfall data with regard to their spatial and temporal pattern has, due to the strong non-linear hydrological response, a large impact on the simulation results. (2) The uncertainty of soil parameters is in general of larger importance on model uncertainty than uncertainty of vegetation or topographic parameters. (3) The effect of uncertainty of individual model components or parameters is usually different for years with rainfall volumes being above or below the average, because individual hydrological processes are of different relevance in both cases. Thus, the uncertainty of individual model components or parameters is of different importance for the uncertainty of scenario simulations with increasing or decreasing precipitation trends. (4) The most important factor of uncertainty for scenarios of water availability in the study area is the uncertainty in the results of global climate models on which the regional climate scenarios are based. Both a marked increase or a decrease in precipitation can be assumed for the given data. Results of model simulations for climate scenarios until the year 2050 show that a possible future change in precipitation volumes causes a larger percentage change in runoff volumes by a factor of two to three. In the case of a decreasing precipitation trend, the efficiency of new reservoirs for securing water availability tends to decrease in the study area because of the interaction of the large number of reservoirs in retaining the overall decreasing runoff volumes.
This dissertation investigates the impact of the economic and fiscal crisis starting in 2008 on EU climate policy-making. While the overall number of adopted greenhouse gas emission reduction policies declined in the crisis aftermath, EU lawmakers decided to introduce new or tighten existing regulations in some important policy domains. Existing knowledge about the crisis impact on EU legislative decision-making cannot explain these inconsistencies. In response, this study develops an actor-centred conceptual framework based on rational choice institutionalism that provides a micro-level link to explain how economic crises translate into altered policy-making patterns. The core theoretical argument draws on redistributive conflicts, arguing that tensions between ‘beneficiaries’ and ‘losers’ of a regulatory initiative intensify during economic crises and spill over to the policy domain. To test this hypothesis and using social network analysis, this study analyses policy processes in three case studies: The introduction of carbon dioxide emission limits for passenger cars, the expansion of the EU Emissions Trading System to aviation, and the introduction of a regulatory framework for biofuels. The key finding is that an economic shock causes EU policy domains to polarise politically, resulting in intensified conflict and more difficult decision-making. The results also show that this process of political polarisation roots in the industry that is the subject of the regulation, and that intergovernmental bargaining among member states becomes more important, but also more difficult in times of crisis.
In a changing world facing several direct or indirect anthropogenic challenges the freshwater resources are endangered in quantity and quality. An excessive supply of nutrients, for example, can cause disproportional phytoplankton development and oxygen deficits in large rivers, leading to failure of the aims requested by the Water Framework Directive (WFD). Such problems can be observed in many European river catchments including the Elbe basin, and effective measures for improving water quality status are highly appreciated.
In water resources management and protection, modelling tools can help to understand the dominant nutrient processes and to identify the main sources of nutrient pollution in a watershed. They can be effective instruments for impact assessments investigating the effects of changing climate or socio-economic conditions on the status of surface water bodies, and for testing the usefulness of possible protection measures. Due to the high number of interrelated processes, ecohydrological model approaches containing water quality components are more complex than the pure hydrological ones, and their setup and calibration require more efforts. Such models, including the Soil and Water Integrated Model (SWIM), still need some further development and improvement.
Therefore, this cumulative dissertation focuses on two main objectives: 1) the approach-related objectives aiming in the SWIM model improvement and further development regarding nutrient (nitrogen and phosphorus) process description, and 2) the application-related objectives in meso- to large-scale Elbe river basins to support adaptive river basin management in view of possible future changes. The dissertation is based on five scientific papers published in international journals and dealing with these research questions.
Several adaptations were implemented in the model code to improve the representation of nutrient processes including a simple wetland approach, an extended by ammonium nitrogen cycle in the soils, as well as a detailed in-stream module, simulating algal growth, nutrient transformation processes and oxygen conditions in the river reaches, mainly driven by water temperature and light. Although this new approaches created a highly complex ecohydrological model with a large number of additional calibration parameters and rising uncertainty, the calibration and validation of the SWIM model enhanced by the new approaches in selected subcatchment and the entire Elbe river basin delivered satisfactory to good model results in terms of criteria of fit. Thus, the calibrated and validated model provided a sound base for the assessment of possible future changes and impacts in climate, land use and management in the Elbe river (sub)basin(s).
The new enhanced modelling approach improved the applicability of the SWIM model for the WFD related research questions, where the ability to consider biological water quality components (such as phytoplankton) is important. It additionally enhanced its ability to simulate the behaviour of nutrients coming mainly from point sources (e.g. phosphate phosphorus). Scenario results can be used by decision makers and stakeholders to find and understand future challenges and possible adaptation measures in the Elbe river basin.
Long-term bacteria-fungi-plant associations in permafrost soils inferred from palaeometagenomics
(2024)
The arctic is warming 2 – 4 times faster than the global average, resulting in a strong feedback on northern ecosystems such as boreal forests, which cover a vast area of the high northern latitudes. With ongoing global warming, the treeline subsequently migrates northwards into tundra areas. The consequences of turning ecosystems are complex: on the one hand, boreal forests are storing large amounts of global terrestrial carbon and act as a carbon sink, dragging carbon dioxide out of the global carbon cycle, suggesting an enhanced carbon uptake with increased tree cover. On the other hand, with the establishment of trees, the albedo effect of tundra decreases, leading to enhanced soil warming. Meanwhile, permafrost thaws, releasing large amounts of previously stored carbon into the atmosphere. So far, mainly vegetation dynamics have been assessed when studying the impact of warming onto ecosystems. Most land plants are living in close symbiosis with bacterial and fungal communities, sustaining their growth in nutrient poor habitats. However, the impact of climate change on these subsoil communities alongside changing vegetation cover remains poorly understood. Therefore, a better understanding of soil community dynamics on multi millennial timescales is inevitable when addressing the development of entire ecosystems. Unravelling long-term cross-kingdom dependencies between plant, fungi, and bacteria is not only a milestone for the assessment of warming on boreal ecosystems. On top, it also is the basis for agriculture strategies to sustain society with sufficient food in a future warming world.
The first objective of this thesis was to assess ancient DNA as a proxy for reconstructing the soil microbiome (Manuscripts I, II, III, IV). Research findings across these projects enable a comprehensive new insight into the relationships of soil microorganisms to the surrounding vegetation. First, this was achieved by establishing (Manuscript I) and applying (Manuscript II) a primer pair for the selective amplification of ancient fungal DNA from lake sediment samples with the metabarcoding approach. To assess fungal and plant co-variation, the selected primer combination (ITS67, 5.8S) amplifying the ITS1 region was applied on samples from five boreal and arctic lakes. The obtained data showed that the establishment of fungal communities is impacted by warming as the functional ecological groups are shifting. Yeast and saprotroph dominance during the Late Glacial declined with warming, while the abundance of mycorrhizae and parasites increased with warming. The overall species richness was also alternating. The results were compared to shotgun sequencing data reconstructing fungi and bacteria (Manuscripts III, IV), yielding overall comparable results to the metabarcoding approach. Nonetheless, the comparison also pointed out a bias in the metabarcoding, potentially due to varying ITS lengths or copy numbers per genome.
The second objective was to trace fungus-plant interaction changes over time (Manuscripts II, III). To address this, metabarcoding targeting the ITS1 region for fungi and the chloroplast P6 loop for plants for the selective DNA amplification was applied (Manuscript II). Further, shotgun sequencing data was compared to the metabarcoding results (Manuscript III). Overall, the results between the metabarcoding and the shotgun approaches were comparable, though a bias in the metabarcoding was assumed. We demonstrated that fungal shifts were coinciding with changes in the vegetation. Yeast and lichen were mainly dominant during the Late Glacial with tundra vegetation, while warming in the Holocene lead to the expansion of boreal forests with increasing mycorrhizae and parasite abundance. Aside, we highlighted that Pinaceae establishment is dependent on mycorrhizal fungi such as Suillineae, Inocybaceae, or Hyaloscypha species also on long-term scales.
The third objective of the thesis was to assess soil community development on a temporal gradient (Manuscripts III, IV). Shotgun sequencing was applied on sediment samples from the northern Siberian lake Lama and the soil microbial community dynamics compared to ecosystem turnover. Alongside, podzolization processes from basaltic bedrock were recovered (Manuscript III). Additionally, the recovered soil microbiome was compared to shotgun data from granite and sandstone catchments (Manuscript IV, Appendix). We assessed if the establishment of the soil microbiome is dependent on the plant taxon and as such comparable between multiple geographic locations or if the community establishment is driven by abiotic soil properties and as such the bedrock area. We showed that the development of soil communities is to a great extent driven by the vegetation changes and temperature variation, while time only plays a minor role. The analyses showed general ecological similarities especially between the granite and basalt locations, while the microbiome on species-level was rather site-specific. A greater number of correlated soil taxa was detected for deep-rooting boreal taxa in comparison to grasses with shallower roots. Additionally, differences between herbaceous taxa of the late Glacial compared to taxa of the Holocene were revealed.
With this thesis, I demonstrate the necessity to investigate subsoil community dynamics on millennial time scales as it enables further understanding of long-term ecosystem as well as soil development processes and such plant establishment. Further, I trace long-term processes leading to podzolization which supports the development of applied carbon capture strategies under future global warming.
Die Anpassung von Sektoren an veränderte klimatische Bedingungen erfordert ein Verständnis von regionalen Vulnerabilitäten. Vulnerabilität ist als Funktion von Sensitivität und Exposition, welche potentielle Auswirkungen des Klimawandels darstellen, und der Anpassungsfähigkeit von Systemen definiert. Vulnerabilitätsstudien, die diese Komponenten quantifizieren, sind zu einem wichtigen Werkzeug in der Klimawissenschaft geworden. Allerdings besteht von der wissenschaftlichen Perspektive aus gesehen Uneinigkeit darüber, wie diese Definition in Studien umgesetzt werden soll. Ausdiesem Konflikt ergeben sich viele Herausforderungen, vor allem bezüglich der Quantifizierung und Aggregierung der einzelnen Komponenten und deren angemessenen Komplexitätsniveaus. Die vorliegende Dissertation hat daher zum Ziel die Anwendbarkeit des Vulnerabilitätskonzepts voranzubringen, indem es in eine systematische Struktur übersetzt wird. Dies beinhaltet alle Komponenten und schlägt für jede Klimaauswirkung (z.B. Sturzfluten) eine Beschreibung des vulnerablen Systems vor (z.B. Siedlungen), welches direkt mit einer bestimmten Richtung eines relevanten klimatischen Stimulus in Verbindung gebracht wird (z.B. stärkere Auswirkungen bei Zunahme der Starkregentage). Bezüglich der herausfordernden Prozedur der Aggregierung werden zwei alternative Methoden, die einen sektorübergreifenden Überblick ermöglichen, vorgestellt und deren Vor- und Nachteile diskutiert. Anschließend wird die entwickelte Struktur einer Vulnerabilitätsstudie mittels eines indikatorbasierten und deduktiven Ansatzes beispielhaft für Gemeinden in Nordrhein-Westfalen in Deutschland angewandt. Eine Übertragbarkeit auf andere Regionen ist dennoch möglich. Die Quantifizierung für die Gemeinden stützt sich dabei auf Informationen aus der Literatur. Da für viele Sektoren keine geeigneten Indikatoren vorhanden waren, werden in dieser Arbeit neue Indikatoren entwickelt und angewandt, beispielsweise für den Forst- oder Gesundheitssektor. Allerdings stellen fehlende empirische Daten bezüglich relevanter Schwellenwerte eine Lücke dar, beispielsweise welche Stärke von Klimaänderungen eine signifikante Auswirkung hervorruft. Dies führt dazu, dass die Studie nur relative Aussagen zum Grad der Vulnerabilität jeder Gemeinde im Vergleich zum Rest des Bundeslandes machen kann. Um diese Lücke zu füllen, wird für den Forstsektor beispielhaft die heutige und zukünftige Sturmwurfgefahr von Wäldern berechnet. Zu diesem Zweck werden die Eigenschaften der Wälder mit empirischen Schadensdaten eines vergangenen Sturmereignisses in Verbindung gebracht. Der sich daraus ergebende Sensitivitätswert wird anschließend mit den Windverhältnissen verknüpft. Sektorübergreifende Vulnerabilitätsstudien erfordern beträchtliche Ressourcen, was oft deren Anwendbarkeit erschwert. In einem nächsten Schritt wird daher das Potential einer Vereinfachung der Komplexität anhand zweier sektoraler Beispiele untersucht. Um das Auftreten von Waldbränden vorherzusagen, stehen zahlreiche meteorologische Indices zur Verfügung, welche eine Spannbreite unterschiedlicher Komplexitäten aufweisen. Bezüglich der Anzahl monatlicher Waldbrände weist die relative Luftfeuchtigkeit für die meisten deutschen Bundesländer eine bessere Vorhersagekraft als komplexere Indices auf. Dies ist er Fall, obgleich sie selbst als Eingangsvariable für die komplexeren Indices verwendet wird. Mit Hilfe dieses einzelnen meteorologischen Faktors kann also die Waldbrandgefahr in deutschen Region ausreichend genau ausgedrückt werden, was die Ressourceneffizienz von Studien erhöht. Die Methodenkomplexität wird auf ähnliche Weise hinsichtlich der Anwendung des ökohydrologischen Modells SWIM für die Region Brandenburg untersucht. Die interannuellen Bodenwasserwerte, welche durch dieses Modell simuliert werden, können nur unzureichend durch ein einfacheres statistisches Modell, welches auf denselben Eingangsdaten aufbaut, abgebildet werden. Innerhalb eines Zeithorizonts von Jahrzehnten, kann der statistische Ansatz jedoch das Bodenwasser zufriedenstellend abbilden und zeigt eine Dominanz der Bodeneigenschaft Feldkapazität. Dies deutet darauf hin, dass die Komplexität im Hinblick auf die Anzahl der Eingangsvariablen für langfristige Berechnungen reduziert werden kann. Allerdings sind die Aussagen durch fehlende beobachtete Bodenwasserwerte zur Validierung beschränkt. Die vorliegenden Studien zur Vulnerabilität und ihren Komponenten haben gezeigt, dass eine Anwendung noch immer wissenschaftlich herausfordernd ist. Folgt man der hier verwendeten Vulnerabilitätsdefinition, treten zahlreiche Probleme bei der Implementierung in regionalen Studien auf. Mit dieser Dissertation wurden Fortschritte bezüglich der aufgezeigten Lücken bisheriger Studien erzielt, indem eine systematische Struktur für die Beschreibung und Aggregierung von Vulnerabilitätskomponenten erarbeitet wurde. Hierfür wurden mehrere Ansätze diskutiert, die jedoch Vor- und Nachteile besitzen. Diese sollten vor der Anwendung von zukünftigen Studien daher ebenfalls sorgfältig abgewogen werden. Darüber hinaus hat sich gezeigt, dass ein Potential besteht einige Ansätze zu vereinfachen, jedoch sind hierfür weitere Untersuchungen nötig. Insgesamt konnte die Dissertation die Anwendung von Vulnerabilitätsstudien als Werkzeug zur Unterstützung von Anpassungsmaßnahmen stärken.