@phdthesis{Schmidt2024,
  author    = {Schmidt, Lena Katharina},
  title     = {Altered hydrological and sediment dynamics in high-alpine areas - Exploring the potential of machine-learning for estimating past and future changes},
  doi       = {10.25932/publishup-62330},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-623302},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxi, 129},
  year      = {2024},
  abstract  = {Climate change fundamentally transforms glaciated high-alpine regions, with well-known cryospheric and hydrological implications, such as accelerating glacier retreat, transiently increased runoff, longer snow-free periods and more frequent and intense summer rainstorms. These changes affect the availability and transport of sediments in high alpine areas by altering the interaction and intensity of different erosion processes and catchment properties. Gaining insight into the future alterations in suspended sediment transport by high alpine streams is crucial, given its wide-ranging implications, e.g. for flood damage potential, flood hazard in downstream river reaches, hydropower production, riverine ecology and water quality. However, the current understanding of how climate change will impact suspended sediment dynamics in these high alpine regions is limited. For one, this is due to the scarcity of measurement time series that are long enough to e.g. infer trends. On the other hand, it is difficult - if not impossible - to develop process-based models, due to the complexity and multitude of processes involved in high alpine sediment dynamics. Therefore, knowledge has so far been confined to conceptual models (which do not facilitate deriving concrete timings or magnitudes for individual catchments) or qualitative estimates ('higher export in warmer years') that may not be able to capture decreases in sediment export. Recently, machine-learning approaches have gained in popularity for modeling sediment dynamics, since their black box nature tailors them to the problem at hand, i.e. relatively well-understood input and output data, linked by very complex processes. Therefore, the overarching aim of this thesis is to estimate sediment export from the high alpine {\"O}tztal valley in Tyrol, Austria, over decadal timescales in the past and future - i.e. timescales relevant to anthropogenic climate change. This is achieved by informing, extending, evaluating and applying a quantile regression forest (QRF) approach, i.e. a nonparametric, multivariate machine-learning technique based on random forest. The first study included in this thesis aimed to understand present sediment dynamics, i.e. in the period with available measurements (up to 15 years). To inform the modeling setup for the two subsequent studies, this study identified the most important predictors, areas within the catchments and time periods. To that end, water and sediment yields from three nested gauges in the upper {\"O}tztal, Vent, S{\"o}lden and Tumpen (98 to almost 800 km² catchment area, 930 to 3772 m a.s.l.) were analyzed for their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. The findings suggest that the areas situated above 2500 m a.s.l., containing glacier tongues and recently deglaciated areas, play a pivotal role in sediment generation across all sub-catchments. In contrast, precipitation events were relatively unimportant (on average, 21 \% of annual sediment yield was associated to precipitation events). Thus, the second and third study focused on the Vent catchment and its sub-catchment above gauge Vernagt (11.4 and 98 km², 1891 to 3772 m a.s.l.), due to their higher share of areas above 2500 m. Additionally, they included discharge, precipitation and air temperature (as well as their antecedent conditions) as predictors. The second study aimed to estimate sediment export since the 1960s/70s at gauges Vent and Vernagt. This was facilitated by the availability of long records of the predictors, discharge, precipitation and air temperature, and shorter records (four and 15 years) of turbidity-derived sediment concentrations at the two gauges. The third study aimed to estimate future sediment export until 2100, by applying the QRF models developed in the second study to pre-existing precipitation and temperature projections (EURO-CORDEX) and discharge projections (physically-based hydroclimatological and snow model AMUNDSEN) for the three representative concentration pathways RCP2.6, RCP4.5 and RCP8.5. The combined results of the second and third study show overall increasing sediment export in the past and decreasing export in the future. This suggests that peak sediment is underway or has already passed - unless precipitation changes unfold differently than represented in the projections or changes in the catchment erodibility prevail and override these trends. Despite the overall future decrease, very high sediment export is possible in response to precipitation events. This two-fold development has important implications for managing sediment, flood hazard and riverine ecology. This thesis shows that QRF can be a very useful tool to model sediment export in high-alpine areas. Several validations in the second study showed good performance of QRF and its superiority to traditional sediment rating curves - especially in periods that contained high sediment export events, which points to its ability to deal with threshold effects. A technical limitation of QRF is the inability to extrapolate beyond the range of values represented in the training data. We assessed the number and severity of such out-of-observation-range (OOOR) days in both studies, which showed that there were few OOOR days in the second study and that uncertainties associated with OOOR days were small before 2070 in the third study. As the pre-processed data and model code have been made publically available, future studies can easily test further approaches or apply QRF to further catchments.},
  language  = {en}
}
@phdthesis{Popp2007,
  author    = {Popp, Alexander},
  title     = {An integrated modelling approach for sustainable management of semi-arid and arid rangelands},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-15103},
  school      = {Universit{\"a}t Potsdam},
  year      = {2007},
  abstract  = {The need to develop sustainable resource management strategies for semi-arid and arid rangelands is acute as non-adapted grazing strategies lead to irreversible environmental problems such as desertification and associated loss of economic support to society. In such vulnerable ecosystems, successful implementation of sustainable management strategies depends on well-founded under-standing of processes at different scales that underlay the complex system dynamic. There is ample evidence that, in contrast to traditional sectoral approaches, only interdisciplinary research does work for resolving problems in conservation and natural resource management. In this thesis I combined a range of modeling approaches that integrate different disciplines and spatial scales in order to contribute to basic guidelines for sustainable management of semi-arid and arid range-lands. Since water availability and livestock management are seen as most potent determinants for the dynamics of semi-arid and arid ecosystems I focused on (i) the interaction of ecological and hydro-logical processes and (ii) the effect of farming strategies. First, I developed a grid-based and small-scaled model simulating vegetation dynamics and inter-linked hydrological processes. The simulation results suggest that ecohydrological interactions gain importance in rangelands with ascending slope where vegetation cover serves to obstruct run-off and decreases evaporation from the soil. Disturbances like overgrazing influence these positive feedback mechanisms by affecting vegetation cover and composition. In the second part, I present a modeling approach that has the power to transfer and integrate ecological information from the small scale vegetation model to the landscape scale, most relevant for the conservation of biodiversity and sustainable management of natural resources. I combined techniques of stochastic modeling with remotely sensed data and GIS to investigate to which ex-tent spatial interactions, like the movement of surface water by run-off in water limited environments, affect ecosystem functioning at the landscape scale. My simulation experiments show that overgrazing decreases the number of vegetation patches that act as hydrological sinks and run-off increases. The results of both simulation models implicate that different vegetation types should not only be regarded as provider of forage production but also as regulator of ecosystem functioning. Vegetation patches with good cover of perennial vegetation are capable to catch and conserve surface run-off from degraded surrounding areas. Therefore, downstream out of the simulated system is prevented and efficient use of water resources is guaranteed at all times. This consequence also applies to commercial rotational grazing strategies for semi-arid and arid rangelands with ascending slope where non-degraded paddocks act as hydrological sinks. Finally, by the help of an integrated ecological-economic modeling approach, I analyzed the relevance of farmers' ecological knowledge for longterm functioning of semi-arid and arid grazing systems under current and future climatic conditions. The modeling approach consists of an ecological and an economic module and combines relevant processes on either level. Again, vegetation dynamics and forage productivity is derived by the small-scaled vegetation model. I showed that sustainable management of semi-arid and arid rangelands relies strongly on the farmers' knowledge on how the ecosystem works. Furthermore, my simulation results indicate that the projected lower annual rainfall due to climate change in combination with non-adapted grazing strategies adds an additional layer of risk to these ecosystems that are already prone to land degradation. All simulation models focus on the most essential factors and ignore specific details. Therefore, even though all simulation models are parameterized for a specific dwarf shrub savanna in arid southern Namibia, the conclusions drawn are applicable for semi-arid and arid rangelands in general.},
  language  = {en}
}
@phdthesis{MogrovejoArias2021,
  author    = {Mogrovejo Arias, Diana Carolina},
  title     = {Assessment of the frequency and relevance of potentially pathogenic phenotypes in microbial isolates from Arctic environments},
  school      = {Universit{\"a}t Potsdam},
  pages     = {125},
  year      = {2021},
  abstract  = {The Arctic environments constitute rich and dynamic ecosystems, dominated by microorganisms extremely well adapted to survive and function under severe conditions. A range of physiological adaptations allow the microbiota in these habitats to withstand low temperatures, low water and nutrient availability, high levels of UV radiation, etc. In addition, other adaptations of clear competitive nature are directed at not only surviving but thriving in these environments, by disrupting the metabolism of neighboring cells and affecting intermicrobial communication. Since Arctic microbes are bioindicators which amplify climate alterations in the environment, the Arctic region presents the opportunity to study local microbiota and carry out research about interesting, potentially virulent phenotypes that could be dispersed into other habitats around the globe as a consequence of accelerating climate change. In this context, exploration of Arctic habitats as well as descriptions of the microbes inhabiting them are abundant but microbial competitive strategies commonly associated with virulence and pathogens are rarely reported. In this project, environmental samples from the Arctic region were collected and microorganisms (bacteria and fungi) were isolated. The clinical relevance of these microorganisms was assessed by observing the following virulence markers: ability to grow at a range of temperatures, expression of antimicrobial resistance and production of hemolysins. The aim of this project is to determine the frequency and relevance of these characteristics in an effort to understand microbial adaptations in habitats threatened by climate change. The isolates obtained and described here were able to grow at a range of temperatures, in some cases more than 30 °C higher than their original isolation temperature. A considerable number of them consistently expressed compounds capable of lysing sheep and bovine erythrocytes on blood agar at different incubation temperatures. Ethanolic extracts of these bacteria were able to cause rapid and complete lysis of erythrocyte suspensions and might even be hemolytic when assayed on human blood. In silico analyses showed a variety of resistance elements, some of them novel, against natural and synthetic antimicrobial compounds. In vitro experiments against a number of antimicrobial compounds showed resistance phenotypes belonging to wild-type populations and some non-wild type which clearly denote human influence in the acquisition of antimicrobial resistance. The results of this project demonstrate the presence of virulence-associated factors expressed by microorganisms of natural, non-clinical environments. This study contains some of the first reports, to the best of our knowledge, of hemolytic microbes isolated from the Arctic region. In addition, it provides additional information about the presence and expression of intrinsic and acquired antimicrobial resistance in environmental isolates, contributing to the understanding of the evolution of relevant pathogenic species and opportunistic pathogens. Finally, this study highlights some of the potential risks associated with changes in the polar regions (habitat melting and destruction, ecosystem transition and re-colonization) as important indirect consequences of global warming and altered climatic conditions around the planet.},
  language  = {en}
}
@phdthesis{Courtin2023,
  author    = {Courtin, J{\´e}r{\´e}my},
  title     = {Biodiversity changes in Siberia between quaternary glacial and interglacial stages},
  doi       = {10.25932/publishup-59584},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-595847},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vi, 199},
  year      = {2023},
  abstract  = {Der vom Menschen verursachte Klimawandel wirkt sich auf die biologische Vielfalt der Erde und damit auf die {\"O}kosysteme und ihre Leistungen aus. Die {\"O}kosysteme in den hohen Breitengraden sind aufgrund der verst{\"a}rkten Erw{\"a}rmung an den Polen noch st{\"a}rker betroffen als der Rest der n{\"o}rdlichen Hemisph{\"a}re. Dennoch ist es schwierig, die Dynamik von {\"O}kosystemen in den hohen Breitengraden vorherzusagen, da die Wechselwirkungen zwischen abiotischen und biotischen Komponenten sehr komplex sind. Da die Vergangenheit der Schl{\"u}ssel zur Zukunft ist, ist die Interpretation vergangener {\"o}kologischer Ver{\"a}nderungen m{\"o}glich, um laufende Prozesse besser zu verstehen. Im Quart{\"a}r durchlief das Pleistoz{\"a}n mehrere glaziale und interglaziale Phasen, welche die {\"O}kosysteme der Vergangenheit beeinflussten. W{\"a}hrend des letzten Glazials bedeckte die pleistoz{\"a}ne Steppentundra den gr{\"o}ßten Teil der unvergletscherten n{\"o}rdlichen Hemisph{\"a}re und verschwand parallel zum Aussterben der Megafauna am {\"U}bergang zum Holoz{\"a}n (vor etwa 11 700 Jahren). Der Ursprung des R{\"u}ckgangs der Steppentundra ist nicht gut erforscht, und die Kenntnis {\"u}ber die Mechanismen, die zu den Ver{\"a}nderungen in den vergangenen Lebensgemeinschaften und {\"O}kosystemen gef{\"u}hrt haben, ist von hoher Priorit{\"a}t, da sie wahrscheinlich mit denen vergleichbar sind, die sich auf moderne {\"O}kosysteme auswirken. Durch die Entnahme von See- oder Permafrostkernsedimenten kann die vergangene Artenvielfalt an den {\"U}berg{\"a}ngen zwischen Eis- und Zwischeneiszeiten untersucht werden. Sibirien und Beringia waren der Ursprung der Ausbreitung der Steppentundra, weshalb die Untersuchung dieses Gebiets hohe Priorit{\"a}t hat. Bis vor kurzem waren Makrofossilien und Pollen die g{\"a}ngigsten Methoden. Sie dienen der Rekonstruktion vergangener Ver{\"a}nderungen in der Zusammensetzung der Bev{\"o}lkerung, haben aber ihre Grenzen und Schw{\"a}chen. Seit Ende des 20. Jahrhunderts kann auch sediment{\"a}re alte DNA (sedaDNA) untersucht werden. Mein Hauptziel war es, durch den Einsatz von sedaDNA-Ans{\"a}tzen wissenschaftliche Beweise f{\"u}r Ver{\"a}nderungen in der Zusammensetzung und Vielfalt der {\"O}kosysteme der n{\"o}rdlichen Hemisph{\"a}re am {\"U}bergang zwischen den quart{\"a}ren Eiszeiten und Zwischeneiszeiten zu liefern. In dieser Arbeit liefere ich Momentaufnahmen ganzer alter {\"O}kosysteme und beschreibe die Ver{\"a}nderungen in der Zusammensetzung zwischen Quart{\"a}rglazialen und Interglazialen und best{\"a}tige die Vegetationszusammensetzung sowie die r{\"a}umlichen und zeitlichen Grenzen der pleistoz{\"a}nen Steppentundra. Ich stelle einen allgemeinen Verlust der Pflanzenvielfalt fest, wobei das Aussterben der Pflanzen parallel zum Aussterben der Megafauna verlief. Ich zeige auf, wie der Verlust der biotischen Widerstandsf{\"a}higkeit zum Zusammenbruch eines zuvor gut etablierten Systems f{\"u}hrte, und diskutiere meine Ergebnisse im Hinblick auf den laufenden Klimawandel. Mit weiteren Arbeiten zur Eingrenzung von Verzerrungen und Grenzen kann sedaDNA parallel zu den etablierteren Makrofossilien- und Pollenans{\"a}tzen verwendet werden oder diese sogar ersetzen, da meine Ergebnisse die Robustheit und das Potenzial von sedaDNA zur Beantwortung neuer pal{\"a}o{\"o}kologischer Fragen wie Ver{\"a}nderungen der Pflanzenvielfalt und -verluste belegen und Momentaufnahmen ganzer alter Biota liefern.},
  language  = {en}
}
@phdthesis{Grosse2005,
  author    = {Grosse, Guido},
  title     = {Characterisation and evolution of periglacial landscapes in Northern Siberia during the Late Quaternary : remote sensing and GIS studies},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-5544},
  school      = {Universit{\"a}t Potsdam},
  year      = {2005},
  abstract  = {About 24 \% of the land surface in the northern hemisphere are underlayed by permafrost in various states. Permafrost aggradation occurs under special environmental conditions with overall low annual precipitation rates and very low mean annual temperatures. Because the general permafrost occurrence is mainly driven by large-scale climatic conditions, the distribution of permafrost deposits can be considered as an important climate indicator. The region with the most extensive continuous permafrost is Siberia. In northeast Siberia, the ice- and organic-rich permafrost deposits of the Ice Complex are widely distributed. These deposits consist mostly of silty to fine-grained sandy sediments that were accumulated during the Late Pleistocene in an extensive plain on the then subaerial Laptev Sea shelf. One important precondition for the Ice Complex sedimentation was, that the Laptev Sea shelf was not glaciated during the Late Pleistocene, resulting in a mostly continuous accumulation of permafrost sediments for at least this period. This shelf landscape became inundated and eroded in large parts by the Holocene marine transgression after the Last Glacial Maximum. Remnants of this landscape are preserved only in the present day coastal areas. Because the Ice Complex deposits contain a wide variety of palaeo-environmental proxies, it is an excellent palaeo-climate archive for the Late Quaternary in the region. Furthermore, the ice-rich Ice Complex deposits are sensible to climatic change, i.e. climate warming. Because of the large-scale climatic changes at the transition from the Pleistocene to the Holocene, the Ice Complex was subject to extensive thermokarst processes since the Early Holocene. Permafrost deposits are not only an environmental indicator, but also an important climate factor. Tundra wetlands, which have developed in environments with aggrading permafrost, are considered a net sink for carbon, as organic matter is stored in peat or is syn-sedimentary frozen with permafrost aggradation. Contrary, the Holocene thermokarst development resulted in permafrost degradation and thus the release of formerly stored organic carbon. Modern tundra wetlands are also considered an important source for the climate-driving gas methane, originating mainly from microbial activity in the seasonal active layer. Most scenarios for future global climate development predict a strong warming trend especially in the Arctic. Consequently, for the understanding of how permafrost deposits will react and contribute to such scenarios, it is necessary to investigate and evaluate ice-rich permafrost deposits like the widespread Ice Complex as climate indicator and climate factor during the Late Quaternary. Such investigations are a pre-condition for the precise modelling of future developments in permafrost distribution and the influence of permafrost degradation on global climate. The focus of this work, which was conducted within the frame of the multi-disciplinary joint German-Russian research projects "Laptev Sea 2000" (1998-2002) and "Dynamics of Permafrost" (2003-2005), was twofold. First, the possibilities of using remote sensing and terrain modelling techniques for the observation of periglacial landscapes in Northeast Siberia in their present state was evaluated and applied to key sites in the Laptev Sea coastal lowlands. The key sites were situated in the eastern Laptev Sea (Bykovsky Peninsula and Khorogor Valley) and the western Laptev Sea (Cape Mamontovy Klyk region). For this task, techniques using CORONA satellite imagery, Landsat-7 satellite imagery, and digital elevation models were developed for the mapping of periglacial structures, which are especially indicative of permafrost degradation. The major goals were to quantify the extent of permafrost degradation structures and their distribution in the investigated key areas, and to establish techniques, which can be used also for the investigation of other regions with thermokarst occurrence. Geographical information systems were employed for the mapping, the spatial analysis, and the enhancement of classification results by rule-based stratification. The results from the key sites show, that thermokarst, and related processes and structures, completely re-shaped the former accumulation plain to a strongly degraded landscape, which is characterised by extensive deep depressions and erosional remnants of the Late Pleistocene surface. As a results of this rapid process, which in large parts happened within a short period during the Early Holocene, the hydrological and sedimentological regime was completely changed on a large scale. These events resulted also in a release of large amounts of organic carbon. Thermokarst is now the major component in the modern periglacial landscapes in terms of spatial extent, but also in its influence on hydrology, sedimentation and the development of vegetation assemblages. Second, the possibilities of using remote sensing and terrain modelling as a supplementary tool for palaeo-environmental reconstructions in the investigated regions were explored. For this task additionally a comprehensive cryolithological field database was developed for the Bykovsky Peninsula and the Khorogor Valley, which contains previously published data from boreholes, outcrops sections, subsurface samples, and subsurface samples, as well as additional own field data. The period covered by this database is mainly the Late Pleistocene and the Holocene, but also the basal deposits of the sedimentary sequence, interpreted as Pliocene to Early Pleistocene, are contained. Remote sensing was applied for the observation of periglacial strucures, which then were successfully related to distinct landscape development stages or time intervals in the investigation area. Terrain modelling was used for providing a general context of the landscape development. Finally, a scheme was developed describing mainly the Late Quaternary landscape evolution in this area. A major finding was the possibility of connecting periglacial surface structures to distinct landscape development stages, and thus use them as additional palaeo-environmental indicator together with other proxies for area-related palaeo-environmental reconstructions. In the landscape evolution scheme, i.e. of the genesis of the Late Pleistocene Ice Complex and the Holocene thermokarst development, some new aspects are presented in terms of sediment source and general sedimentation conditions. This findings apply also for other sites in the Laptev Sea region.},
  subject      = {Dauerfrostboden},
  language  = {en}
}
@phdthesis{Gudipudi2017,
  author    = {Gudipudi, Venkata Ramana},
  title     = {Cities and global sustainability},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407113},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxii, 101},
  year      = {2017},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Olonscheck2016,
  author    = {Olonscheck, Mady},
  title     = {Climate change impacts on electricity and residential energy demand},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-98378},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XXIV, 127},
  year      = {2016},
  abstract  = {The energy sector is both affected by climate change and a key sector for climate protection measures. Energy security is the backbone of our modern society and guarantees the functioning of most critical infrastructure. Thus, decision makers and energy suppliers of different countries should be familiar with the factors that increase or decrease the susceptibility of their electricity sector to climate change. Susceptibility means socioeconomic and structural characteristics of the electricity sector that affect the demand for and supply of electricity under climate change. Moreover, the relevant stakeholders are supposed to know whether the given national energy and climate targets are feasible and what needs to be done in order to meet these targets. In this regard, a focus should be on the residential building sector as it is one of the largest energy consumers and therefore emitters of anthropogenic CO 2 worldwide. This dissertation addresses the first aspect, namely the susceptibility of the electricity sector, by developing a ranked index which allows for quantitative comparison of the electricity sector susceptibility of 21 European countries based on 14 influencing factors. Such a ranking has not been completed to date. We applied a sensitivity analysis to test the relative effect of each influencing factor on the susceptibility index ranking. We also discuss reasons for the ranking position and thus the susceptibility of selected countries. The second objective, namely the impact of climate change on the energy demand of buildings, is tackled by means of a new model with which the heating and cooling energy demand of residential buildings can be estimated. We exemplarily applied the model to Germany and the Netherlands. It considers projections of future changes in population, climate and the insulation standards of buildings, whereas most of the existing studies only take into account fewer than three different factors that influence the future energy demand of buildings. Furthermore, we developed a comprehensive retrofitting algorithm with which the total residential building stock can be modeled for the first time for each year in the past and future. The study confirms that there is no correlation between the geographical location of a country and its position in the electricity sector susceptibility ranking. Moreover, we found no pronounced pattern of susceptibility influencing factors between countries that ranked higher or lower in the index. We illustrate that Luxembourg, Greece, Slovakia and Italy are the countries with the highest electricity sector susceptibility. The electricity sectors of Norway, the Czech Republic, Portugal and Denmark were found to be least susceptible to climate change. Knowledge about the most important factors for the poor and good ranking positions of these countries is crucial for finding adequate adaptation measures to reduce the susceptibility of the electricity sector. Therefore, these factors are described within this study. We show that the heating energy demand of residential buildings will strongly decrease in both Germany and the Netherlands in the future. The analysis for the Netherlands focused on the regional level and a finer temporal resolution which revealed strong variations in the future heating energy demand changes by province and by month. In the German study, we additionally investigated the future cooling energy demand and could demonstrate that it will only slightly increase up to the middle of this century. Thus, increases in the cooling energy demand are not expected to offset reductions in heating energy demand. The main factor for substantial heating energy demand reductions is the retrofitting of buildings. We are the first to show that the given German and Dutch energy and climate targets in the building sector can only be met if the annual retrofitting rates are substantially increased. The current rate of only about 1 \% of the total building stock per year is insufficient for reaching a nearly zero-energy demand of all residential buildings by the middle of this century. To reach this target, it would need to be at least tripled. To sum up, this thesis emphasizes that country-specific characteristics are decisive for the electricity sector susceptibility of European countries. It also shows for different scenarios how much energy is needed in the future to heat and cool residential buildings. With this information, existing climate mitigation and adaptation measures can be justified or new actions encouraged.},
  language  = {en}
}
@phdthesis{Holsten2013,
  author    = {Holsten, Anne},
  title     = {Climate change vulnerability assessments in the regional context},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-66836},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {Adapting sectors to new conditions under climate change requires an understanding of regional vulnerabilities. Conceptually, vulnerability is defined as a function of sensitivity and exposure, which determine climate impacts, and adaptive capacity of a system. Vulnerability assessments for quantifying these components have become a key tool within the climate change field. However, there is a disagreement on how to make the concept operational in studies from a scientific perspective. This conflict leads to many still unsolved challenges, especially regarding the quantification and aggregation of the components and their suitable level of complexity. This thesis therefore aims at advancing the scientific foundation of such studies by translating the concept of vulnerability into a systematic assessment structure. This includes all components and implies that for each considered impact (e.g. flash floods) a clear sensitive entity is defined (e.g. settlements) and related to a direction of change for a specific climatic stimulus (e.g. increasing impact due to increasing days with heavy precipitation). Regarding the challenging aggregation procedure, two alternative methods allowing a cross-sectoral overview are introduced and their advantages and disadvantages discussed. This assessment structure is subsequently exemplified for municipalities of the German state North Rhine-Westphalia via an indicator-based deductive approach using information from literature. It can be transferred also to other regions. As for many relevant sectors, suitable indicators to express the vulnerability components are lacking, new quantification methods are developed and applied in this thesis, for example for the forestry and health sector. A lack of empirical data on relevant thresholds is evident, for example which climatic changes would cause significant impacts. Consequently, the multi-sectoral study could only provide relative measures for each municipality, in relation to the region. To fill this gap, an exemplary sectoral study was carried out on windthrow impacts in forests to provide an absolute quantification of the present and future impact. This is achieved by formulating an empirical relation between the forest characteristics and damage based on data from a past storm event. The resulting measure indicating the sensitivity is then combined with wind conditions. Multi-sectoral vulnerability assessments require considerable resources, which often hinders the implementation. Thus, in a next step, the potential for reducing the complexity is explored. To predict forest fire occurrence, numerous meteorological indices are available, spanning over a range of complexity. Comparing their performance, the single variable relative humidity outperforms complex indicators for most German states in explaining the monthly fire pattern. This is the case albeit it is itself an input factor in most indices. Thus, this meteorological factor alone is well suited to evaluate forest fire danger in many Germany regions and allows a resource-efficient assessment. Similarly, the complexity of methods is assessed regarding the application of the ecohydrological model SWIM to the German region of Brandenburg. The inter-annual soil moisture levels simulated by this model can only poorly be represented by simpler statistical approach using the same input data. However, on a decadal time horizon, the statistical approach shows a good performance and a strong dominance of the soil characteristic field capacity. This points to a possibility to reduce the input factors for predicting long-term averages, but the results are restricted by a lack of empirical data on soil water for validation. The presented assessments of vulnerability and its components have shown that they are still a challenging scientific undertaking. Following the applied terminology, many problems arise when implementing it for regional studies. Advances in addressing shortcomings of previous studies have been made by constructing a new systematic structure for characterizing and aggregating vulnerability components. For this, multiple approaches were presented, but they have specific advantages and disadvantages, which should also be carefully considered in future studies. There is a potential to simplify some methods, but more systematic assessments on this are needed. Overall, this thesis strengthened the use of vulnerability assessments as a tool to support adaptation by enhancing their scientific basis.},
  language  = {en}
}
@phdthesis{Schwager2005,
  author    = {Schwager, Monika},
  title     = {Climate change, variable colony sizes and temporal autocorrelation : consequences of living in changing environments},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-5744},
  school      = {Universit{\"a}t Potsdam},
  year      = {2005},
  abstract  = {Natural and human induced environmental changes affect populations at different time scales. If they occur in a spatial heterogeneous way, they cause spatial variation in abundance. In this thesis I addressed three topics, all related to the question, how environmental changes influence population dynamics. In the first part, I analysed the effect of positive temporal autocorrelation in environmental noise on the extinction risk of a population, using a simple population model. The effect of autocorrelation depended on the magnitude of the effect of single catastrophic events of bad environmental conditions on a population. If a population was threatened by extinction only, when bad conditions occurred repeatedly, positive autocorrelation increased extinction risk. If a population could become extinct, even if bad conditions occurred only once, positive autocorrelation decreased extinction risk. These opposing effects could be explained by two features of an autocorrelated time series. On the one hand, positive autocorrelation increased the probability of series of bad environmental conditions, implying a negative effect on populations. On the other hand, aggregation of bad years also implied longer periods with relatively good conditions. Therefore, for a given time period, the overall probability of occurrence of at least one extremely bad year was reduced in autocorrelated noise. This can imply a positive effect on populations. The results could solve a contradiction in the literature, where opposing effects of autocorrelated noise were found in very similar population models. In the second part, I compared two approaches, which are commonly used for predicting effects of climate change on future abundance and distribution of species: a "space for time approach", where predictions are based on the geographic pattern of current abundance in relation to climate, and a "population modelling approach" which is based on correlations between demographic parameters and the inter-annual variation of climate. In this case study, I compared the two approaches for predicting the effect of a shift in mean precipitation on a population of the sociable weaver Philetairus socius, a common colonially living passerine bird of semiarid savannahs of southern Africa. In the space for time approach, I compared abundance and population structure of the sociable weaver in two areas with highly different mean annual precipitation. The analysis showed no difference between the two populations. This result, as well as the wide distribution range of the species, would lead to the prediction of no sensitive response of the species to a slight shift in mean precipitation. In contrast, the population modelling approach, based on a correlation between reproductive success and rainfall, predicted a sensitive response in most model types. The inconsistency of predictions was confirmed in a cross-validation between the two approaches. I concluded that the inconsistency was caused, because the two approaches reflect different time scales. On a short time scale, the population may respond sensitively to rainfall. However, on a long time scale, or in a regional comparison, the response may be compensated or buffered by a variety of mechanisms. These may include behavioural or life history adaptations, shifts in the interactions with other species, or differences in the physical environment. The study implies that understanding, how such mechanisms work, and at what time scale they would follow climate change, is a crucial precondition for predicting ecological consequences of climate change. In the third part of the thesis, I tested why colony sizes of the sociable weaver are highly variable. The high variation of colony sizes is surprising, as in studies on coloniality it is often assumed that an optimal colony size exists, in which individual bird fitness is maximized. Following this assumption, the pattern of bird dispersal should keep colony sizes near an optimum. However, I showed by analysing data on reproductive success and survival that for the sociable weaver fitness in relation to colony size did not follow an optimum curve. Instead, positive and negative effects of living in large colonies overlaid each other in a way that fitness was generally close to one, and density dependence was low. I showed in a population model, which included an evolutionary optimisation process of dispersal that this specific shape of the fitness function could lead to a dispersal strategy, where the variation of colony sizes was maintained.},
  subject      = {Populationsbiologie},
  language  = {en}
}
@phdthesis{Huber2010,
  author    = {Huber, Veronika Emilie Charlotte},
  title     = {Climate impact on phytoplankton blooms in shallow lakes},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-42346},
  school      = {Universit{\"a}t Potsdam},
  year      = {2010},
  abstract  = {Lake ecosystems across the globe have responded to climate warming of recent decades. However, correctly attributing observed changes to altered climatic conditions is complicated by multiple anthropogenic influences on lakes. This thesis contributes to a better understanding of climate impacts on freshwater phytoplankton, which forms the basis of the food chain and decisively influences water quality. The analyses were, for the most part, based on a long-term data set of physical, chemical and biological variables of a shallow, polymictic lake in north-eastern Germany (M{\"u}ggelsee), which was subject to a simultaneous change in climate and trophic state during the past three decades. Data analysis included constructing a dynamic simulation model, implementing a genetic algorithm to parameterize models, and applying statistical techniques of classification tree and time-series analysis. Model results indicated that climatic factors and trophic state interactively determine the timing of the phytoplankton spring bloom (phenology) in shallow lakes. Under equally mild spring conditions, the phytoplankton spring bloom collapsed earlier under high than under low nutrient availability, due to a switch from a bottom-up driven to a top-down driven collapse. A novel approach to model phenology proved useful to assess the timings of population peaks in an artificially forced zooplankton-phytoplankton system. Mimicking climate warming by lengthening the growing period advanced algal blooms and consequently also peaks in zooplankton abundance. Investigating the reasons for the contrasting development of cyanobacteria during two recent summer heat wave events revealed that anomalously hot weather did not always, as often hypothesized, promote cyanobacteria in the nutrient-rich lake studied. The seasonal timing and duration of heat waves determined whether critical thresholds of thermal stratification, decisive for cyanobacterial bloom formation, were crossed. In addition, the temporal patterns of heat wave events influenced the summer abundance of some zooplankton species, which as predators may serve as a buffer by suppressing phytoplankton bloom formation. This thesis adds to the growing body of evidence that lake ecosystems have strongly responded to climatic changes of recent decades. It reaches beyond many previous studies of climate impacts on lakes by focusing on underlying mechanisms and explicitly considering multiple environmental changes. Key findings show that climate impacts are more severe in nutrient-rich than in nutrient-poor lakes. Hence, to develop lake management plans for the future, limnologists need to seek a comprehensive, mechanistic understanding of overlapping effects of the multi-faceted human footprint on aquatic ecosystems.},
  language  = {en}
}