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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.
Stochastic information, to be understood as "information gained by the application of stochastic methods", is proposed as a tool in the assessment of changes in climate. This thesis aims at demonstrating that stochastic information can improve the consideration and reduction of uncertainty in the assessment of changes in climate. The thesis consists of three parts. In part one, an indicator is developed that allows the determination of the proximity to a critical threshold. In part two, the tolerable windows approach (TWA) is extended to a probabilistic TWA. In part three, an integrated assessment of changes in flooding probability due to climate change is conducted within the TWA. The thermohaline circulation (THC) is a circulation system in the North Atlantic, where the circulation may break down in a saddle-node bifurcation under the influence of climate change. Due to uncertainty in ocean models, it is currently very difficult to determine the distance of the THC to the bifurcation point. We propose a new indicator to determine the system's proximity to the bifurcation point by considering the THC as a stochastic system and using the information contained in the fluctuations of the circulation around the mean state. As the system is moved closer to the bifurcation point, the power spectrum of the overturning becomes "redder", i.e. more energy is contained in the low frequencies. Since the spectral changes are a generic property of the saddle-node bifurcation, the method is not limited to the THC, but it could also be applicable to other systems, e.g. transitions in ecosystems. In part two, a probabilistic extension to the tolerable windows approach (TWA) is developed. In the TWA, the aim is to determine the complete set of emission strategies that are compatible with so-called guardrails. Guardrails are limits to impacts of climate change or to climate change itself. Therefore, the TWA determines the "maneuvering space" humanity has, if certain impacts of climate change are to be avoided. Due to uncertainty it is not possible to definitely exclude the impacts of climate change considered, but there will always be a certain probability of violating a guardrail. Therefore the TWA is extended to a probabilistic TWA that is able to consider "probabilistic uncertainty", i.e. uncertainty that can be expressed as a probability distribution or uncertainty that arises through natural variability. As a first application, temperature guardrails are imposed, and the dependence of emission reduction strategies on probability distributions for climate sensitivities is investigated. The analysis suggests that it will be difficult to observe a temperature guardrail of 2°C with high probabilities of actually meeting the target. In part three, an integrated assessment of changes in flooding probability due to climate change is conducted. A simple hydrological model is presented, as well as a downscaling scheme that allows the reconstruction of the spatio-temporal natural variability of temperature and precipitation. These are used to determine a probabilistic climate impact response function (CIRF), a function that allows the assessment of changes in probability of certain flood events under conditions of a changed climate. The assessment of changes in flooding probability is conducted in 83 major river basins. Not all floods can be considered: Events that either happen very fast, or affect only a very small area can not be considered, but large-scale flooding due to strong longer-lasting precipitation events can be considered. Finally, the probabilistic CIRFs obtained are used to determine emission corridors, where the guardrail is a limit to the fraction of world population that is affected by a predefined shift in probability of the 50-year flood event. This latter analysis has two main results. The uncertainty about regional changes in climate is still very high, and even small amounts of further climate change may lead to large changes in flooding probability in some river systems.
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.